diff --git a/.github/workflows/tests-mssql.yml b/.github/workflows/tests-mssql.yml new file mode 100644 index 0000000..8bedf8f --- /dev/null +++ b/.github/workflows/tests-mssql.yml @@ -0,0 +1,64 @@ +--- +name: mssql integration tests +on: + pull_request: + workflow_dispatch: + +env: + PYTHON_VERSION: "3.10" + MSSQL_SA_PASSWORD: "Datafaker!Test123" + +jobs: + mssql-tests: + runs-on: ubuntu-latest + + services: + mssql: + image: mcr.microsoft.com/mssql/server:2022-latest + env: + ACCEPT_EULA: "Y" + MSSQL_SA_PASSWORD: "Datafaker!Test123" + ports: + - 1433:1433 + options: >- + --health-cmd "/opt/mssql-tools18/bin/sqlcmd -S localhost -U sa -P 'Datafaker!Test123' -Q 'SELECT 1' -No" + --health-interval 10s + --health-timeout 5s + --health-retries 12 + --health-start-period 30s + + steps: + - name: Checkout Code + uses: actions/checkout@v6 + + - name: Install ODBC Driver 18 for SQL Server + shell: bash + run: | + curl -fsSL https://packages.microsoft.com/keys/microsoft.asc \ + | sudo gpg --dearmor -o /usr/share/keyrings/microsoft-prod.gpg + curl -fsSL "https://packages.microsoft.com/config/ubuntu/$(lsb_release -rs)/prod.list" \ + | sudo tee /etc/apt/sources.list.d/mssql-release.list + sudo apt-get update + ACCEPT_EULA=Y sudo apt-get install -y msodbcsql18 + + - name: Install poetry + shell: bash + run: | + sudo apt install python3-poetry + + - name: Configure poetry + shell: bash + run: | + python -m poetry config virtualenvs.in-project true + + - name: Install dependencies (with mssql extras) + shell: bash + run: | + python -m poetry install --extras mssql + + - name: Run MS-SQL integration tests + shell: bash + env: + MSSQL_TEST_DSN: "mssql+pyodbc://sa:Datafaker!Test123@localhost:1433/master?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes" + run: | + poetry run python -m unittest tests.test_functional_mssql -v diff --git a/datafaker/create.py b/datafaker/create.py index 849a1ec..0300ded 100644 --- a/datafaker/create.py +++ b/datafaker/create.py @@ -36,6 +36,22 @@ serial_re = re.compile(r"\bSERIAL\b") + +@compiles(CreateTable, "mssql") +def remove_mssql_on_delete_cascade(element: CreateTable, compiler: Any, **kw: Any) -> str: + """ + Strip ON DELETE CASCADE from MS-SQL table DDL. + + MS-SQL rejects multiple cascading FK paths to the same table (error 1785). + OMOP-style schemas commonly have many FK columns on one table all pointing at + the same vocabulary table, which triggers this limit. Dropping CASCADE is + safe for datafaker because referential integrity is enforced by insert order, + not by the database engine. + """ + text: str = compiler.visit_create_table(element, **kw) + return text.replace(" ON DELETE CASCADE", "") + + @compiles(CreateTable, "duckdb") def remove_on_delete_cascade(element: CreateTable, compiler: Any, **kw: Any) -> str: """ @@ -194,7 +210,7 @@ def create_db_data_into( :param metadata: Destination database metadata. """ dst_engine = get_sync_engine(create_db_engine_dst(db_dsn, schema_name=schema_name)) - gen_info = get_generation_info(metadata, config) + gen_info = get_generation_info(metadata, config, dst_engine.dialect.name) context = get_symbols( gen_info.row_generator_module_name, gen_info.story_generator_module_name, diff --git a/datafaker/db_utils.py b/datafaker/db_utils.py index 19233cc..253b53b 100644 --- a/datafaker/db_utils.py +++ b/datafaker/db_utils.py @@ -38,6 +38,7 @@ get_ignored_table_names, get_vocabulary_table_names, logger, + make_async_dsn, make_foreign_key_name, ) @@ -139,10 +140,10 @@ def create_db_engine( **kwargs: Any, ) -> MaybeAsyncEngine: """Create a SQLAlchemy Engine.""" + kwargs.setdefault("pool_pre_ping", True) try: if use_asyncio: - async_dsn = db_dsn.replace("postgresql://", "postgresql+asyncpg://") - engine: MaybeAsyncEngine = create_async_engine(async_dsn, **kwargs) + engine: MaybeAsyncEngine = create_async_engine(make_async_dsn(db_dsn), **kwargs) else: engine = create_engine(db_dsn, **kwargs) except NoSuchModuleError as exc: @@ -155,7 +156,10 @@ def create_db_engine( settings = {} if schema_name is not None: - settings["search_path"] = schema_name + if get_sync_engine(engine).dialect.name == "mssql": + engine = engine.execution_options(schema_translate_map={None: schema_name}) + else: + settings["search_path"] = schema_name if parquet_dir is not None: joined = ",".join(_find_parquet_directories(parquet_dir)) # double up single quotes @@ -202,11 +206,11 @@ def create_db_engine_dst( return create_db_engine(db_dsn, schema_name, use_asyncio) -def get_metadata(engine: Engine) -> MetaData: +def get_metadata(engine: Engine, schema_name: Optional[str] = None) -> MetaData: """Get the MetaData object associated with the engine passed.""" md = MetaData() try: - md.reflect(engine) + md.reflect(engine, schema=schema_name) except OperationalError as exc: logger.error("Cannot connect to database: %s", exc) raise Exit(1) from exc diff --git a/datafaker/interactive/base.py b/datafaker/interactive/base.py index 5bf1a3a..c22b160 100644 --- a/datafaker/interactive/base.py +++ b/datafaker/interactive/base.py @@ -10,7 +10,7 @@ import sqlalchemy from prettytable import PrettyTable -from sqlalchemy import Engine, ForeignKey, MetaData, Table +from sqlalchemy import Engine, ForeignKey, MetaData, Table, func, literal_column, or_, select from sqlalchemy.exc import DatabaseError, SQLAlchemyError from typing_extensions import Self @@ -352,17 +352,13 @@ def do_counts(self, _arg: str) -> None: return table_name = self.table_name() nullable_columns = self.get_nullable_columns(table_name) - colcounts = [f', COUNT("{nnc}") AS "{nnc}"' for nnc in nullable_columns] + tbl = self.table_metadata() + count_exprs = [func.count().label("row_count")] + [ + func.count(tbl.c[col]).label(col) for col in nullable_columns + ] + stmt = select(*count_exprs).select_from(tbl) with self.sync_engine.connect() as connection: - result = ( - connection.execute( - sqlalchemy.text( - f'SELECT COUNT(*) AS row_count{"".join(colcounts)} FROM "{table_name}"' - ) - ) - .mappings() - .first() - ) + result = connection.execute(stmt).mappings().first() if result is None: self.print("Could not count rows in table {0}", table_name) return @@ -411,23 +407,27 @@ def do_peek(self, arg: str) -> None: max_peek_rows = 25 if len(self._table_entries) <= self.table_index: return - table_name = self.table_name() col_names = arg.split() if not col_names: col_names = self._get_column_names() - nonnulls = [f'"{cn}" IS NOT NULL' for cn in col_names] + random_fn = ( + func.newid() if self.sync_engine.dialect.name == "mssql" else func.random() + ) + table = self.table_metadata() + col_exprs = [table.columns[cn] for cn in col_names] + nonnull_clauses = [ce.isnot(None) for ce in col_exprs] + stmt = ( + select(*col_exprs) + .select_from(table) + .where(or_(*nonnull_clauses)) + .order_by(random_fn) + .limit(max_peek_rows) + ) with self.sync_engine.connect() as connection: - cols = ", ".join(f'"{cn}"' for cn in col_names) - where = "WHERE" if nonnulls else "" - nonnull = " OR ".join(nonnulls) - query = sqlalchemy.text( - f'SELECT {cols} FROM "{table_name}" {where} {nonnull}' - f" ORDER BY RANDOM() LIMIT {max_peek_rows}" - ) try: - result = connection.execute(query) + result = connection.execute(stmt) except SQLAlchemyError as exc: - self.print(self.ERROR_FAILED_SQL, exc=exc, query=query) + self.print(self.ERROR_FAILED_SQL, exc=exc, query=stmt) return self.print_table(list(result.keys()), result.fetchmany(max_peek_rows)) diff --git a/datafaker/interactive/generators.py b/datafaker/interactive/generators.py index e076e24..7e67449 100644 --- a/datafaker/interactive/generators.py +++ b/datafaker/interactive/generators.py @@ -6,7 +6,7 @@ from typing import Any, Callable, Optional, cast import sqlalchemy -from sqlalchemy import Column +from sqlalchemy import Column, and_, func, literal_column, select from datafaker.db_utils import MaybeAsyncEngine, primary_private_fks, table_is_private from datafaker.interactive.base import DbCmd, TableEntry, fk_column_name, or_default @@ -16,6 +16,7 @@ get_columns_assigned, get_row_generators, logger, + schema_qualified_name, split_column_full_name, ) @@ -61,8 +62,9 @@ def get_aggregate_query( ] if not clauses: return None + qualified = schema_qualified_name(table_name, engine) alias = f' AS "{table_name}"' if engine.dialect.name == "duckdb" else "" - return f'SELECT {", ".join(clauses)} FROM "{table_name}"{alias}' + return f'SELECT {", ".join(clauses)} FROM "{qualified}"{alias}' # pylint: disable=too-many-public-methods @@ -779,15 +781,20 @@ def _get_column_data( self, count: int, to_str: Callable[[Any], str] = repr ) -> list[list[str]]: columns = self._get_column_names() - columns_string = ", ".join(columns) - pred = " AND ".join(f"{column} IS NOT NULL" for column in columns) + random_fn = ( + func.newid() if self.sync_engine.dialect.name == "mssql" else func.random() + ) + col_exprs = [literal_column(col) for col in columns] + nonnull_clauses = [literal_column(col).isnot(None) for col in columns] + stmt = ( + select(*col_exprs) + .select_from(self.table_metadata()) + .where(and_(*nonnull_clauses)) + .order_by(random_fn) + .limit(count) + ) with self.sync_engine.connect() as connection: - result = connection.execute( - sqlalchemy.text( - f'SELECT {columns_string} FROM "{self.table_name()}"' - f" WHERE {pred} ORDER BY RANDOM() LIMIT {count}" - ) - ) + result = connection.execute(stmt) return [[to_str(x) for x in xs] for xs in result.all()] def do_propose(self, _arg: str) -> None: diff --git a/datafaker/interactive/missingness.py b/datafaker/interactive/missingness.py index 74eaaf6..361330d 100644 --- a/datafaker/interactive/missingness.py +++ b/datafaker/interactive/missingness.py @@ -23,19 +23,32 @@ class MissingnessType: columns: list[str] @classmethod - def sampled_query(cls, table: str, count: int, column_names: Iterable[str]) -> str: + def sampled_query( + cls, + table: str, + count: int, + column_names: Iterable[str], + dialect_name: str = "", + ) -> str: """ Construct a query to make a sampling of the named rows of the table. :param table: The name of the table to sample. :param count: The number of samples to get. :param column_names: The columns to fetch. + :param dialect_name: The SQLAlchemy dialect name (e.g. ``"mssql"``). :return: The SQL query to do the sampling. """ result_names = ", ".join([f"{c}__is_null" for c in column_names]) column_is_nulls = ", ".join( [f"{c} IS NULL AS {c}__is_null" for c in column_names] ) + if dialect_name == "mssql": + return ( + f"SELECT COUNT(*) AS row_count, {result_names} FROM " + f"(SELECT TOP {count} {column_is_nulls} FROM {table} ORDER BY NEWID())" + f" AS __t GROUP BY {result_names}" + ) return cls.SAMPLED_QUERY.format( result_names=result_names, column_is_nulls=column_is_nulls, @@ -330,6 +343,7 @@ def do_sampled(self, arg: str) -> None: entry.name, count, self.get_nullable_columns(entry.name), + dialect_name=self.sync_engine.dialect.name, ), [ "The missingness patterns and how often they appear in a" diff --git a/datafaker/interactive/table.py b/datafaker/interactive/table.py index c32913a..9a02177 100644 --- a/datafaker/interactive/table.py +++ b/datafaker/interactive/table.py @@ -4,6 +4,7 @@ from typing import Any, cast import sqlalchemy +from sqlalchemy import func, literal_column, select, text from datafaker.interactive.base import ( TYPE_LETTER, @@ -477,16 +478,23 @@ def print_column_data(self, column: str, count: int, min_length: int) -> None: :param count: The number of rows to sample. :param min_length: The minimum length of text to choose from (0 for any text). """ - where = f"WHERE {column} IS NOT NULL" + random_fn = ( + func.newid() if self.sync_engine.dialect.name == "mssql" else func.random() + ) + col_expr = literal_column(column) if 0 < min_length: - where = f"WHERE LENGTH({column}) >= {min_length}" + where_clause = func.length(col_expr) >= min_length + else: + where_clause = col_expr.isnot(None) + stmt = ( + select(col_expr) + .select_from(self.table_metadata()) + .where(where_clause) + .order_by(random_fn) + .limit(count) + ) with self.sync_engine.connect() as connection: - result = connection.execute( - sqlalchemy.text( - f'SELECT {column} FROM "{self.table_name()}"' - f" {where} ORDER BY RANDOM() LIMIT {count}" - ) - ) + result = connection.execute(stmt) self.columnize([str(x[0]) for x in result.all()]) def print_row_data(self, count: int) -> None: @@ -495,12 +503,17 @@ def print_row_data(self, count: int) -> None: :param count: The number of rows to report. """ + random_fn = ( + func.newid() if self.sync_engine.dialect.name == "mssql" else func.random() + ) + stmt = ( + select(text("*")) + .select_from(self.table_metadata()) + .order_by(random_fn) + .limit(count) + ) with self.sync_engine.connect() as connection: - result = connection.execute( - sqlalchemy.text( - f'SELECT * FROM "{self.table_name()}" ORDER BY RANDOM() LIMIT {count}' - ) - ) + result = connection.execute(stmt) if result is None: self.print("No rows in this table!") return diff --git a/datafaker/main.py b/datafaker/main.py index baf2d49..3907004 100644 --- a/datafaker/main.py +++ b/datafaker/main.py @@ -24,10 +24,9 @@ TableWriter, get_parquet_table_writer, ) -from datafaker.interactive import ( +from datafaker.interactive import ( # update_missingness, update_config_generators, update_config_tables, - update_missingness, ) from datafaker.interactive.base import DbCmd from datafaker.make import make_src_stats, make_tables_file, make_vocabulary_tables @@ -39,6 +38,7 @@ get_source_dsn, get_source_schema, ) +from datafaker.serialize_metadata import dict_to_metadata, should_ignore_fk from datafaker.utils import ( CONFIG_SCHEMA_PATH, conf_logger, @@ -47,14 +47,12 @@ logger, read_config_file, ) - -from .serialize_metadata import dict_to_metadata, should_ignore_fk - # pylint: disable=too-many-arguments ORM_FILENAME: Final[str] = "orm.yaml" CONFIG_FILENAME: Final[str] = "config.yaml" STATS_FILENAME: Final[str] = "src-stats.yaml" +DF_FILENAME: Final[str] = "df.py" app = Typer(no_args_is_help=True) @@ -143,169 +141,44 @@ def main( conf_logger(verbose) -@app.command() -def create_data( - orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), - config_file: Optional[Path] = Option( - CONFIG_FILENAME, - help="The configuration file", +@app.command(rich_help_panel="Configure") +def make_tables( + orm_file: Path = Option(ORM_FILENAME, help="Path to write the ORM yaml file to"), + force: bool = Option( + False, "--force", "-f", help="Overwrite any existing orm yaml file." ), - stats_file: Optional[Path] = Option( + parquet_dir: Optional[Path] = Option( None, help=( - "Statistics file (output of make-stats); default is src-stats.yaml if the " - "config file references SRC_STATS, or None otherwise." + "Directory of Parquet files to consider part of the database." + " This can be useful when using DuckDB." + " Make sure you check the output!" ), - show_default=False, - dir_okay=False, - ), - num_passes: int = Option(1, help="Number of passes (rows or stories) to make"), -) -> None: - """Populate the schema in the target directory with synthetic data. - - This CLI command generates synthetic data for - Python table structures, and inserts these rows - into a destination schema. - - Also takes as input object relational model as represented - by file containing Python classes and its attributes. - - Takes as input datafaker output as represented by Python - classes, its attributes and methods for generating values - for those attributes. - - Final input is the number of rows required. - - Example: - $ datafaker create-data - """ - logger.debug("Creating data.") - config = read_config_file(config_file) if config_file is not None else {} - if stats_file is None and generators_require_stats(config): - stats_file = Path(STATS_FILENAME) - orm_metadata = load_metadata_for_output(orm_file, config) - try: - row_counts = create_db_data( - sorted_non_vocabulary_tables(orm_metadata, config), - config, - stats_file, - num_passes, - orm_metadata, - ) - logger.debug( - "Data created in %s %s.", - num_passes, - "pass" if num_passes == 1 else "passes", - ) - for table_name, row_count in row_counts.items(): - logger.debug( - "%s: %s %s created.", - table_name, - row_count, - "row" if row_count == 1 else "rows", - ) - return - except RuntimeError as e: - logger.error(e.args[0]) - except SettingsError as e: - logger.error(str(e)) - raise Exit(1) - - -@app.command() -def create_vocab( - orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), - config_file: Path = Option( - CONFIG_FILENAME, - help="The configuration file", - dir_okay=False, - ), -) -> None: - """Import vocabulary data into the target database. - - Example: - $ datafaker create-vocab - """ - logger.debug("Loading vocab.") - config = read_config_file(config_file) if config_file is not None else {} - meta_dict = load_metadata_config(orm_file, config) - orm_metadata = dict_to_metadata(meta_dict, config) - vocabs_loaded = create_db_vocab(orm_metadata, meta_dict, config) - num_vocabs = len(vocabs_loaded) - logger.debug("%s %s loaded.", num_vocabs, "table" if num_vocabs == 1 else "tables") - - -@app.command() -def create_tables( - orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), - config_file: Optional[Path] = Option( - CONFIG_FILENAME, - help="The configuration file", - dir_okay=False, + file_okay=False, + dir_okay=True, ), ) -> None: - """Create schema from the ORM YAML file. - - This CLI command creates the destination schema using object - relational model declared as Python tables. + """Make a YAML file representing the tables in the schema. Example: - $ datafaker create-tables + $ datafaker make_tables """ - logger.debug("Creating tables.") - config = read_config_file(config_file) if config_file is not None else {} - orm_metadata = load_metadata_for_output(orm_file, config) - create_db_tables(orm_metadata) - logger.debug("Tables created.") + logger.debug("Creating %s.", orm_file) + orm_file_path = Path(orm_file) + if not force: + _check_file_non_existence(orm_file_path) -@app.command() -def create_generators( - _orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), - _df_file: Path = Option( - None, - help="Path to write Python generators to.", - dir_okay=False, - ), - _config_file: Path = Option( - CONFIG_FILENAME, - help="The configuration file", - dir_okay=False, - ), - _stats_file: Optional[Path] = Option( - None, - help=( - "Statistics file (output of make-stats); default is src-stats.yaml if the " - "config file references SRC_STATS, or None otherwise." - ), - show_default=False, - dir_okay=False, - ), - _force: bool = Option( - False, "--force", "-f", help="Overwrite any existing Python generators file." - ), -) -> None: - """Obsolete command.""" - logger.error("This command is deprecated; it does nothing.") + content = make_tables_file( + get_source_dsn(), + get_source_schema(), + parquet_dir, + ) + orm_file_path.write_text(content, encoding="utf-8") + logger.debug("%s created.", orm_file) -@app.command() +@app.command(rich_help_panel="Configure") def make_vocab( orm_file: Path = Option( ORM_FILENAME, @@ -344,82 +217,7 @@ def make_vocab( ) -@app.command() -def make_stats( - orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), - config_file: Optional[Path] = Option( - CONFIG_FILENAME, - help="The configuration file", - dir_okay=False, - ), - stats_file: Path = Option(STATS_FILENAME), - force: bool = Option( - False, "--force", "-f", help="Overwrite any existing vocabulary file." - ), -) -> None: - """Compute summary statistics from the source database.""" - logger.debug("Creating %s.", stats_file) - - if not force: - _check_file_non_existence(stats_file) - - config = read_config_file(config_file) if config_file is not None else {} - meta_dict = load_metadata_config(orm_file, config) - - src_stats = asyncio.get_event_loop().run_until_complete( - make_src_stats( - get_source_dsn(), - config, - get_source_schema(), - parquet_dir=meta_dict.get("parquet-dir", None), - ) - ) - stats_file.write_text(yaml.dump(src_stats), encoding="utf-8") - logger.debug("%s created.", stats_file) - - -@app.command() -def make_tables( - orm_file: Path = Option(ORM_FILENAME, help="Path to write the ORM yaml file to"), - force: bool = Option( - False, "--force", "-f", help="Overwrite any existing orm yaml file." - ), - parquet_dir: Optional[Path] = Option( - None, - help=( - "Directory of Parquet files to consider part of the database." - " This can be useful when using DuckDB." - " Make sure you check the output!" - ), - file_okay=False, - dir_okay=True, - ), -) -> None: - """Make a YAML file representing the tables in the schema. - - Example: - $ datafaker make_tables - """ - logger.debug("Creating %s.", orm_file) - - orm_file_path = Path(orm_file) - if not force: - _check_file_non_existence(orm_file_path) - - content = make_tables_file( - get_source_dsn(), - get_source_schema(), - parquet_dir, - ) - orm_file_path.write_text(content, encoding="utf-8") - logger.debug("%s created.", orm_file) - - -@app.command() +@app.command(rich_help_panel="Configure") def configure_tables( config_file: Path = Option( CONFIG_FILENAME, @@ -457,46 +255,7 @@ def configure_tables( logger.debug("Tables configured in %s.", config_file) -@app.command() -def configure_missing( - config_file: Path = Option( - CONFIG_FILENAME, - help="Path to write the configuration file to", - dir_okay=False, - ), - orm_file: Path = Option( - ORM_FILENAME, - help="The name of the ORM yaml file", - dir_okay=False, - ), -) -> None: - """Interactively set the missingness of the generated data.""" - logger.debug("Configuring missingness in %s.", config_file) - config: dict[str, Any] = {} - if config_file.exists(): - config_any = yaml.load( - config_file.read_text(encoding="UTF-8"), Loader=yaml.SafeLoader - ) - if isinstance(config_any, dict): - config = config_any - meta_dict = load_metadata_config(orm_file, config) - metadata = dict_to_metadata(meta_dict, None) - config_updated = update_missingness( - get_source_dsn(), - get_source_schema(), - metadata, - config, - Path(meta_dict["parquet-dir"]) if "parquet-dir" in meta_dict else None, - ) - if config_updated is None: - logger.debug("Cancelled") - return - content = yaml.dump(config_updated) - config_file.write_text(content, encoding="utf-8") - logger.debug("Missingness generators in %s.", config_file) - - -@app.command() +@app.command(rich_help_panel="Configure") def configure_generators( config_file: Path = Option( CONFIG_FILENAME, @@ -543,6 +302,206 @@ def configure_generators( logger.debug("Generators configured in %s.", config_file) +@app.command(rich_help_panel="Extract") +def make_stats( + orm_file: Path = Option( + ORM_FILENAME, + help="The name of the ORM yaml file", + dir_okay=False, + ), + config_file: Optional[Path] = Option( + CONFIG_FILENAME, + help="The configuration file", + dir_okay=False, + ), + stats_file: Path = Option(STATS_FILENAME), + force: bool = Option( + False, "--force", "-f", help="Overwrite any existing vocabulary file." + ), +) -> None: + """Compute summary statistics from the source database.""" + logger.debug("Creating %s.", stats_file) + + if not force: + _check_file_non_existence(stats_file) + + config = read_config_file(config_file) if config_file is not None else {} + meta_dict = load_metadata_config(orm_file, config) + + src_stats = asyncio.get_event_loop().run_until_complete( + make_src_stats( + get_source_dsn(), + config, + get_source_schema(), + parquet_dir=meta_dict.get("parquet-dir", None), + ) + ) + stats_file.write_text(yaml.dump(src_stats), encoding="utf-8") + logger.debug("%s created.", stats_file) + + +@app.command(rich_help_panel="Create Synthetic Database") +def create_tables( + orm_file: Path = Option( + ORM_FILENAME, + help="The name of the ORM yaml file", + dir_okay=False, + ), + config_file: Optional[Path] = Option( + CONFIG_FILENAME, + help="The configuration file", + dir_okay=False, + ), +) -> None: + """Create schema from the ORM YAML file. + + This CLI command creates the destination schema using object + relational model declared as Python tables. + + Example: + $ datafaker create-tables + """ + logger.debug("Creating tables.") + config = read_config_file(config_file) if config_file is not None else {} + orm_metadata = load_metadata_for_output(orm_file, config) + create_db_tables(orm_metadata) + logger.debug("Tables created.") + + +@app.command(rich_help_panel="Create Synthetic Database") +def create_vocab( + orm_file: Path = Option( + ORM_FILENAME, + help="The name of the ORM yaml file", + dir_okay=False, + ), + config_file: Path = Option( + CONFIG_FILENAME, + help="The configuration file", + dir_okay=False, + ), +) -> None: + """Import vocabulary data into the target database. + + Example: + $ datafaker create-vocab + """ + logger.debug("Loading vocab.") + config = read_config_file(config_file) if config_file is not None else {} + meta_dict = load_metadata_config(orm_file, config) + orm_metadata = dict_to_metadata(meta_dict, config) + vocabs_loaded = create_db_vocab(orm_metadata, meta_dict, config) + num_vocabs = len(vocabs_loaded) + logger.debug("%s %s loaded.", num_vocabs, "table" if num_vocabs == 1 else "tables") + + +@app.command(rich_help_panel="Create Synthetic Database") +def create_generators( + _orm_file: Path = Option( + ORM_FILENAME, + help="The name of the ORM yaml file", + dir_okay=False, + ), + _df_file: Path = Option( + None, + help="Path to write Python generators to.", + dir_okay=False, + ), + _config_file: Path = Option( + CONFIG_FILENAME, + help="The configuration file", + dir_okay=False, + ), + _stats_file: Optional[Path] = Option( + None, + help=( + "Statistics file (output of make-stats); default is src-stats.yaml if the " + "config file references SRC_STATS, or None otherwise." + ), + show_default=False, + dir_okay=False, + ), + _force: bool = Option( + False, "--force", "-f", help="Overwrite any existing Python generators file." + ), +) -> None: + """Obsolete command.""" + logger.error("This command is deprecated; it does nothing.") + + +@app.command(rich_help_panel="Create Synthetic Database") +def create_data( + orm_file: Path = Option( + ORM_FILENAME, + help="The name of the ORM yaml file", + dir_okay=False, + ), + config_file: Optional[Path] = Option( + CONFIG_FILENAME, + help="The configuration file", + ), + stats_file: Optional[Path] = Option( + None, + help=( + "Statistics file (output of make-stats); default is src-stats.yaml if the " + "config file references SRC_STATS, or None otherwise." + ), + show_default=False, + dir_okay=False, + ), + num_passes: int = Option(1, help="Number of passes (rows or stories) to make"), +) -> None: + """Populate the schema in the target directory with synthetic data. + + This CLI command generates synthetic data for + Python table structures, and inserts these rows + into a destination schema. + + Also takes as input object relational model as represented + by file containing Python classes and its attributes. + + Takes as input datafaker output as represented by Python + classes, its attributes and methods for generating values + for those attributes. + + Final input is the number of rows required. + + Example: + $ datafaker create-data + """ + logger.debug("Creating data.") + config = read_config_file(config_file) if config_file is not None else {} + if stats_file is None and generators_require_stats(config): + stats_file = Path(STATS_FILENAME) + orm_metadata = load_metadata_for_output(orm_file, config) + try: + row_counts = create_db_data( + sorted_non_vocabulary_tables(orm_metadata, config), + config, + stats_file, + num_passes, + orm_metadata, + ) + logger.debug( + "Data created in %s %s.", + num_passes, + "pass" if num_passes == 1 else "passes", + ) + for table_name, row_count in row_counts.items(): + logger.debug( + "%s: %s %s created.", + table_name, + row_count, + "row" if row_count == 1 else "rows", + ) + return + except RuntimeError as e: + logger.error(e.args[0]) + except SettingsError as e: + logger.error(str(e)) + raise Exit(1) + + def convert_table_names_to_tables( table_names: list[str], metadata: MetaData ) -> list[Table]: @@ -612,7 +571,7 @@ def _dump_tables_to_directory( logger.warning("Failed to write %s", f) -@app.command() +@app.command(rich_help_panel="Inspect and Export") def dump_data( config_file: Optional[Path] = Option( CONFIG_FILENAME, @@ -674,7 +633,7 @@ def dump_data( _dump_tables_to_directory(writer, directory, mtables) -@app.command() +@app.command(rich_help_panel="Inspect and Export") def validate_config( config_file: Path = Argument(help="The configuration file to validate"), ) -> None: @@ -691,7 +650,7 @@ def validate_config( logger.debug("Config file is valid.") -@app.command() +@app.command(rich_help_panel="Remove") def remove_data( orm_file: Path = Option( ORM_FILENAME, @@ -718,7 +677,7 @@ def remove_data( logger.info("Would truncate non-vocabulary tables if called with --yes.") -@app.command() +@app.command(rich_help_panel="Remove") def remove_vocab( orm_file: Path = Option( ORM_FILENAME, @@ -746,7 +705,7 @@ def remove_vocab( logger.info("Would truncate vocabulary tables if called with --yes.") -@app.command() +@app.command(rich_help_panel="Remove") def remove_tables( orm_file: Path = Option( ORM_FILENAME, @@ -797,7 +756,7 @@ class TableType(str, Enum): GENERATED = "generated" -@app.command() +@app.command(rich_help_panel="Inspect and Export") def list_tables( orm_file: Path = Option( ORM_FILENAME, @@ -830,7 +789,7 @@ def list_tables( print(name) -@app.command() +@app.command(rich_help_panel="Inspect and Export") def version() -> None: """Display version information.""" assert __package__ is not None @@ -843,3 +802,42 @@ def version() -> None: if __name__ == "__main__": datafaker() + + +# @app.command(rich_help_panel="Discovery and Configuration") +# def configure_missing( +# config_file: Path = Option( +# CONFIG_FILENAME, +# help="Path to write the configuration file to", +# dir_okay=False, +# ), +# orm_file: Path = Option( +# ORM_FILENAME, +# help="The name of the ORM yaml file", +# dir_okay=False, +# ), +# ) -> None: +# """Interactively set the missingness of the generated data.""" +# logger.debug("Configuring missingness in %s.", config_file) +# config: dict[str, Any] = {} +# if config_file.exists(): +# config_any = yaml.load( +# config_file.read_text(encoding="UTF-8"), Loader=yaml.SafeLoader +# ) +# if isinstance(config_any, dict): +# config = config_any +# meta_dict = load_metadata_config(orm_file, config) +# metadata = dict_to_metadata(meta_dict, None) +# config_updated = update_missingness( +# get_source_dsn(), +# get_source_schema(), +# metadata, +# config, +# Path(meta_dict["parquet-dir"]) if "parquet-dir" in meta_dict else None, +# ) +# if config_updated is None: +# logger.debug("Cancelled") +# return +# content = yaml.dump(config_updated) +# config_file.write_text(content, encoding="utf-8") +# logger.debug("Generators missingness in %s.", config_file) diff --git a/datafaker/make.py b/datafaker/make.py index 88d3b38..3041eee 100644 --- a/datafaker/make.py +++ b/datafaker/make.py @@ -14,8 +14,8 @@ import typer import yaml from mimesis.providers.base import BaseProvider -from sqlalchemy import CursorResult, Engine, MetaData, text -from sqlalchemy.dialects import postgresql +from sqlalchemy import CursorResult, Engine, Integer, MetaData, UniqueConstraint, text +from sqlalchemy.dialects import mssql, postgresql from sqlalchemy.engine import Connection from sqlalchemy.ext.asyncio import AsyncConnection, AsyncEngine from sqlalchemy.schema import ( @@ -195,10 +195,32 @@ def _get_row_generator( return row_gen_info, columns_covered -def _get_default_generator(column: Column) -> RowGeneratorInfo: - """Get default generator information, for the given column.""" - # If it's a primary key column, we presume that primary keys are populated - # automatically. +def _is_db_generated_pk(column: Column, dialect_name: str = "") -> bool: + """Return True if this column's value should be generated by the database. + + Single-column integer PKs with no FK are left to the DB (IDENTITY / SERIAL) + on dialects that support it (mssql, postgresql). DuckDB does not auto-generate + INTEGER PKs so datafaker must supply explicit values there. + Composite PKs and PK-FK columns must still be generated explicitly. + """ + if dialect_name not in ("mssql", "postgresql"): + return False + return ( + column.primary_key + and not column.foreign_keys + and len(column.table.primary_key.columns) == 1 + and isinstance(column.type, Integer) + ) + + +def _get_default_generator(column: Column, dialect_name: str = "") -> RowGeneratorInfo | None: + """Get default generator information, for the given column. + + Returns None for single-column integer PKs; the database generates those. + """ + # Single-column integer PKs are generated by the DB (IDENTITY / SERIAL). + if _is_db_generated_pk(column, dialect_name): + return None # If it's a foreign key column, pull random values from the column it # references. @@ -312,10 +334,7 @@ class GeneratorInfo: # Name or function to generate random objects of this type (not using summary data) generator: str | Callable[[Column], tuple[str, dict[str, str]]] - # SQL query that gets the data to supply as arguments to the generator - # ({column} and {table} will be interpolated) - summary_query: str | None = None - # Dictionary of the names returned from the summary_query to arg types. + # Dictionary of arg types for any summary query. # An arg type is a callable turning the returned value into a Python type to # pass as an argument to the generator. arg_types: dict[str, Callable] = field(default_factory=dict) @@ -352,12 +371,10 @@ def get_result_mappings( ), sqltypes.Date: GeneratorInfo( generator="generic.datetime.date", - summary_query=_YEAR_SUMMARY_QUERY, arg_types={"start": int, "end": int}, ), sqltypes.DateTime: GeneratorInfo( generator="generic.datetime.datetime", - summary_query=_YEAR_SUMMARY_QUERY, arg_types={"start": int, "end": int}, ), sqltypes.Integer: GeneratorInfo( # must be before Numeric @@ -379,6 +396,9 @@ def get_result_mappings( postgresql.UUID: GeneratorInfo( generator="generic.cryptographic.uuid", ), + mssql.UNIQUEIDENTIFIER: GeneratorInfo( + generator="generic.cryptographic.uuid", + ), sqltypes.String: GeneratorInfo( generator=_string_generator, choice=True, @@ -468,6 +488,7 @@ def _get_provider_for_column(column: Column) -> Tuple[list[str], str, dict[str, def _get_generator_for_table( table_config: Mapping[str, Any], table: Table, + dialect_name: str = "", ) -> TableGeneratorInfo: """Get generator information for the given table.""" unique_constraints = sorted( @@ -490,10 +511,14 @@ def _get_generator_for_table( nonnull_columns = { str(col.name) for col in table.columns - if not table.columns[col.name].nullable + if not table.columns[col.name].nullable and not _is_db_generated_pk(col, dialect_name) } else: - nonnull_columns = {str(col.name) for col in table.columns} + nonnull_columns = { + str(col.name) + for col in table.columns + if not _is_db_generated_pk(col, dialect_name) + } table_data: TableGeneratorInfo = TableGeneratorInfo( table_name=table.name, class_name=table.name.title().replace(".", "") + "Generator", @@ -508,7 +533,9 @@ def _get_generator_for_table( for column in table.columns: if column.name not in columns_covered: - table_data.row_gens.append(_get_default_generator(column)) + gen = _get_default_generator(column, dialect_name) + if gen is not None: + table_data.row_gens.append(gen) return table_data @@ -585,6 +612,7 @@ class GenerationInfo: def get_generation_info( metadata: MetaData, config: Mapping, + dialect_name: str = "", ) -> GenerationInfo: """ Create datafaker generator classes. @@ -649,6 +677,7 @@ def get_generation_info( _get_generator_for_table( tables_config.get(table.name, {}), table, + dialect_name, ) ) @@ -701,11 +730,13 @@ def make_tables_file( db_dsn: str, schema_name: Optional[str], parquet_dir: Optional[Path] = None, + engine: Optional[Engine] = None, ) -> str: """Construct the YAML file representing the schema.""" - engine = get_sync_engine(create_db_engine(db_dsn, schema_name=schema_name)) + if engine is None: + engine = get_sync_engine(create_db_engine(db_dsn, schema_name=schema_name)) - metadata = get_metadata(engine) + metadata = get_metadata(engine, schema_name=schema_name) meta_dict = metadata_to_dict(metadata, schema_name, engine, parquet_dir) if parquet_dir is not None: diff --git a/datafaker/proposers/base.py b/datafaker/proposers/base.py index 617d428..d0807dc 100644 --- a/datafaker/proposers/base.py +++ b/datafaker/proposers/base.py @@ -163,7 +163,9 @@ class PredefinedProposer(Proposer): that have been defined previously. """ - SELECT_AGGREGATE_RE = re.compile(r"SELECT (.*) FROM ([A-Za-z_][A-Za-z0-9_]*)") + SELECT_AGGREGATE_RE = re.compile( + r"SELECT (.*) FROM ((?:[A-Za-z_][A-Za-z0-9_]*\.)?[A-Za-z_][A-Za-z0-9_]*)" + ) AS_CLAUSE_RE = re.compile(r" *(.+) +AS +([A-Za-z_][A-Za-z0-9_]*) *") SRC_STAT_NAME_RE = re.compile(r'\bSRC_STATS\["([^]]*)"\].*') @@ -220,7 +222,7 @@ def __init__( # This query is one that this generator is interested in sam = None if query is None else self.SELECT_AGGREGATE_RE.match(query) # sam.group(2) is the table name from the FROM clause of the query - if sam and name == f"auto__{sam.group(2)}": + if sam and name == f"auto__{sam.group(2).split('.')[-1]}": # name is auto__{table_name}, so it's a select_aggregate, # so we split up its clauses sacs = [ @@ -365,6 +367,7 @@ def __init__( mean: float, stddev: float, count: int, + src_table: Any = None, ): """Initialise a Buckets object.""" bottom = mean - 2 * stddev @@ -392,8 +395,8 @@ def __init__( # catches errors if SQLAlchemy returns something that # isn't a number for some other unknown reason. pass - self.mean = mean - self.stddev = stddev + self.mean = mean + self.stddev = stddev @classmethod def make_buckets( @@ -412,15 +415,14 @@ def make_buckets( :param table: SQLAlchemy table (or joined tables) to pull data from. :param column: SQLAlchemy column or expression to measure. """ + stddev_fn = func.stdev if engine.dialect.name == "mssql" else func.stddev with engine.connect() as connection: result = connection.execute( duckdb_workaround( select( func.avg(column).label("mean"), - func.stddev(column).label("stddev"), - func.count(column).label( # pylint: disable=not-callable - "count" - ), + stddev_fn(column).label("stddev"), + func.count(column).label("count"), # pylint: disable=not-callable ).select_from(table) ) ).first() diff --git a/datafaker/proposers/choice.py b/datafaker/proposers/choice.py index ed4c471..863459b 100644 --- a/datafaker/proposers/choice.py +++ b/datafaker/proposers/choice.py @@ -6,7 +6,7 @@ from abc import abstractmethod from typing import Any, Sequence, Union -from sqlalchemy import Column, CursorResult, Engine, text +from sqlalchemy import Column, CursorResult, Engine, desc, func, literal_column, select, table, text from datafaker.proposers.base import ( Proposer, @@ -14,6 +14,7 @@ dist_gen, fit_from_buckets, ) +from datafaker.utils import schema_qualified_name NumericType = Union[int, float] @@ -44,6 +45,56 @@ def zipf_distribution(total: int, bins: int) -> typing.Generator[int, None, None yield x +def _choice_stmt( + column_name: str, + table_name: str, + store_counts: bool, + sample_count: int | None, + suppress_count: int, + random_fn: Any, + table_sql: str | None = None, +) -> Any: + """Build a SQLAlchemy SELECT for gathering choice value distributions. + + Compiles to dialect-correct SQL: LIMIT/random() on PostgreSQL/DuckDB, + TOP/newid() on MS-SQL. MS-SQL also forbids ORDER BY inside a subquery + without TOP; this function never emits such a clause. + """ + col = literal_column(f'"{column_name}"') + tbl = text(table_sql) if table_sql else table(table_name) + if sample_count is not None: + sample_sub = ( + select(col.label("value")) + .where(col.isnot(None)) + .select_from(tbl) + .order_by(random_fn) + .limit(sample_count) + .subquery("_inner") + ) + counted_sub = ( + select(sample_sub.c.value, func.count(sample_sub.c.value).label("count")) + .group_by(sample_sub.c.value) + .subquery("_counted") + ) + else: + counted_sub = ( + select(col.label("value"), func.count(col).label("count")) + .where(col.isnot(None)) + .select_from(tbl) + .group_by(col) + .subquery("_counted") + ) + out_cols = [counted_sub.c.value] + if store_counts: + out_cols.append(counted_sub.c["count"]) + stmt = select(*out_cols).select_from(counted_sub) + if suppress_count > 0: + stmt = stmt.where(counted_sub.c["count"] > suppress_count) + else: + stmt = stmt.order_by(desc(counted_sub.c["count"])) + return stmt + + class ChoiceProposer(Proposer): """Base proposer for all proposers producing choices of items.""" @@ -58,6 +109,8 @@ def __init__( counts: list[int], sample_count: int | None = None, suppress_count: int = 0, + dialect: Any = None, + table_sql: str | None = None, ) -> None: """Initialise a ChoiceProposer.""" super().__init__() @@ -67,33 +120,29 @@ def __init__( estimated_counts = self.get_estimated_counts(counts) self._fit = fit_from_buckets(counts, estimated_counts) - extra_results = "" - extra_expo = "" - extra_comment = "" - if self.STORE_COUNTS: - extra_results = f", COUNT({column_name}) AS count" - extra_expo = ", count" - extra_comment = " and their counts" + extra_comment = " and their counts" if self.STORE_COUNTS else "" + random_fn = ( + func.newid() + if (dialect is not None and dialect.name == "mssql") + else func.random() + ) + stmt = _choice_stmt( + column_name, table_name, self.STORE_COUNTS, sample_count, suppress_count, random_fn, + table_sql=table_sql, + ) + compile_opts: dict[str, Any] = {"compile_kwargs": {"literal_binds": True}} + if dialect is not None: + compile_opts["dialect"] = dialect + self._query = str(stmt.compile(**compile_opts)) + if suppress_count == 0: if sample_count is None: - self._query = ( - f'SELECT {column_name} AS value{extra_results} FROM "{table_name}"' - f" WHERE {column_name} IS NOT NULL GROUP BY value" - f" ORDER BY COUNT({column_name}) DESC" - ) self._comment = ( f"All the values{extra_comment} that appear in column {column_name}" f" of table {table_name}" ) self._annotation = None else: - self._query = ( - f"SELECT {column_name} AS value{extra_results} FROM" - f' (SELECT {column_name} FROM "{table_name}"' - f" WHERE {column_name} IS NOT NULL" - f" ORDER BY RANDOM() LIMIT {sample_count})" - f" AS _inner GROUP BY value ORDER BY COUNT({column_name}) DESC" - ) self._comment = ( f"The values{extra_comment} that appear in column {column_name}" f" of a random sample of {sample_count} rows of table {table_name}" @@ -101,26 +150,12 @@ def __init__( self._annotation = "sampled" else: if sample_count is None: - self._query = ( - f"SELECT value{extra_expo} FROM" - f" (SELECT {column_name} AS value, COUNT({column_name}) AS count" - f' FROM "{table_name}" WHERE {column_name} IS NOT NULL' - f" GROUP BY value ORDER BY count DESC) AS _inner" - f" WHERE {suppress_count} < count" - ) self._comment = ( f"All the values{extra_comment} that appear in column {column_name}" f" of table {table_name} more than {suppress_count} times" ) self._annotation = "suppressed" else: - self._query = ( - f"SELECT value{extra_expo} FROM (SELECT value, COUNT(value) AS count FROM" - f' (SELECT {column_name} AS value FROM "{table_name}"' - f" WHERE {column_name} IS NOT NULL ORDER BY RANDOM() LIMIT {sample_count})" - f" AS _inner GROUP BY value ORDER BY count DESC)" - f" AS _inner WHERE {suppress_count} < count" - ) self._comment = ( f"The values{extra_comment} that appear more than {suppress_count} times" f" in column {column_name}, out of a random sample of {sample_count} rows" @@ -302,112 +337,118 @@ def get_proposers( column = columns[0] column_name = column.name table_name = column.table.name + table_sql = schema_qualified_name(table_name, engine) + src_table = column.table + dialect = engine.dialect + random_fn = func.newid() if dialect.name == "mssql" else func.random() + col = literal_column(f'"{column_name}"') + src_table = column.table # preserves schema for schema-qualified databases generators = [] with engine.connect() as connection: - results = connection.execute( - text( - f'SELECT "{column_name}" AS v, COUNT("{column_name}")' - f' AS f FROM "{table_name}" GROUP BY v' - f" ORDER BY f DESC LIMIT {MAXIMUM_CHOICES + 1}" - ) + stmt_count = ( + select(col.label("v"), func.count(col).label("f")) + .select_from(src_table) + .group_by(col) + .order_by(desc(func.count(col))) + .limit(MAXIMUM_CHOICES + 1) ) + results = connection.execute(stmt_count) if results is not None and results.rowcount <= MAXIMUM_CHOICES: vg = ValueGatherer(results, self.SUPPRESS_COUNT) if vg.counts: generators += [ ZipfChoiceProposer( - table_name, column_name, vg.values, vg.counts + table_name, column_name, vg.values, vg.counts, + dialect=dialect, table_sql=table_sql, ), UniformChoiceProposer( - table_name, column_name, vg.values, vg.counts + table_name, column_name, vg.values, vg.counts, + dialect=dialect, table_sql=table_sql, ), WeightedChoiceProposer( - table_name, column_name, vg.cvs, vg.counts + table_name, column_name, vg.cvs, vg.counts, + dialect=dialect, table_sql=table_sql, ), ] if vg.counts_not_suppressed: generators += [ ZipfChoiceProposer( - table_name, - column_name, - vg.values_not_suppressed, - vg.counts_not_suppressed, - suppress_count=self.SUPPRESS_COUNT, + table_name, column_name, + vg.values_not_suppressed, vg.counts_not_suppressed, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), UniformChoiceProposer( - table_name, - column_name, - vg.values_not_suppressed, - vg.counts_not_suppressed, - suppress_count=self.SUPPRESS_COUNT, + table_name, column_name, + vg.values_not_suppressed, vg.counts_not_suppressed, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), WeightedChoiceProposer( - table_name=table_name, - column_name=column_name, + table_name=table_name, column_name=column_name, values=vg.cvs_not_suppressed, counts=vg.counts_not_suppressed, - suppress_count=self.SUPPRESS_COUNT, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), ] - sampled_results = connection.execute( - text( - f"SELECT v, COUNT(v) AS f FROM" - f' (SELECT "{column_name}" as v FROM "{table_name}"' - f" ORDER BY RANDOM() LIMIT {self.SAMPLE_COUNT})" - f" AS _inner GROUP BY v ORDER BY f DESC" - ) + inner = ( + select(col.label("v")) + .select_from(src_table) + .order_by(random_fn) + .limit(self.SAMPLE_COUNT) + .subquery("_inner") + ) + stmt_sample = ( + select(inner.c.v, func.count(inner.c.v).label("f")) + .select_from(inner) + .group_by(inner.c.v) + .order_by(desc(func.count(inner.c.v))) ) + sampled_results = connection.execute(stmt_sample) if sampled_results is not None: vg = ValueGatherer(sampled_results, self.SUPPRESS_COUNT) if vg.counts: generators += [ ZipfChoiceProposer( - table_name, - column_name, - vg.values, - vg.counts, - sample_count=self.SAMPLE_COUNT, + table_name, column_name, vg.values, vg.counts, + sample_count=self.SAMPLE_COUNT, dialect=dialect, + table_sql=table_sql, ), UniformChoiceProposer( - table_name, - column_name, - vg.values, - vg.counts, - sample_count=self.SAMPLE_COUNT, + table_name, column_name, vg.values, vg.counts, + sample_count=self.SAMPLE_COUNT, dialect=dialect, + table_sql=table_sql, ), WeightedChoiceProposer( - table_name, - column_name, - vg.cvs, - vg.counts, - sample_count=self.SAMPLE_COUNT, + table_name, column_name, vg.cvs, vg.counts, + sample_count=self.SAMPLE_COUNT, dialect=dialect, + table_sql=table_sql, ), ] if vg.counts_not_suppressed: generators += [ ZipfChoiceProposer( - table_name, - column_name, - vg.values_not_suppressed, - vg.counts_not_suppressed, + table_name, column_name, + vg.values_not_suppressed, vg.counts_not_suppressed, sample_count=self.SAMPLE_COUNT, - suppress_count=self.SUPPRESS_COUNT, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), UniformChoiceProposer( - table_name, - column_name, - vg.values_not_suppressed, - vg.counts_not_suppressed, + table_name, column_name, + vg.values_not_suppressed, vg.counts_not_suppressed, sample_count=self.SAMPLE_COUNT, - suppress_count=self.SUPPRESS_COUNT, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), WeightedChoiceProposer( - table_name=table_name, - column_name=column_name, + table_name=table_name, column_name=column_name, values=vg.cvs_not_suppressed, counts=vg.counts_not_suppressed, sample_count=self.SAMPLE_COUNT, - suppress_count=self.SUPPRESS_COUNT, + suppress_count=self.SUPPRESS_COUNT, dialect=dialect, + table_sql=table_sql, ), ] return generators diff --git a/datafaker/proposers/continuous.py b/datafaker/proposers/continuous.py index 056f6c6..44c9701 100644 --- a/datafaker/proposers/continuous.py +++ b/datafaker/proposers/continuous.py @@ -5,7 +5,7 @@ from collections.abc import Iterable, Mapping, Sequence from typing import Any -from sqlalchemy import Column, Engine, RowMapping, text +from sqlalchemy import Column, Engine, RowMapping, Table, case, func, null, select, text from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.types import Integer, Numeric from typing_extensions import Self @@ -18,7 +18,7 @@ dist_gen, get_column_type, ) -from datafaker.utils import logger +from datafaker.utils import logger, schema_qualified_name class ContinuousDistributionProposer(Proposer): @@ -139,13 +139,13 @@ class ContinuousDistributionProposerFactory(ProposerFactory): def _get_generators_from_buckets( self, engine: Engine, # pylint: disable=unused-argument - table_name: str, + src_table: Table, column_name: str, buckets: Buckets, ) -> Sequence[Proposer]: return [ - GaussianProposer(table_name, column_name, buckets), - UniformProposer(table_name, column_name, buckets), + GaussianProposer(src_table.name, column_name, buckets), + UniformProposer(src_table.name, column_name, buckets), ] def get_proposers( @@ -163,7 +163,7 @@ def get_proposers( if buckets is None: return [] return self._get_generators_from_buckets( - engine, table.name, column.name, buckets + engine, table, column.name, buckets ) @@ -271,24 +271,25 @@ class ContinuousLogDistributionProposerFactory(ContinuousDistributionProposerFac def _get_generators_from_buckets( self, engine: Engine, - table_name: str, + src_table: Table, column_name: str, buckets: Buckets, ) -> Sequence[Proposer]: + col = case( + (src_table.c[column_name] > 0, func.log(src_table.c[column_name])), + else_=null(), + ) + stmt = select( + func.avg(col).label("logmean"), + func.stddev_samp(col).label("logstddev"), + ).select_from(src_table) with engine.connect() as connection: - result = connection.execute( - text( - f"SELECT AVG(CASE WHEN 0<{column_name} THEN LN({column_name})" - " ELSE NULL END) AS logmean," - f" STDDEV(CASE WHEN 0<{column_name} THEN LN({column_name}) ELSE NULL END)" - f' AS logstddev FROM "{table_name}"' - ) - ).first() + result = connection.execute(stmt).first() if result is None or result.logstddev is None: return [] return [ LogNormalProposer( - table_name, + src_table.name, column_name, buckets, float(result.logmean), @@ -395,6 +396,7 @@ def __init__( self, table: str, factory: MultivariateNormalGeneratorFactoryBase, + dialect_name: str = "", ) -> None: """ Initialize the query for the basics for multivariate normal/lognormal parameters. @@ -402,6 +404,7 @@ def __init__( :param table: The name of the table to be queried. :param factory: The generator factory, perhaps with overridden ``query_var`` and ``query_predicate`` methods. + :param dialect_name: The SQLAlchemy dialect name (e.g. ``"mssql"``). """ self.table = table self._columns: Sequence[Column] = [] @@ -411,6 +414,7 @@ def __init__( self.suppress_count = 1 self._sample_count: int | None = None self._factory = factory + self._dialect_name = dialect_name self._predicate_fn = lambda x: x + " IS NOT NULL" def get_query_comment(self) -> str: @@ -565,6 +569,11 @@ def _inner_query(self) -> str: where = " WHERE " + where if self._sample_count is None: return f'"{self.table}"{where}' + if self._dialect_name == "mssql": + return ( + f"(SELECT TOP {self._sample_count} * FROM {self.table}{where}" + f" ORDER BY NEWID()) AS _sampled" + ) return ( f'(SELECT * FROM "{self.table}"{where} ORDER BY RANDOM()' f" LIMIT {self._sample_count}) AS _sampled" @@ -627,7 +636,8 @@ def get_proposers( return [] column_names = [c.name for c in columns] table = columns[0].table.name - cq = CovariateQuery(table, self).columns(columns) + table_sql = schema_qualified_name(table, engine) + cq = CovariateQuery(table_sql, self, dialect_name=engine.dialect.name).columns(columns) query = cq.get() with engine.connect() as connection: try: diff --git a/datafaker/proposers/mimesis.py b/datafaker/proposers/mimesis.py index e14b042..78a183e 100644 --- a/datafaker/proposers/mimesis.py +++ b/datafaker/proposers/mimesis.py @@ -5,7 +5,7 @@ import mimesis import mimesis.locales -from sqlalchemy import Column, Engine, func, text +from sqlalchemy import Column, Engine, cast, extract, func, literal_column, select from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.types import Date, DateTime, Integer, Numeric, String, Time @@ -187,17 +187,20 @@ def make_singleton( cls, column: Column, engine: Engine, function_name: str ) -> Sequence[Proposer]: """Make the appropriate generation configuration for this column.""" - extract_year = f"CAST(EXTRACT(YEAR FROM {column.name}) AS INT)" - max_year = f"MAX({extract_year})" - min_year = f"MIN({extract_year})" + col_expr = literal_column(column.name) + year_expr = cast(extract("year", col_expr), Integer()) + min_expr = func.min(year_expr) + max_expr = func.max(year_expr) + stmt = select(min_expr.label("start"), max_expr.label("end")).select_from( + column.table + ) with engine.connect() as connection: - result = connection.execute( - text( - f'SELECT {min_year} AS start, {max_year} AS end FROM "{column.table.name}"' - ) - ).first() + result = connection.execute(stmt).first() if result is None or result.start is None or result.end is None: return [] + dialect = engine.dialect + min_year = str(min_expr.compile(dialect=dialect, compile_kwargs={"literal_binds": True})) + max_year = str(max_expr.compile(dialect=dialect, compile_kwargs={"literal_binds": True})) return [ MimesisDateTimeProposer( column, diff --git a/datafaker/providers.py b/datafaker/providers.py index 57d8345..eb9d16b 100644 --- a/datafaker/providers.py +++ b/datafaker/providers.py @@ -28,7 +28,13 @@ def column_value( db_connection: Connection, orm_class: Any, column_name: str ) -> Any: """Return a random value from the column specified.""" - query = select(orm_class).order_by(functions.random()).limit(1) + # MS-SQL has no random() function; NEWID() produces a per-row random GUID. + # RAND() is not usable here because it returns the same value for every row. + if db_connection.dialect.name == "mssql": + random_fn = func.newid() + else: + random_fn = functions.random() + query = select(orm_class).order_by(random_fn).limit(1) random_row = db_connection.execute(query).first() if random_row: diff --git a/datafaker/remove.py b/datafaker/remove.py index 917c784..0949e04 100644 --- a/datafaker/remove.py +++ b/datafaker/remove.py @@ -60,12 +60,13 @@ def remove_db_vocab( def remove_db_tables(metadata: Optional[MetaData]) -> None: """Drop the tables in the destination schema.""" + schema_name = get_destination_schema() dst_engine = get_sync_engine( create_db_engine( get_destination_dsn(), - schema_name=get_destination_schema(), + schema_name=schema_name, ) ) if metadata is None: - metadata = get_metadata(dst_engine) + metadata = get_metadata(dst_engine, schema_name=schema_name) metadata.drop_all(dst_engine) diff --git a/datafaker/serialize_metadata.py b/datafaker/serialize_metadata.py index e4e8179..df5224f 100644 --- a/datafaker/serialize_metadata.py +++ b/datafaker/serialize_metadata.py @@ -7,7 +7,7 @@ import parsy from sqlalchemy import Column, Dialect, Engine, ForeignKey, MetaData, Table -from sqlalchemy.dialects import oracle, postgresql +from sqlalchemy.dialects import mssql, oracle, postgresql from sqlalchemy.sql import schema, sqltypes from datafaker.db_utils import constraint_name @@ -74,7 +74,9 @@ def string_type(type_: type) -> ParserType: Make a parser for a SQL string type. Parses TYPE_NAME, TYPE_NAME(32), TYPE_NAME COLLATE "fr" - or TYPE_NAME(32) COLLATE "fr" + or TYPE_NAME(32) COLLATE "fr" (PostgreSQL style, quoted collation name) + or TYPE_NAME(32) COLLATE SQL_Latin1_General_CP1_CI_AS + (MS-SQL style, unquoted collation name) """ @generate(type_.__name__) @@ -84,15 +86,18 @@ def st_parser() -> typing.Generator[ParserType, None, typing.Any]: length: int | None = yield ( parsy.string("(") >> integer() << parsy.string(")") ).optional() - collation: str | None = yield ( - parsy.string(' COLLATE "') >> parsy.regex(r'[^"]*') << parsy.string('"') + collation: str | None = yield parsy.alt( + # PostgreSQL: COLLATE "name" (quoted) + parsy.string(' COLLATE "') >> parsy.regex(r'[^"]*') << parsy.string('"'), + # MS-SQL: COLLATE name (unquoted identifier) + parsy.string(" COLLATE ") >> parsy.regex(r'\S+'), ).optional() return type_(length=length, collation=collation) return st_parser -def time_type(type_: type, pg_type: type) -> ParserType: +def time_type(type_: type, tz_type: type) -> ParserType: """ Make a parser for a SQL date/time type. @@ -100,10 +105,10 @@ def time_type(type_: type, pg_type: type) -> ParserType: or TYPE_NAME(32) WITH TIME ZONE :param type_: The SQLAlchemy type we would like to parse. - :param pg_type: The PostgreSQL type we would like to parse if precision - or timezone is provided. + :param tz_type: The type to instantiate when precision or timezone is + provided (e.g. ``postgresql.types.TIMESTAMP``). :return: ``type_`` if neither precision nor timezone are provided in the - parsed text, ``pg_type(precision, timezone)`` otherwise. + parsed text, ``tz_type(precision, timezone)`` otherwise. """ @generate(type_.__name__) @@ -121,20 +126,40 @@ def pgt_parser() -> typing.Generator[ParserType, None, typing.Any]: if precision is None and not timezone: # normal sql type return type_ - return pg_type(precision=precision, timezone=timezone) + return tz_type(precision=precision, timezone=timezone) return pgt_parser +@parsy.generate("VARBINARY") +def _mssql_varbinary_parser() -> typing.Generator[ParserType, None, typing.Any]: + """Parse VARBINARY, VARBINARY(n), or VARBINARY(max/MAX).""" + yield parsy.string("VARBINARY") + length: int | None = yield ( + parsy.string("(") + >> ( + (parsy.string("max") | parsy.string("MAX")).result(None) + | integer() + ) + << parsy.string(")") + ).optional() + return mssql.VARBINARY(length=length) + + SIMPLE_TYPE_PARSER = parsy.alt( parsy.string("DOUBLE PRECISION").result( sqltypes.DOUBLE_PRECISION ), # must be before DOUBLE - simple(sqltypes.FLOAT), + numeric_type(sqltypes.FLOAT), simple(sqltypes.DOUBLE), simple(sqltypes.INTEGER), simple(sqltypes.SMALLINT), simple(sqltypes.BIGINT), + # DATETIME2 and DATETIMEOFFSET must come before DATETIME — parsy.alt() is + # ordered and does not backtrack once a parser has consumed input, so the + # longer names must be tried first. + numeric_type(mssql.DATETIMEOFFSET), + numeric_type(mssql.DATETIME2), simple(sqltypes.DATETIME), simple(sqltypes.DATE), simple(sqltypes.CLOB), @@ -142,13 +167,36 @@ def pgt_parser() -> typing.Generator[ParserType, None, typing.Any]: simple(sqltypes.UUID), simple(sqltypes.BLOB), simple(sqltypes.BOOLEAN), - simple(postgresql.TSVECTOR), - simple(postgresql.BYTEA), - simple(postgresql.CIDR), + # PostgreSQL-specific types — mapped to cross-dialect equivalents so that + # an orm.yaml produced from a PostgreSQL source can be used with MS-SQL. + # PostgreSQL recreates these correctly; MSSQL gets a functional fallback. + parsy.string("TSVECTOR").result(sqltypes.Text), # no MS-SQL equivalent; degrade to Text + parsy.string("BYTEA").result(sqltypes.LargeBinary), # MS-SQL: VARBINARY(MAX) + parsy.string("CIDR").result(sqltypes.String(43)), # no MS-SQL equivalent; store as VARCHAR(43) + # PostgreSQL SERIAL pseudo-types — map to plain integers. datafaker does + # not rely on server-side autoincrement; the @compiles hook in create.py + # strips IDENTITY from MS-SQL DDL so explicit INSERTs work without + # SET IDENTITY_INSERT. BIGSERIAL/SMALLSERIAL listed before SERIAL so + # the common "SERIAL" prefix is tried last (defensive ordering). + parsy.string("BIGSERIAL").result(sqltypes.BIGINT), + parsy.string("SMALLSERIAL").result(sqltypes.SMALLINT), + parsy.string("SERIAL").result(sqltypes.INTEGER), numeric_type(sqltypes.NUMERIC), numeric_type(sqltypes.DECIMAL), numeric_type(postgresql.BIT), - numeric_type(postgresql.REAL), + numeric_type(sqltypes.REAL), # was postgresql.REAL; sqltypes.REAL is cross-dialect + # MS-SQL-specific types + simple(mssql.UNIQUEIDENTIFIER), + _mssql_varbinary_parser, + numeric_type(mssql.BINARY), + simple(mssql.MONEY), + simple(mssql.SMALLMONEY), + simple(mssql.IMAGE), + simple(mssql.TINYINT), + simple(mssql.SMALLDATETIME), + simple(mssql.NTEXT), + simple(mssql.SQL_VARIANT), + simple(mssql.ROWVERSION), string_type(sqltypes.CHAR), string_type(sqltypes.NCHAR), string_type(sqltypes.VARCHAR), @@ -201,11 +249,35 @@ def column_to_dict(column: Column, dialect: Dialect) -> dict[str, typing.Any]: return result +def _unqualify_fk_target( + fk: str, table_names: typing.Optional[frozenset] = None +) -> str: + """ + Drop the schema qualifier from a 3-part FK target. + + Converts ``schema.table.column`` → ``table.column`` so that SQLAlchemy + can resolve the reference against a MetaData whose tables were registered + without a schema prefix. 2-part ``table.column`` targets are returned + unchanged. + + When ``table_names`` is supplied, a 3-part target whose first two parts + form a known table name (e.g. ``manufacturer.parquet``) is left unchanged + because the dot is part of the table name, not a schema prefix. + """ + parts = fk.split(".") + if len(parts) == 3: + if table_names is not None and f"{parts[0]}.{parts[1]}" in table_names: + return fk + return f"{parts[1]}.{parts[2]}" + return fk + + def dict_to_column( table_name: str, col_name: str, rep: dict, ignore_fk: typing.Callable[[str], bool], + table_names: typing.Optional[frozenset] = None, ) -> Column: """ Produce column from aspects of its dict description. @@ -231,7 +303,7 @@ def dict_to_column( if "foreign_keys" in rep: args = [ ForeignKey( - fk, + _unqualify_fk_target(fk, table_names), name=make_foreign_key_name(table_name, col_name), ondelete="CASCADE", ) @@ -282,13 +354,14 @@ def dict_to_table( meta: MetaData, table_dict: TableT, ignore_fk: typing.Callable[[str], bool], + table_names: typing.Optional[frozenset] = None, ) -> Table: """Create a Table from its description.""" return Table( name, meta, *[ - dict_to_column(name, colname, col, ignore_fk) + dict_to_column(name, colname, col, ignore_fk, table_names) for (colname, col) in table_dict.get("columns", {}).items() ], *[dict_to_unique(constraint) for constraint in table_dict.get("unique", [])], @@ -328,7 +401,14 @@ def should_ignore_fk(tables_dict: dict[str, TableT], fk: str) -> bool: :param fk: The name of the foreign key. """ (table, _column) = split_column_full_name(fk) - td: dict[str, TableT] = get_property(tables_dict, table, {}) + # FK targets may be schema-qualified (e.g. "mimic100.concept"). + # Try the fully-qualified name first so users can be explicit in config + # (e.g. "mimic100.concept: ignore: true"); fall back to the bare table + # name for configs that don't include a schema prefix. + td = tables_dict.get(table) + if td is None: + bare = table.split(".")[-1] + td = tables_dict.get(bare, {}) return get_property(td, "ignore", False) @@ -355,7 +435,8 @@ def dict_to_metadata( ignore_fk = partial(should_ignore_fk, tables_config) else: ignore_fk = _always_false + table_names = frozenset(tables_dict.keys()) meta = MetaData() for k, td in tables_dict.items(): - dict_to_table(k, meta, td, ignore_fk) + dict_to_table(k, meta, td, ignore_fk, table_names) return meta diff --git a/datafaker/utils.py b/datafaker/utils.py index c8bcc97..bb6f8e6 100644 --- a/datafaker/utils.py +++ b/datafaker/utils.py @@ -16,6 +16,7 @@ import yaml from jsonschema.exceptions import ValidationError from jsonschema.validators import validate +from sqlalchemy.engine import make_url from datafaker.settings import SettingsError @@ -92,6 +93,62 @@ def import_file(file_path: str) -> ModuleType: return module +_ASYNC_DRIVER_MAP: dict[str, str] = { + "postgresql": "postgresql+asyncpg", + "mssql": "mssql+aioodbc", +} + + +def make_async_dsn(db_dsn: str) -> str: + """Return an async-driver DSN for the given sync DSN. + + Replaces the driver component based on the dialect so that both PostgreSQL + and MS-SQL connections can be made async without hardcoding dialect names at + each call site. Raises ``ValueError`` for dialects with no known async driver. + """ + url = make_url(db_dsn) + dialect = url.drivername.split("+")[0] + async_driver = _ASYNC_DRIVER_MAP.get(dialect) + if async_driver is None: + raise ValueError( + f"No async driver is registered for dialect '{dialect}'. " + f"Add an entry to _ASYNC_DRIVER_MAP in datafaker/utils.py." + ) + return str(url.set(drivername=async_driver)) + + +def _is_undefined_object_error(exc: Exception) -> bool: + """Return True if *exc* represents a 'constraint does not exist' error. + + Checks for psycopg2's UndefinedObject when psycopg2 is installed, and falls + back to inspecting the SQLSTATE pgcode attribute so the function works without + psycopg2 (e.g. in an MS-SQL environment). + """ + try: + import psycopg2.errors # type: ignore[import] + + if isinstance(exc, psycopg2.errors.UndefinedObject): + return True + except ImportError: + pass + # SQLSTATE 42704 = undefined_object — present on psycopg2 and pyodbc errors + return getattr(exc, "pgcode", None) == "42704" + + +def schema_qualified_name(table_name: str, engine: Any) -> str: + """Return schema-qualified table name using the engine's schema_translate_map. + + When create_db_engine sets schema_translate_map={None: schema_name}, this + reads it back so raw SQL strings (which schema_translate_map doesn't rewrite) + can include the correct qualifier. + """ + schema_map = engine.get_execution_options().get("schema_translate_map", {}) + schema = schema_map.get(None) + if schema and "." not in table_name: + return f"{schema}.{table_name}" + return table_name + + def info_or_lower(record: logging.LogRecord) -> bool: """Allow records with level of INFO or lower.""" return record.levelno in (logging.DEBUG, logging.INFO) diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..dc0beca --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,25 @@ +services: + mssql: + image: mcr.microsoft.com/mssql/server:2022-latest + environment: + ACCEPT_EULA: "Y" + MSSQL_SA_PASSWORD: "Datafaker!Test123" + ports: + - "1433:1433" + healthcheck: + test: + - "CMD" + - "/opt/mssql-tools18/bin/sqlcmd" + - "-S" + - "localhost" + - "-U" + - "sa" + - "-P" + - "Datafaker!Test123" + - "-Q" + - "SELECT 1" + - "-No" + interval: 10s + timeout: 5s + retries: 12 + start_period: 30s diff --git a/examples/omop-mssql/.env.example b/examples/omop-mssql/.env.example new file mode 100644 index 0000000..83453da --- /dev/null +++ b/examples/omop-mssql/.env.example @@ -0,0 +1,4 @@ +SRC_DSN=mssql+pyodbc://:@127.0.0.1:1433/?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes +SRC_SCHEMA= +DST_DSN=mssql+pyodbc://:@127.0.0.1:1433/?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes +DST_SCHEMA= diff --git a/examples/omop-mssql/README.md b/examples/omop-mssql/README.md new file mode 100644 index 0000000..00c9a23 --- /dev/null +++ b/examples/omop-mssql/README.md @@ -0,0 +1,151 @@ +# How to run datafaker process on OMOP schema with MS SQL Server + +## About + +This example is for testing datafaker against a Microsoft SQL Server (MS-SQL) database using the OMOP schema. It can be used to verify that datafaker correctly generates and manages synthetic data in an MS-SQL environment. + +## Challenges for MS-SQL support + +Datafaker was built with PostgreSQL as its primary target. The following issues need to be addressed to support MS-SQL (Microsoft SQL Server). + +### 1. Driver dependency ([#93](https://github.com/SAFEHR-data/datafaker/issues/93)) + +`psycopg2` (PostgreSQL driver) is a hard dependency imported directly in [datafaker/utils.py](../../datafaker/utils.py). MS-SQL requires a different driver such as `pyodbc` or `pymssql`, which are not currently listed in `pyproject.toml`. The `asyncpg` async driver is also PostgreSQL-specific; MS-SQL async support would require `aioodbc` or similar. + +### 2. Hardcoded async connection string rewriting ([#94](https://github.com/SAFEHR-data/datafaker/issues/94)) + +In [datafaker/utils.py:208](../../datafaker/utils.py), the async DSN is built by string-replacing `postgresql://` with `postgresql+asyncpg://`. This logic would silently fail (or produce a malformed DSN) for an `mssql://` connection string. + +### 3. PostgreSQL `search_path` for schema selection ([#95](https://github.com/SAFEHR-data/datafaker/issues/95)) + +When a schema name is provided, the code issues `SET search_path TO ` via a connection-level event listener ([datafaker/utils.py:222, 305](../../datafaker/utils.py)). This is PostgreSQL-specific syntax. MS-SQL uses two-part `[schema].[table]` naming and does not support `SET search_path`. SQLAlchemy's `schema` argument on `MetaData` and `Table` objects is the correct cross-dialect approach. + +### 4. PostgreSQL-specific column types in the type parser ([#96](https://github.com/SAFEHR-data/datafaker/issues/96), commit [76fec75](https://github.com/SAFEHR-data/datafaker/commit/76fec75)) + +[datafaker/serialize_metadata.py](../../datafaker/serialize_metadata.py) registers parsers for several PostgreSQL-only types that have no direct MS-SQL equivalent: + +| PostgreSQL type | MS-SQL equivalent / issue | +|---|---| +| `postgresql.TSVECTOR` | No native equivalent (full-text indexing works differently) | +| `postgresql.CIDR` | No native network address type | +| `postgresql.BYTEA` | Use `VARBINARY(MAX)` | +| `postgresql.ARRAY` | Not supported; would need denormalisation or JSON | +| `postgresql.ENUM` | Implemented via `CHECK` constraint or lookup table | +| `postgresql.DOMAIN` | Not supported | +| `postgresql.BIT` | MS-SQL `BIT` is boolean (0/1 only); multi-bit columns use `BINARY` | +| `postgresql.REAL` / `TIMESTAMP` / `TIME` with timezone | Need MS-SQL dialect equivalents (`DATETIMEOFFSET` for tz-aware timestamps) | + +### 5. `SERIAL` autoincrement columns ([#97](https://github.com/SAFEHR-data/datafaker/issues/97), commit [da4a69b](https://github.com/SAFEHR-data/datafaker/commit/da4a69b)) + +PostgreSQL uses `SERIAL` for autoincrement columns. The code already strips `SERIAL` for DuckDB in [datafaker/create.py:29](../../datafaker/create.py), but there is no equivalent handler for MS-SQL, which uses `IDENTITY(1,1)`. + +### 6. `postgresql.UUID` type mapping ([#98](https://github.com/SAFEHR-data/datafaker/issues/98), commit [76fec75](https://github.com/SAFEHR-data/datafaker/commit/76fec75)) + +[datafaker/make.py:384](../../datafaker/make.py) maps `postgresql.UUID` to a generator. MS-SQL uses `UNIQUEIDENTIFIER` for UUIDs, which SQLAlchemy exposes as `sqlalchemy.dialects.mssql.UNIQUEIDENTIFIER`. + +### 7. PostgreSQL-specific error handling (commits [b2f14ab](https://github.com/SAFEHR-data/datafaker/commit/b2f14ab), [39709d8](https://github.com/SAFEHR-data/datafaker/commit/39709d8)) + +[datafaker/utils.py:651](../../datafaker/utils.py) catches `psycopg2.errors.UndefinedObject` to handle missing constraints gracefully. This is a PostgreSQL/psycopg2-specific exception. For MS-SQL the equivalent `pyodbc` error would need to be caught instead, or the check should be made dialect-agnostic. + +### 8. `autocommit` handling in `set_db_settings` ([#99](https://github.com/SAFEHR-data/datafaker/issues/99)) + +[datafaker/utils.py:297-309](../../datafaker/utils.py) toggles `connection.autocommit` directly on the DBAPI connection before executing `SET` commands. The availability and behaviour of `autocommit` differs between `psycopg2`, `pyodbc`, and `pymssql`, so this would need testing or an abstraction per driver. + +**Deferred.** `set_db_settings` is only ever called for DuckDB connections (`parquet_dir` source feature); MS-SQL connections never reach it. Fixing the `autocommit` toggle in isolation would also leave the `SET {k} TO {v}` SQL syntax broken for MS-SQL (which requires `SET {k} {v}`). Both issues should be addressed together if `set_db_settings` is ever extended to MS-SQL. + + +## Setup + +### 1. Install the MS-SQL Python extras + +`pyodbc` and `aioodbc` are optional dependencies. Install them with: + +```bash +poetry install --extras mssql +``` + +### 2. Install and register the ODBC driver + +#### mac OS + +If you do not already have the Microsoft ODBC driver installed: + +```bash +brew tap microsoft/mssql-release +brew install unixodbc msodbcsql18 mssql-tools18 +``` + +Then verify the driver is registered: + +```bash +odbcinst -q -d +``` + +If the output is empty, register it manually: + +```bash +cat >> /opt/homebrew/etc/odbcinst.ini <<'EOF' +[ODBC Driver 18 for SQL Server] +Description=Microsoft ODBC Driver 18 for SQL Server +Driver=/opt/homebrew/lib/libmsodbcsql.18.dylib +UsageCount=1 +EOF +``` + +#### Ubuntu + +Install and check the MS SQL tools: + +```console +$ sudo apt install mssql-tools18 +$ odbcinst -q -d +[ODBC Driver 18 for SQL Server] +``` + +### 3. Configure the connection + +Copy the example environment file and fill in your connection details: + +```bash +cp examples/omop-mssql/.env.example examples/omop-mssql/.env +``` + +Edit `.env` with your server hostname, credentials, database name and schema names. The DSN format is: + +``` +mssql+pyodbc://:@:1433/?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes + +> **Note for Docker on macOS:** use `127.0.0.1` rather than `localhost`. macOS resolves `localhost` to `::1` (IPv6) but Docker Desktop's port forwarding only reliably maps the IPv4 address. +``` + +Run datafaker commands from the `examples/omop-mssql/` directory so that the `.env` file is picked up automatically. + +## Steps + +Run all commands from the `examples/omop-mssql/` directory so that the `.env` file is picked up automatically. + +```bash +cd examples/omop-mssql +``` + +1. Make a YAML file representing the tables in the schema + +`poetry run datafaker make-tables --orm-file ./orm.yaml` + +1. Create schema from the ORM YAML file + +`poetry run datafaker create-tables --orm-file ./orm.yaml --config-file ./config.yaml` + +1. Run `copy_vocabulary.sql` to copy vocabulary table rows. (I did it in DBeaver) + +1. Create generator table + +`poetry run datafaker create-generators --orm-file ./orm.yaml --config-file ./config.yaml --df-file ./df.py` + +1. Create data + +`poetry run datafaker create-data --orm-file ./orm.yaml --config-file ./config.yaml --df-file ./df.py` + +1. Remove data + +`poetry run datafaker remove-data --orm-file ./orm.yaml --config-file ./config.yaml` diff --git a/examples/omop-mssql/config.yaml b/examples/omop-mssql/config.yaml new file mode 100644 index 0000000..d58d83d --- /dev/null +++ b/examples/omop-mssql/config.yaml @@ -0,0 +1,46 @@ +src-stats: +- comments: + - The values and their counts that appear in column gender_concept_id of a random + sample of 500 rows of table person + name: auto__person__gender_concept_id + query: "SELECT _counted.value, _counted.count \nFROM (SELECT _inner.value AS value,\ + \ count(_inner.value) AS count \nFROM (SELECT TOP 500 \"gender_concept_id\" AS\ + \ value \nFROM mimic100.person \nWHERE \"gender_concept_id\" IS NOT NULL ORDER\ + \ BY newid()) AS _inner GROUP BY _inner.value) AS _counted ORDER BY _counted.count\ + \ DESC" +- comments: + - All the values that appear in column year_of_birth of table person + name: auto__person__year_of_birth + query: "SELECT _counted.value \nFROM (SELECT \"year_of_birth\" AS value, count(\"\ + year_of_birth\") AS count \nFROM mimic100.person \nWHERE \"year_of_birth\" IS\ + \ NOT NULL GROUP BY \"year_of_birth\") AS _counted ORDER BY _counted.count DESC" +- comments: + - All the values that appear in column ethnicity_concept_id of table person more + than 7 times + name: auto__person__ethnicity_concept_id + query: "SELECT _counted.value \nFROM (SELECT \"ethnicity_concept_id\" AS value,\ + \ count(\"ethnicity_concept_id\") AS count \nFROM mimic100.person \nWHERE \"ethnicity_concept_id\"\ + \ IS NOT NULL GROUP BY \"ethnicity_concept_id\") AS _counted \nWHERE _counted.count\ + \ > 7" +tables: + concept: + ignore: false + vocabulary_table: true + person: + num_rows_per_pass: 10 + row_generators: + - columns_assigned: + - gender_concept_id + kwargs: + a: SRC_STATS["auto__person__gender_concept_id"]["results"] + name: dist_gen.weighted_choice + - columns_assigned: + - year_of_birth + kwargs: + a: SRC_STATS["auto__person__year_of_birth"]["results"] + name: dist_gen.choice + - columns_assigned: + - ethnicity_concept_id + kwargs: + a: SRC_STATS["auto__person__ethnicity_concept_id"]["results"] + name: dist_gen.choice diff --git a/examples/omop-mssql/df.py b/examples/omop-mssql/df.py new file mode 100644 index 0000000..445f7f7 --- /dev/null +++ b/examples/omop-mssql/df.py @@ -0,0 +1,88 @@ +"""This file was auto-generated by datafaker but can be edited manually.""" +from mimesis import Generic, Numeric, Person +from mimesis.locales import Locale +import sqlalchemy +import sys +from datafaker.base import FileUploader, TableGenerator, ColumnPresence +from datafaker.providers import DistributionProvider + +generic = Generic(locale=Locale.EN_GB) +numeric = Numeric() +person = Person() +dist_gen = DistributionProvider() +column_presence = ColumnPresence() + +sys.path.append("") + +from datafaker.providers import ( + BytesProvider, + ColumnValueProvider, + DistributionProvider, + NullProvider, + SQLGroupByProvider, + TimedeltaProvider, + TimespanProvider, + WeightedBooleanProvider, +) + +generic.add_provider(BytesProvider) +generic.add_provider(ColumnValueProvider) +generic.add_provider(DistributionProvider) +generic.add_provider(NullProvider) +generic.add_provider(SQLGroupByProvider) +generic.add_provider(TimedeltaProvider) +generic.add_provider(TimespanProvider) +generic.add_provider(WeightedBooleanProvider) + + +import yaml + +with open("src-stats.yaml", "r", encoding="utf-8") as f: + SRC_STATS = yaml.unsafe_load(f) + + +class PersonGenerator(TableGenerator): + num_rows_per_pass = 10 + + def __init__(self): + self.initialized = False + + def __call__(self, dst_db_conn, metadata): + if not self.initialized: + self.initialized = True + result = {} + columns_to_generate = set( + { + "ethnicity_concept_id", + "race_concept_id", + "gender_concept_id", + "year_of_birth", + } + ) + while columns_to_generate: + if "gender_concept_id" in columns_to_generate: + result["gender_concept_id"] = dist_gen.weighted_choice( + a=SRC_STATS["auto__person__gender_concept_id"]["results"] + ) + if "year_of_birth" in columns_to_generate: + result["year_of_birth"] = dist_gen.choice( + a=SRC_STATS["auto__person__year_of_birth"]["results"] + ) + if "ethnicity_concept_id" in columns_to_generate: + result["ethnicity_concept_id"] = dist_gen.choice( + a=SRC_STATS["auto__person__ethnicity_concept_id"]["results"] + ) + if "race_concept_id" in columns_to_generate: + result["race_concept_id"] = generic.column_value_provider.column_value( + dst_db_conn, metadata.tables["concept"], "concept_id" + ) + columns_to_generate = set() + return result + + +table_generator_dict = { + "person": PersonGenerator(), +} + + +story_generator_list = [] diff --git a/examples/omop-mssql/orm.yaml b/examples/omop-mssql/orm.yaml new file mode 100644 index 0000000..46fa10a --- /dev/null +++ b/examples/omop-mssql/orm.yaml @@ -0,0 +1,122 @@ +dsn: mssql+pyodbc://sa:***@127.0.0.1:1433/master?TrustServerCertificate=yes&driver=ODBC+Driver+18+for+SQL+Server +schema: mimic100 +tables: + concept: + columns: + concept_class_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + concept_code: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + concept_id: + nullable: false + primary: true + type: BIGINT + concept_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + domain_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + standard_concept: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + vocabulary_id: + nullable: false + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + person: + columns: + # birth_datetime: + # nullable: true + # primary: false + # type: DATETIME2 + # day_of_birth: + # nullable: true + # primary: false + # type: BIGINT + ethnicity_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + # ethnicity_source_concept_id: + # foreign_keys: + # - mimic100.concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # ethnicity_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + gender_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + # gender_source_concept_id: + # foreign_keys: + # - mimic100.concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # gender_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + # month_of_birth: + # nullable: true + # primary: false + # type: BIGINT + person_id: + nullable: false + primary: true + type: BIGINT + # person_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + race_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + # race_source_concept_id: + # foreign_keys: + # - mimic100.concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # race_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + year_of_birth: + nullable: false + primary: false + type: BIGINT + unique: [] + \ No newline at end of file diff --git a/examples/omop-mssql/orm_full.yaml b/examples/omop-mssql/orm_full.yaml new file mode 100644 index 0000000..d4ccf16 --- /dev/null +++ b/examples/omop-mssql/orm_full.yaml @@ -0,0 +1,1868 @@ +dsn: mssql+pyodbc://sa:***@127.0.0.1:1433/master?TrustServerCertificate=yes&driver=ODBC+Driver+18+for+SQL+Server +schema: mimic100 +tables: + care_site: + columns: + care_site_id: + nullable: false + primary: true + type: BIGINT + care_site_name: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + care_site_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + location_id: + nullable: true + primary: false + type: BIGINT + place_of_service_concept_id: + nullable: true + primary: false + type: BIGINT + place_of_service_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + cdm_source: + columns: + cdm_etl_reference: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + cdm_holder: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + cdm_release_date: + nullable: false + primary: false + type: DATE + cdm_source_abbreviation: + nullable: false + primary: false + type: VARCHAR(25) COLLATE SQL_Latin1_General_CP1_CI_AS + cdm_source_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + cdm_version: + nullable: true + primary: false + type: VARCHAR(10) COLLATE SQL_Latin1_General_CP1_CI_AS + source_description: + nullable: true + primary: false + type: VARCHAR(max) COLLATE SQL_Latin1_General_CP1_CI_AS + source_documentation_reference: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + source_release_date: + nullable: false + primary: false + type: DATE + vocabulary_version: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + cohort: + columns: + cohort_definition_id: + nullable: false + primary: false + type: BIGINT + cohort_end_date: + nullable: false + primary: false + type: DATE + cohort_start_date: + nullable: false + primary: false + type: DATE + subject_id: + nullable: false + primary: false + type: BIGINT + unique: [] + cohort_definition: + columns: + cohort_definition_description: + nullable: true + primary: false + type: VARCHAR(max) COLLATE SQL_Latin1_General_CP1_CI_AS + cohort_definition_id: + nullable: false + primary: false + type: BIGINT + cohort_definition_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + cohort_definition_syntax: + nullable: true + primary: false + type: VARCHAR(max) COLLATE SQL_Latin1_General_CP1_CI_AS + cohort_initiation_date: + nullable: true + primary: false + type: DATE + definition_type_concept_id: + nullable: false + primary: false + type: BIGINT + subject_concept_id: + nullable: false + primary: false + type: BIGINT + unique: [] + concept: + columns: + concept_class_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + concept_code: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + concept_id: + nullable: false + primary: true + type: BIGINT + concept_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + domain_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + standard_concept: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + vocabulary_id: + nullable: false + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + concept_ancestor: + columns: + ancestor_concept_id: + nullable: false + primary: false + type: BIGINT + descendant_concept_id: + nullable: false + primary: false + type: BIGINT + max_levels_of_separation: + nullable: false + primary: false + type: BIGINT + min_levels_of_separation: + nullable: false + primary: false + type: BIGINT + unique: [] + concept_class: + columns: + concept_class_concept_id: + nullable: false + primary: false + type: BIGINT + concept_class_id: + nullable: false + primary: true + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + concept_class_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + concept_relationship: + columns: + concept_id_1: + nullable: false + primary: false + type: BIGINT + concept_id_2: + nullable: false + primary: false + type: BIGINT + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + relationship_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + concept_synonym: + columns: + concept_id: + nullable: false + primary: false + type: BIGINT + concept_synonym_name: + nullable: false + primary: false + type: VARCHAR(1000) COLLATE SQL_Latin1_General_CP1_CI_AS + language_concept_id: + nullable: false + primary: false + type: BIGINT + unique: [] + condition_era: + columns: + condition_concept_id: + nullable: false + primary: false + type: BIGINT + condition_era_end_date: + nullable: false + primary: false + type: DATE + condition_era_id: + nullable: false + primary: true + type: BIGINT + condition_era_start_date: + nullable: false + primary: false + type: DATE + condition_occurrence_count: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + unique: [] + condition_occurrence: + columns: + condition_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + condition_end_date: + nullable: true + primary: false + type: DATE + condition_end_datetime: + nullable: true + primary: false + type: DATETIME2 + condition_occurrence_id: + nullable: false + primary: true + type: BIGINT + condition_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + condition_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + condition_start_date: + nullable: false + primary: false + type: DATE + condition_start_datetime: + nullable: true + primary: false + type: DATETIME2 + condition_status_concept_id: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + condition_status_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + condition_type_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - mimic100.provider.provider_id + nullable: true + primary: false + type: BIGINT + stop_reason: + nullable: true + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_id: + foreign_keys: + - mimic100.visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - mimic100.visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + cost: + columns: + amount_allowed: + nullable: true + primary: false + type: NUMERIC(18, 0) + cost_domain_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + cost_event_id: + nullable: false + primary: false + type: BIGINT + cost_id: + nullable: false + primary: true + type: BIGINT + cost_type_concept_id: + nullable: false + primary: false + type: BIGINT + currency_concept_id: + nullable: true + primary: false + type: BIGINT + drg_concept_id: + nullable: true + primary: false + type: BIGINT + drg_source_value: + nullable: true + primary: false + type: VARCHAR(3) COLLATE SQL_Latin1_General_CP1_CI_AS + paid_by_patient: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_by_payer: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_by_primary: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_dispensing_fee: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_ingredient_cost: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_patient_coinsurance: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_patient_copay: + nullable: true + primary: false + type: NUMERIC(18, 0) + paid_patient_deductible: + nullable: true + primary: false + type: NUMERIC(18, 0) + payer_plan_period_id: + nullable: true + primary: false + type: BIGINT + revenue_code_concept_id: + nullable: true + primary: false + type: BIGINT + revenue_code_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + total_charge: + nullable: true + primary: false + type: NUMERIC(18, 0) + total_cost: + nullable: true + primary: false + type: NUMERIC(18, 0) + total_paid: + nullable: true + primary: false + type: NUMERIC(18, 0) + unique: [] + death: + columns: + cause_concept_id: + nullable: true + primary: false + type: BIGINT + cause_source_concept_id: + nullable: true + primary: false + type: BIGINT + cause_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + death_date: + nullable: false + primary: false + type: DATE + death_datetime: + nullable: true + primary: false + type: DATETIME2 + death_type_concept_id: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + unique: [] + device_exposure: + columns: + device_concept_id: + nullable: false + primary: false + type: BIGINT + device_exposure_end_date: + nullable: true + primary: false + type: DATE + device_exposure_end_datetime: + nullable: true + primary: false + type: DATETIME2 + device_exposure_id: + nullable: false + primary: true + type: BIGINT + device_exposure_start_date: + nullable: false + primary: false + type: DATE + device_exposure_start_datetime: + nullable: true + primary: false + type: DATETIME2 + device_source_concept_id: + nullable: true + primary: false + type: BIGINT + device_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + device_type_concept_id: + nullable: false + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + provider_id: + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: BIGINT + unique_device_id: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_id: + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + nullable: true + primary: false + type: BIGINT + unique: [] + domain: + columns: + domain_concept_id: + nullable: false + primary: false + type: BIGINT + domain_id: + nullable: false + primary: true + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + domain_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + dose_era: + columns: + dose_era_end_date: + nullable: false + primary: false + type: DATE + dose_era_id: + nullable: false + primary: true + type: BIGINT + dose_era_start_date: + nullable: false + primary: false + type: DATE + dose_value: + nullable: false + primary: false + type: NUMERIC(18, 0) + drug_concept_id: + nullable: false + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + unit_concept_id: + nullable: false + primary: false + type: BIGINT + unique: [] + drug_era: + columns: + drug_concept_id: + nullable: false + primary: false + type: BIGINT + drug_era_end_date: + nullable: false + primary: false + type: DATE + drug_era_id: + nullable: false + primary: true + type: BIGINT + drug_era_start_date: + nullable: false + primary: false + type: DATE + drug_exposure_count: + nullable: true + primary: false + type: BIGINT + gap_days: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + unique: [] + drug_exposure: + columns: + days_supply: + nullable: true + primary: false + type: BIGINT + dose_unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + drug_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + drug_exposure_end_date: + nullable: false + primary: false + type: DATE + drug_exposure_end_datetime: + nullable: true + primary: false + type: DATETIME2 + drug_exposure_id: + nullable: false + primary: true + type: BIGINT + drug_exposure_start_date: + nullable: false + primary: false + type: DATE + drug_exposure_start_datetime: + nullable: true + primary: false + type: DATETIME2 + drug_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + drug_source_value: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + drug_type_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + lot_number: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - mimic100.provider.provider_id + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: NUMERIC(18, 0) + refills: + nullable: true + primary: false + type: BIGINT + route_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + route_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + sig: + nullable: true + primary: false + type: VARCHAR(max) COLLATE SQL_Latin1_General_CP1_CI_AS + stop_reason: + nullable: true + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + verbatim_end_date: + nullable: true + primary: false + type: DATE + visit_detail_id: + foreign_keys: + - mimic100.visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - mimic100.visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + drug_strength: + columns: + amount_unit_concept_id: + nullable: true + primary: false + type: BIGINT + amount_value: + nullable: true + primary: false + type: NUMERIC(18, 0) + box_size: + nullable: true + primary: false + type: BIGINT + denominator_unit_concept_id: + nullable: true + primary: false + type: BIGINT + denominator_value: + nullable: true + primary: false + type: NUMERIC(18, 0) + drug_concept_id: + nullable: false + primary: false + type: BIGINT + ingredient_concept_id: + nullable: false + primary: false + type: BIGINT + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + numerator_unit_concept_id: + nullable: true + primary: false + type: BIGINT + numerator_value: + nullable: true + primary: false + type: NUMERIC(18, 0) + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + episode: + columns: + episode_concept_id: + nullable: false + primary: false + type: BIGINT + episode_end_date: + nullable: true + primary: false + type: DATE + episode_end_datetime: + nullable: true + primary: false + type: DATETIME2 + episode_id: + nullable: false + primary: true + type: BIGINT + episode_number: + nullable: true + primary: false + type: BIGINT + episode_object_concept_id: + nullable: false + primary: false + type: BIGINT + episode_parent_id: + nullable: true + primary: false + type: BIGINT + episode_source_concept_id: + nullable: true + primary: false + type: BIGINT + episode_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + episode_start_date: + nullable: false + primary: false + type: DATE + episode_start_datetime: + nullable: true + primary: false + type: DATETIME2 + episode_type_concept_id: + nullable: false + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + unique: [] + episode_event: + columns: + episode_event_field_concept_id: + nullable: false + primary: false + type: BIGINT + episode_id: + nullable: false + primary: false + type: BIGINT + event_id: + nullable: false + primary: false + type: BIGINT + unique: [] + fact_relationship: + columns: + domain_concept_id_1: + nullable: false + primary: false + type: BIGINT + domain_concept_id_2: + nullable: false + primary: false + type: BIGINT + fact_id_1: + nullable: false + primary: false + type: BIGINT + fact_id_2: + nullable: false + primary: false + type: BIGINT + relationship_concept_id: + nullable: false + primary: false + type: BIGINT + unique: [] + location: + columns: + address_1: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + address_2: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + city: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + county: + nullable: true + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + location_id: + nullable: false + primary: true + type: BIGINT + location_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + state: + nullable: true + primary: false + type: VARCHAR(2) COLLATE SQL_Latin1_General_CP1_CI_AS + zip: + nullable: true + primary: false + type: VARCHAR(9) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + measurement: + columns: + measurement_concept_id: + nullable: false + primary: false + type: BIGINT + measurement_date: + nullable: false + primary: false + type: DATE + measurement_datetime: + nullable: true + primary: false + type: DATETIME2 + measurement_id: + nullable: false + primary: true + type: BIGINT + measurement_source_concept_id: + nullable: true + primary: false + type: BIGINT + measurement_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + measurement_time: + nullable: true + primary: false + type: VARCHAR(10) COLLATE SQL_Latin1_General_CP1_CI_AS + measurement_type_concept_id: + nullable: false + primary: false + type: BIGINT + operator_concept_id: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + provider_id: + nullable: true + primary: false + type: BIGINT + range_high: + nullable: true + primary: false + type: NUMERIC(18, 0) + range_low: + nullable: true + primary: false + type: NUMERIC(18, 0) + unit_concept_id: + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + value_as_concept_id: + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC(18, 0) + value_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_id: + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + nullable: true + primary: false + type: BIGINT + unique: [] + metadata: + columns: + metadata_concept_id: + nullable: false + primary: false + type: BIGINT + metadata_date: + nullable: true + primary: false + type: DATE + metadata_datetime: + nullable: true + primary: false + type: DATETIME2 + metadata_id: + nullable: false + primary: true + type: BIGINT + metadata_type_concept_id: + nullable: false + primary: false + type: BIGINT + name: + nullable: false + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + value_as_concept_id: + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC(18, 0) + value_as_string: + nullable: true + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + note: + columns: + encoding_concept_id: + nullable: false + primary: false + type: BIGINT + language_concept_id: + nullable: false + primary: false + type: BIGINT + note_class_concept_id: + nullable: false + primary: false + type: BIGINT + note_date: + nullable: false + primary: false + type: DATE + note_datetime: + nullable: true + primary: false + type: DATETIME2 + note_event_field_concept_id: + nullable: true + primary: false + type: BIGINT + note_event_id: + nullable: true + primary: false + type: BIGINT + note_id: + nullable: false + primary: true + type: BIGINT + note_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + note_text: + nullable: false + primary: false + type: VARCHAR(max) COLLATE SQL_Latin1_General_CP1_CI_AS + note_title: + nullable: true + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + note_type_concept_id: + nullable: false + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + provider_id: + nullable: true + primary: false + type: BIGINT + visit_detail_id: + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + nullable: true + primary: false + type: BIGINT + unique: [] + note_nlp: + columns: + lexical_variant: + nullable: false + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + nlp_date: + nullable: false + primary: false + type: DATE + nlp_datetime: + nullable: true + primary: false + type: DATETIME2 + nlp_system: + nullable: true + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + note_id: + nullable: false + primary: false + type: BIGINT + note_nlp_concept_id: + nullable: true + primary: false + type: BIGINT + note_nlp_id: + nullable: false + primary: true + type: BIGINT + note_nlp_source_concept_id: + nullable: true + primary: false + type: BIGINT + offset: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + section_concept_id: + nullable: true + primary: false + type: BIGINT + snippet: + nullable: true + primary: false + type: VARCHAR(250) COLLATE SQL_Latin1_General_CP1_CI_AS + term_exists: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + term_modifiers: + nullable: true + primary: false + type: VARCHAR(2000) COLLATE SQL_Latin1_General_CP1_CI_AS + term_temporal: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + observation: + columns: + observation_concept_id: + nullable: false + primary: false + type: BIGINT + observation_date: + nullable: false + primary: false + type: DATE + observation_datetime: + nullable: true + primary: false + type: DATETIME2 + observation_id: + nullable: false + primary: true + type: BIGINT + observation_source_concept_id: + nullable: true + primary: false + type: BIGINT + observation_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + observation_type_concept_id: + nullable: false + primary: false + type: BIGINT + person_id: + nullable: false + primary: false + type: BIGINT + provider_id: + nullable: true + primary: false + type: BIGINT + qualifier_concept_id: + nullable: true + primary: false + type: BIGINT + qualifier_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unit_concept_id: + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + value_as_concept_id: + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC(18, 0) + value_as_string: + nullable: true + primary: false + type: VARCHAR(120) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_id: + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + nullable: true + primary: false + type: BIGINT + unique: [] + observation_period: + columns: + observation_period_end_date: + nullable: false + primary: false + type: DATE + observation_period_id: + nullable: false + primary: true + type: BIGINT + observation_period_start_date: + nullable: false + primary: false + type: DATE + period_type_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + payer_plan_period: + columns: + family_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + payer_concept_id: + nullable: true + primary: false + type: BIGINT + payer_plan_period_end_date: + nullable: false + primary: false + type: DATE + payer_plan_period_id: + nullable: false + primary: true + type: BIGINT + payer_plan_period_start_date: + nullable: false + primary: false + type: DATE + payer_source_concept_id: + nullable: true + primary: false + type: BIGINT + payer_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + nullable: false + primary: false + type: BIGINT + plan_concept_id: + nullable: true + primary: false + type: BIGINT + plan_source_concept_id: + nullable: true + primary: false + type: BIGINT + plan_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + sponsor_concept_id: + nullable: true + primary: false + type: BIGINT + sponsor_source_concept_id: + nullable: true + primary: false + type: BIGINT + sponsor_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + stop_reason_concept_id: + nullable: true + primary: false + type: BIGINT + stop_reason_source_concept_id: + nullable: true + primary: false + type: BIGINT + stop_reason_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + person: + columns: + birth_datetime: + nullable: true + primary: false + type: DATETIME2 + care_site_id: + foreign_keys: + - mimic100.care_site.care_site_id + nullable: true + primary: false + type: BIGINT + day_of_birth: + nullable: true + primary: false + type: BIGINT + ethnicity_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + ethnicity_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + ethnicity_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + gender_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + gender_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + gender_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + location_id: + foreign_keys: + - mimic100.location.location_id + nullable: true + primary: false + type: BIGINT + month_of_birth: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: true + type: BIGINT + person_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + provider_id: + foreign_keys: + - mimic100.provider.provider_id + nullable: true + primary: false + type: BIGINT + race_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + race_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + race_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + year_of_birth: + nullable: false + primary: false + type: BIGINT + unique: [] + procedure_occurrence: + columns: + modifier_concept_id: + nullable: true + primary: false + type: BIGINT + modifier_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + procedure_concept_id: + nullable: false + primary: false + type: BIGINT + procedure_date: + nullable: false + primary: false + type: DATE + procedure_datetime: + nullable: true + primary: false + type: DATETIME2 + procedure_occurrence_id: + nullable: false + primary: true + type: BIGINT + procedure_source_concept_id: + nullable: true + primary: false + type: BIGINT + procedure_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + procedure_type_concept_id: + nullable: false + primary: false + type: BIGINT + provider_id: + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: BIGINT + visit_detail_id: + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + nullable: true + primary: false + type: BIGINT + unique: [] + provider: + columns: + care_site_id: + nullable: true + primary: false + type: BIGINT + dea: + nullable: true + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + gender_concept_id: + nullable: true + primary: false + type: BIGINT + gender_source_concept_id: + nullable: true + primary: false + type: BIGINT + gender_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + npi: + nullable: true + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + provider_id: + nullable: false + primary: true + type: BIGINT + provider_name: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + provider_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + specialty_concept_id: + nullable: true + primary: false + type: BIGINT + specialty_source_concept_id: + nullable: true + primary: false + type: BIGINT + specialty_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + year_of_birth: + nullable: true + primary: false + type: BIGINT + unique: [] + relationship: + columns: + defines_ancestry: + nullable: false + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + is_hierarchical: + nullable: false + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + relationship_concept_id: + nullable: false + primary: false + type: BIGINT + relationship_id: + nullable: false + primary: true + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + relationship_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + reverse_relationship_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + source_to_concept_map: + columns: + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AS + source_code: + nullable: false + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + source_code_description: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + source_concept_id: + nullable: false + primary: false + type: BIGINT + source_vocabulary_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + target_concept_id: + nullable: false + primary: false + type: BIGINT + target_vocabulary_id: + nullable: false + primary: false + type: VARCHAR(20) COLLATE SQL_Latin1_General_CP1_CI_AS + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + specimen: + columns: + anatomic_site_concept_id: + nullable: true + primary: false + type: BIGINT + anatomic_site_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + disease_status_concept_id: + nullable: true + primary: false + type: BIGINT + disease_status_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + nullable: false + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: NUMERIC(18, 0) + specimen_concept_id: + nullable: false + primary: false + type: BIGINT + specimen_date: + nullable: false + primary: false + type: DATE + specimen_datetime: + nullable: true + primary: false + type: DATETIME2 + specimen_id: + nullable: false + primary: true + type: BIGINT + specimen_source_id: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + specimen_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + specimen_type_concept_id: + nullable: false + primary: false + type: BIGINT + unit_concept_id: + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] + visit_detail: + columns: + admitting_source_concept_id: + nullable: true + primary: false + type: BIGINT + admitting_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + care_site_id: + foreign_keys: + - mimic100.care_site.care_site_id + nullable: true + primary: false + type: BIGINT + discharge_to_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + discharge_to_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + preceding_visit_detail_id: + foreign_keys: + - mimic100.visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + provider_id: + foreign_keys: + - mimic100.provider.provider_id + nullable: true + primary: false + type: BIGINT + visit_detail_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_detail_end_date: + nullable: false + primary: false + type: DATE + visit_detail_end_datetime: + nullable: true + primary: false + type: DATETIME2 + visit_detail_id: + nullable: false + primary: true + type: BIGINT + visit_detail_parent_id: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_source_concept_id: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_source_value: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_detail_start_date: + nullable: false + primary: false + type: DATE + visit_detail_start_datetime: + nullable: true + primary: false + type: DATETIME2 + visit_detail_type_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - mimic100.visit_occurrence.visit_occurrence_id + nullable: false + primary: false + type: BIGINT + unique: [] + visit_occurrence: + columns: + admitted_from_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + admitted_from_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + care_site_id: + foreign_keys: + - mimic100.care_site.care_site_id + nullable: true + primary: false + type: BIGINT + discharged_to_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + discharged_to_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + person_id: + foreign_keys: + - mimic100.person.person_id + nullable: false + primary: false + type: BIGINT + preceding_visit_occurrence_id: + foreign_keys: + - mimic100.visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + provider_id: + foreign_keys: + - mimic100.provider.provider_id + nullable: true + primary: false + type: BIGINT + visit_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_end_date: + nullable: false + primary: false + type: DATE + visit_end_datetime: + nullable: true + primary: false + type: DATETIME2 + visit_occurrence_id: + nullable: false + primary: true + type: BIGINT + visit_source_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: true + primary: false + type: BIGINT + visit_source_value: + nullable: true + primary: false + type: VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS + visit_start_date: + nullable: false + primary: false + type: DATE + visit_start_datetime: + nullable: true + primary: false + type: DATETIME2 + visit_type_concept_id: + foreign_keys: + - mimic100.concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + vocabulary: + columns: + vocabulary_concept_id: + nullable: false + primary: false + type: BIGINT + vocabulary_id: + nullable: false + primary: true + type: VARCHAR(30) COLLATE SQL_Latin1_General_CP1_CI_AS + vocabulary_name: + nullable: false + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + vocabulary_reference: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + vocabulary_version: + nullable: true + primary: false + type: VARCHAR(255) COLLATE SQL_Latin1_General_CP1_CI_AS + unique: [] diff --git a/examples/omop-mssql/sql/copy_vocabulary.sql b/examples/omop-mssql/sql/copy_vocabulary.sql new file mode 100644 index 0000000..7d531da --- /dev/null +++ b/examples/omop-mssql/sql/copy_vocabulary.sql @@ -0,0 +1,24 @@ +INSERT INTO mimic100_synthetic.concept ( + concept_class_id, + concept_code, + concept_id, + concept_name, + domain_id, + invalid_reason, + standard_concept, + valid_end_date, + valid_start_date, + vocabulary_id +) +SELECT + concept_class_id, + concept_code, + concept_id, + concept_name, + domain_id, + invalid_reason, + standard_concept, + valid_end_date, + valid_start_date, + vocabulary_id +FROM mimic100.concept; \ No newline at end of file diff --git a/examples/omop-mssql/src-stats.yaml b/examples/omop-mssql/src-stats.yaml new file mode 100644 index 0000000..17f5b39 --- /dev/null +++ b/examples/omop-mssql/src-stats.yaml @@ -0,0 +1,102 @@ +auto__person__ethnicity_concept_id: + comments: + - All the values that appear in column ethnicity_concept_id of table person more + than 7 times + queries: + date: '2026-05-22 15:26:05' + query: "SELECT _counted.value \nFROM (SELECT \"ethnicity_concept_id\" AS value,\ + \ count(\"ethnicity_concept_id\") AS count \nFROM mimic100.person \nWHERE \"\ + ethnicity_concept_id\" IS NOT NULL GROUP BY \"ethnicity_concept_id\") AS _counted\ + \ \nWHERE _counted.count > 7" + results: + - value: 0 +auto__person__gender_concept_id: + comments: + - The values and their counts that appear in column gender_concept_id of a random + sample of 500 rows of table person + queries: + date: '2026-05-22 15:26:05' + query: "SELECT _counted.value, _counted.count \nFROM (SELECT _inner.value AS value,\ + \ count(_inner.value) AS count \nFROM (SELECT TOP 500 \"gender_concept_id\"\ + \ AS value \nFROM mimic100.person \nWHERE \"gender_concept_id\" IS NOT NULL\ + \ ORDER BY newid()) AS _inner GROUP BY _inner.value) AS _counted ORDER BY _counted.count\ + \ DESC" + results: + - count: 57 + value: 8507 + - count: 43 + value: 8532 +auto__person__year_of_birth: + comments: + - All the values that appear in column year_of_birth of table person + queries: + date: '2026-05-22 15:26:05' + query: "SELECT _counted.value \nFROM (SELECT \"year_of_birth\" AS value, count(\"\ + year_of_birth\") AS count \nFROM mimic100.person \nWHERE \"year_of_birth\" IS\ + \ NOT NULL GROUP BY \"year_of_birth\") AS _counted ORDER BY _counted.count DESC" + results: + - value: 2062 + - value: 2058 + - value: 2059 + - value: 2070 + - value: 2073 + - value: 2084 + - value: 2119 + - value: 2123 + - value: 2125 + - value: 2102 + - value: 2104 + - value: 2106 + - value: 2136 + - value: 2130 + - value: 2133 + - value: 2055 + - value: 2085 + - value: 2086 + - value: 2089 + - value: 2094 + - value: 2075 + - value: 2079 + - value: 2083 + - value: 2066 + - value: 2043 + - value: 2050 + - value: 2052 + - value: 2054 + - value: 2049 + - value: 2030 + - value: 2031 + - value: 2033 + - value: 2038 + - value: 2041 + - value: 2067 + - value: 2069 + - value: 2064 + - value: 2060 + - value: 2061 + - value: 2077 + - value: 2074 + - value: 2071 + - value: 2095 + - value: 2096 + - value: 2097 + - value: 2099 + - value: 2090 + - value: 2092 + - value: 2093 + - value: 2134 + - value: 2138 + - value: 2145 + - value: 2149 + - value: 2108 + - value: 2111 + - value: 2114 + - value: 2115 + - value: 2116 + - value: 2117 + - value: 2118 + - value: 2105 + - value: 2103 + - value: 2128 + - value: 2120 + - value: 2122 diff --git a/examples/omop-postgresql/README.md b/examples/omop-postgresql/README.md new file mode 100644 index 0000000..9a79779 --- /dev/null +++ b/examples/omop-postgresql/README.md @@ -0,0 +1,29 @@ +# How to run datafaker process on omop schema + +1. Make a YAML file representing the tables in the schema + +`poetry run datafaker make-tables --orm-file ./orm.yaml --config-file ./config.yaml` + +1. Interactively set generators for column data. +`poetry run datafaker configure-generators --orm-file ./orm.yaml --config-file ./config.yaml` + +1. Compute summary statistics from the source database. +`poetry run datafaker make-stats --orm-file ./orm.yaml --config-file ./config.yaml --stats-file ./src-stats.yaml` + +1. Create schema from the ORM YAML file + +`poetry run datafaker create-tables --orm-file ./orm.yaml --config-file ./config.yaml` + +1. Create generator table + +`poetry run datafaker create-generators --orm-file ./orm.yaml --config-file ./config.yaml --df-file ./df.py` + +1. Create data + +`poetry run datafaker create-data --orm-file ./orm.yaml --config-file ./config.yaml --df-file ./df.py` + +1. Remove data + +`poetry run datafaker remove-data --orm-file ./orm.yaml --config-file ./config.yaml` + +Plan: /Users/myong/.claude/plans/cached-rolling-snowglobe.md \ No newline at end of file diff --git a/examples/omop-postgresql/config.yaml b/examples/omop-postgresql/config.yaml new file mode 100644 index 0000000..b94eef4 --- /dev/null +++ b/examples/omop-postgresql/config.yaml @@ -0,0 +1,59 @@ +src-stats: +- comments: + - All the values and their counts that appear in column ethnicity_concept_id of + table person + name: auto__person__ethnicity_concept_id + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"ethnicity_concept_id\"\ + \ AS value, count(\"ethnicity_concept_id\") AS count \nFROM mimic.person \nWHERE\ + \ \"ethnicity_concept_id\" IS NOT NULL GROUP BY \"ethnicity_concept_id\") AS _counted\ + \ ORDER BY _counted.count DESC" +- comments: + - All the values and their counts that appear in column gender_concept_id of table + person + name: auto__person__gender_concept_id + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"gender_concept_id\"\ + \ AS value, count(\"gender_concept_id\") AS count \nFROM mimic.person \nWHERE\ + \ \"gender_concept_id\" IS NOT NULL GROUP BY \"gender_concept_id\") AS _counted\ + \ ORDER BY _counted.count DESC" +- comments: + - All the values and their counts that appear in column race_concept_id of table + person + name: auto__person__race_concept_id + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"race_concept_id\"\ + \ AS value, count(\"race_concept_id\") AS count \nFROM mimic.person \nWHERE \"\ + race_concept_id\" IS NOT NULL GROUP BY \"race_concept_id\") AS _counted ORDER\ + \ BY _counted.count DESC" +- comments: + - All the values and their counts that appear in column year_of_birth of table person + name: auto__person__year_of_birth + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"year_of_birth\" AS\ + \ value, count(\"year_of_birth\") AS count \nFROM mimic.person \nWHERE \"year_of_birth\"\ + \ IS NOT NULL GROUP BY \"year_of_birth\") AS _counted ORDER BY _counted.count\ + \ DESC" +tables: + concept: + ignore: false + vocabulary_table: true + person: + num_rows_per_pass: 1 + row_generators: + - columns_assigned: + - ethnicity_concept_id + kwargs: + a: SRC_STATS["auto__person__ethnicity_concept_id"]["results"] + name: dist_gen.weighted_choice + - columns_assigned: + - gender_concept_id + kwargs: + a: SRC_STATS["auto__person__gender_concept_id"]["results"] + name: dist_gen.weighted_choice + - columns_assigned: + - race_concept_id + kwargs: + a: SRC_STATS["auto__person__race_concept_id"]["results"] + name: dist_gen.weighted_choice + - columns_assigned: + - year_of_birth + kwargs: + a: SRC_STATS["auto__person__year_of_birth"]["results"] + name: dist_gen.weighted_choice diff --git a/examples/omop-postgresql/config_template.yaml b/examples/omop-postgresql/config_template.yaml new file mode 100644 index 0000000..fe7b265 --- /dev/null +++ b/examples/omop-postgresql/config_template.yaml @@ -0,0 +1,131 @@ +tables: + # Unnecessary tables + _measurement_links: + ignore: true + _observation_links: + ignore: true + _person_links: + ignore: true + _procedure_occurrence_links: + ignore: true + _visit_occurrence_links: + ignore: true + + # Vocab tables + concept: + # This one is a vocab, but its too big to handle the usual way + ignore: false + vocabulary_table: true + concept_ancestor: + # This one is a vocab, but its too big to handle the usual way + ignore: true + vocabulary_table: true + vocabulary: + vocabulary_table: true + domain: + vocabulary_table: true + concept_class: + vocabulary_table: true + concept_synonym: + # This one is a vocab, but its too big to handle the usual way + ignore: true + # vocabulary_table: true + concept_relationship: + # This one is a vocab, but its too big to handle the usual way + ignore: true + # vocabulary_table: true + drug_strength: + # This one is a vocab, but its too big to handle the usual way + ignore: true + # vocabulary_table: true + relationship: + vocabulary_table: true + source_to_concept_map: + vocabulary_table: true + location: + vocabulary_table: true + care_site: + vocabulary_table: true + provider: + vocabulary_table: true + cdm_source: + vocabulary_table: true + + # attribute_definition: + # num_rows_per_pass: 0 + + # cohort_definition: + # num_rows_per_pass: 0 + + # condition_era: + # num_rows_per_pass: 0 + + # cost: + # num_rows_per_pass: 0 + + # device_exposure: + # num_rows_per_pass: 0 + + # dose_era: + # num_rows_per_pass: 0 + + # drug_era: + # num_rows_per_pass: 0 + + # drug_exposure: + # num_rows_per_pass: 0 + + # fact_relationship: + # num_rows_per_pass: 0 + + # measurement: + # num_rows_per_pass: 0 + + # metadata: + # num_rows_per_pass: 0 + + # note: + # num_rows_per_pass: 0 + + # note_nlp: + # num_rows_per_pass: 0 + + # observation: + # num_rows_per_pass: 0 + + # observation_period: + # num_rows_per_pass: 0 + + # payer_plan_period: + # num_rows_per_pass: 0 + + # procedure_occurrence: + # num_rows_per_pass: 0 + # row_generators: + # - name: generic.null_provider.null + # columns_assigned: person_id + # - name: generic.column_value_provider.column_value + # columns_assigned: procedure_concept_id + # args: + # - dst_db_conn + # - metadata.tables["concept"] + # - '"concept_id"' + + + # specimen: + # num_rows_per_pass: 0 + + # visit_detail: + # num_rows_per_pass: 0 + + # visit_occurrence: + # num_rows_per_pass: 0 + + person: + num_rows_per_pass: 0 + + # death: + # num_rows_per_pass: 0 + + # condition_occurrence: + # num_rows_per_pass: 0 diff --git a/examples/omop-postgresql/df.py b/examples/omop-postgresql/df.py new file mode 100644 index 0000000..6889cf9 --- /dev/null +++ b/examples/omop-postgresql/df.py @@ -0,0 +1,88 @@ +"""This file was auto-generated by datafaker but can be edited manually.""" +from mimesis import Generic, Numeric, Person +from mimesis.locales import Locale +import sqlalchemy +import sys +from datafaker.base import FileUploader, TableGenerator, ColumnPresence +from datafaker.providers import DistributionProvider + +generic = Generic(locale=Locale.EN_GB) +numeric = Numeric() +person = Person() +dist_gen = DistributionProvider() +column_presence = ColumnPresence() + +sys.path.append("") + +from datafaker.providers import ( + BytesProvider, + ColumnValueProvider, + DistributionProvider, + NullProvider, + SQLGroupByProvider, + TimedeltaProvider, + TimespanProvider, + WeightedBooleanProvider, +) + +generic.add_provider(BytesProvider) +generic.add_provider(ColumnValueProvider) +generic.add_provider(DistributionProvider) +generic.add_provider(NullProvider) +generic.add_provider(SQLGroupByProvider) +generic.add_provider(TimedeltaProvider) +generic.add_provider(TimespanProvider) +generic.add_provider(WeightedBooleanProvider) + + +import yaml + +with open("src-stats.yaml", "r", encoding="utf-8") as f: + SRC_STATS = yaml.unsafe_load(f) + + +class PersonGenerator(TableGenerator): + num_rows_per_pass = 1 + + def __init__(self): + self.initialized = False + + def __call__(self, dst_db_conn, metadata): + if not self.initialized: + self.initialized = True + result = {} + columns_to_generate = set( + { + "ethnicity_concept_id", + "year_of_birth", + "gender_concept_id", + "race_concept_id", + } + ) + while columns_to_generate: + if "ethnicity_concept_id" in columns_to_generate: + result["ethnicity_concept_id"] = dist_gen.weighted_choice( + a=SRC_STATS["auto__person__ethnicity_concept_id"]["results"] + ) + if "gender_concept_id" in columns_to_generate: + result["gender_concept_id"] = dist_gen.weighted_choice( + a=SRC_STATS["auto__person__gender_concept_id"]["results"] + ) + if "race_concept_id" in columns_to_generate: + result["race_concept_id"] = dist_gen.weighted_choice( + a=SRC_STATS["auto__person__race_concept_id"]["results"] + ) + if "year_of_birth" in columns_to_generate: + result["year_of_birth"] = dist_gen.weighted_choice( + a=SRC_STATS["auto__person__year_of_birth"]["results"] + ) + columns_to_generate = set() + return result + + +table_generator_dict = { + "person": PersonGenerator(), +} + + +story_generator_list = [] diff --git a/examples/omop-postgresql/orm.yaml b/examples/omop-postgresql/orm.yaml new file mode 100644 index 0000000..b526fe8 --- /dev/null +++ b/examples/omop-postgresql/orm.yaml @@ -0,0 +1,127 @@ +dsn: postgresql://postgres@localhost:5432/omop5.4 +schema: mimic +tables: + concept: + columns: + concept_class_id: + foreign_keys: + - concept_class.concept_class_id + nullable: false + primary: false + type: VARCHAR(20) + concept_code: + nullable: false + primary: false + type: VARCHAR(255) + concept_id: + nullable: false + primary: true + type: BIGINT + concept_name: + nullable: false + primary: false + type: VARCHAR(255) + domain_id: + foreign_keys: + - domain.domain_id + nullable: false + primary: false + type: VARCHAR(20) + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) + standard_concept: + nullable: true + primary: false + type: VARCHAR(1) + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + vocabulary_id: + foreign_keys: + - vocabulary.vocabulary_id + nullable: false + primary: false + type: VARCHAR(50) + unique: [] + person: + columns: + # birth_datetime: + # nullable: true + # primary: false + # type: TIMESTAMP WITHOUT TIME ZONE + # day_of_birth: + # nullable: true + # primary: false + # type: BIGINT + ethnicity_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + # ethnicity_source_concept_id: + # foreign_keys: + # - concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # ethnicity_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) + gender_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + # gender_source_concept_id: + # foreign_keys: + # - concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # gender_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) + # month_of_birth: + # nullable: true + # primary: false + # type: BIGINT + person_id: + nullable: false + primary: true + type: BIGINT + # person_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) + race_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + # race_source_concept_id: + # foreign_keys: + # - concept.concept_id + # nullable: true + # primary: false + # type: BIGINT + # race_source_value: + # nullable: true + # primary: false + # type: VARCHAR(50) + year_of_birth: + nullable: false + primary: false + type: BIGINT + unique: [] diff --git a/examples/omop-postgresql/orm_full.yaml b/examples/omop-postgresql/orm_full.yaml new file mode 100644 index 0000000..a400553 --- /dev/null +++ b/examples/omop-postgresql/orm_full.yaml @@ -0,0 +1,2092 @@ +dsn: postgresql://postgres@localhost:5432/omop5.4 +schema: mimic +tables: + care_site: + columns: + care_site_id: + nullable: false + primary: true + type: BIGINT + care_site_name: + nullable: true + primary: false + type: VARCHAR(255) + care_site_source_value: + nullable: true + primary: false + type: VARCHAR(50) + location_id: + foreign_keys: + - location.location_id + nullable: true + primary: false + type: BIGINT + place_of_service_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + place_of_service_source_value: + nullable: true + primary: false + type: VARCHAR(50) + unique: [] + cdm_source: + columns: + cdm_etl_reference: + nullable: true + primary: false + type: VARCHAR(255) + cdm_holder: + nullable: false + primary: false + type: VARCHAR(255) + cdm_release_date: + nullable: false + primary: false + type: DATE + cdm_source_abbreviation: + nullable: false + primary: false + type: VARCHAR(25) + cdm_source_name: + nullable: false + primary: false + type: VARCHAR(255) + cdm_version: + nullable: true + primary: false + type: VARCHAR(10) + source_description: + nullable: true + primary: false + type: TEXT + source_documentation_reference: + nullable: true + primary: false + type: VARCHAR(255) + source_release_date: + nullable: false + primary: false + type: DATE + vocabulary_version: + nullable: false + primary: false + type: VARCHAR(20) + unique: [] + cohort: + columns: + cohort_definition_id: + nullable: false + primary: false + type: BIGINT + cohort_end_date: + nullable: false + primary: false + type: DATE + cohort_start_date: + nullable: false + primary: false + type: DATE + subject_id: + nullable: false + primary: false + type: BIGINT + unique: [] + cohort_definition: + columns: + cohort_definition_description: + nullable: true + primary: false + type: TEXT + cohort_definition_id: + nullable: false + primary: false + type: BIGINT + cohort_definition_name: + nullable: false + primary: false + type: VARCHAR(255) + cohort_definition_syntax: + nullable: true + primary: false + type: TEXT + cohort_initiation_date: + nullable: true + primary: false + type: DATE + definition_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + subject_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + concept: + columns: + concept_class_id: + foreign_keys: + - concept_class.concept_class_id + nullable: false + primary: false + type: VARCHAR(20) + concept_code: + nullable: false + primary: false + type: VARCHAR(255) + concept_id: + nullable: false + primary: true + type: BIGINT + concept_name: + nullable: false + primary: false + type: VARCHAR(255) + domain_id: + foreign_keys: + - domain.domain_id + nullable: false + primary: false + type: VARCHAR(20) + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) + standard_concept: + nullable: true + primary: false + type: VARCHAR(1) + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + vocabulary_id: + foreign_keys: + - vocabulary.vocabulary_id + nullable: false + primary: false + type: VARCHAR(50) + unique: [] + concept_ancestor: + columns: + ancestor_concept_id: + nullable: false + primary: false + type: BIGINT + descendant_concept_id: + nullable: false + primary: false + type: BIGINT + max_levels_of_separation: + nullable: false + primary: false + type: BIGINT + min_levels_of_separation: + nullable: false + primary: false + type: BIGINT + unique: [] + concept_class: + columns: + concept_class_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + concept_class_id: + nullable: false + primary: true + type: VARCHAR(20) + concept_class_name: + nullable: false + primary: false + type: VARCHAR(255) + unique: [] + concept_relationship: + columns: + concept_id_1: + nullable: false + primary: false + type: BIGINT + concept_id_2: + nullable: false + primary: false + type: BIGINT + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) + relationship_id: + foreign_keys: + - relationship.relationship_id + nullable: false + primary: false + type: VARCHAR(20) + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + concept_synonym: + columns: + concept_id: + nullable: false + primary: false + type: BIGINT + concept_synonym_name: + nullable: false + primary: false + type: VARCHAR(1000) + language_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + condition_era: + columns: + condition_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + condition_era_end_date: + nullable: false + primary: false + type: DATE + condition_era_id: + nullable: false + primary: true + type: BIGINT + condition_era_start_date: + nullable: false + primary: false + type: DATE + condition_occurrence_count: + nullable: true + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + condition_occurrence: + columns: + condition_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + condition_end_date: + nullable: true + primary: false + type: DATE + condition_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + condition_occurrence_id: + nullable: false + primary: true + type: BIGINT + condition_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + condition_source_value: + nullable: true + primary: false + type: VARCHAR(50) + condition_start_date: + nullable: false + primary: false + type: DATE + condition_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + condition_status_concept_id: + nullable: true + primary: false + type: VARCHAR(50) + condition_status_source_value: + nullable: true + primary: false + type: VARCHAR(50) + condition_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + stop_reason: + nullable: true + primary: false + type: VARCHAR(20) + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + cost: + columns: + amount_allowed: + nullable: true + primary: false + type: NUMERIC + cost_domain_id: + foreign_keys: + - domain.domain_id + nullable: false + primary: false + type: VARCHAR(20) + cost_event_id: + nullable: false + primary: false + type: BIGINT + cost_id: + nullable: false + primary: true + type: BIGINT + cost_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + currency_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + drg_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + drg_source_value: + nullable: true + primary: false + type: VARCHAR(3) + paid_by_patient: + nullable: true + primary: false + type: NUMERIC + paid_by_payer: + nullable: true + primary: false + type: NUMERIC + paid_by_primary: + nullable: true + primary: false + type: NUMERIC + paid_dispensing_fee: + nullable: true + primary: false + type: NUMERIC + paid_ingredient_cost: + nullable: true + primary: false + type: NUMERIC + paid_patient_coinsurance: + nullable: true + primary: false + type: NUMERIC + paid_patient_copay: + nullable: true + primary: false + type: NUMERIC + paid_patient_deductible: + nullable: true + primary: false + type: NUMERIC + payer_plan_period_id: + nullable: true + primary: false + type: BIGINT + revenue_code_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + revenue_code_source_value: + nullable: true + primary: false + type: VARCHAR(50) + total_charge: + nullable: true + primary: false + type: NUMERIC + total_cost: + nullable: true + primary: false + type: NUMERIC + total_paid: + nullable: true + primary: false + type: NUMERIC + unique: [] + death: + columns: + cause_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + cause_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + cause_source_value: + nullable: true + primary: false + type: VARCHAR(50) + death_date: + nullable: false + primary: false + type: DATE + death_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + death_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + device_exposure: + columns: + device_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + device_exposure_end_date: + nullable: true + primary: false + type: DATE + device_exposure_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + device_exposure_id: + nullable: false + primary: true + type: BIGINT + device_exposure_start_date: + nullable: false + primary: false + type: DATE + device_exposure_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + device_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + device_source_value: + nullable: true + primary: false + type: VARCHAR(50) + device_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: BIGINT + unique_device_id: + nullable: true + primary: false + type: VARCHAR(255) + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + domain: + columns: + domain_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + domain_id: + nullable: false + primary: true + type: VARCHAR(20) + domain_name: + nullable: false + primary: false + type: VARCHAR(255) + unique: [] + dose_era: + columns: + dose_era_end_date: + nullable: false + primary: false + type: DATE + dose_era_id: + nullable: false + primary: true + type: BIGINT + dose_era_start_date: + nullable: false + primary: false + type: DATE + dose_value: + nullable: false + primary: false + type: NUMERIC + drug_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + drug_era: + columns: + drug_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + drug_era_end_date: + nullable: false + primary: false + type: DATE + drug_era_id: + nullable: false + primary: true + type: BIGINT + drug_era_start_date: + nullable: false + primary: false + type: DATE + drug_exposure_count: + nullable: true + primary: false + type: BIGINT + gap_days: + nullable: true + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + drug_exposure: + columns: + days_supply: + nullable: true + primary: false + type: BIGINT + dose_unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) + drug_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + drug_exposure_end_date: + nullable: false + primary: false + type: DATE + drug_exposure_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + drug_exposure_id: + nullable: false + primary: true + type: BIGINT + drug_exposure_start_date: + nullable: false + primary: false + type: DATE + drug_exposure_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + drug_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + drug_source_value: + nullable: true + primary: false + type: VARCHAR(255) + drug_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + lot_number: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: NUMERIC + refills: + nullable: true + primary: false + type: BIGINT + route_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + route_source_value: + nullable: true + primary: false + type: VARCHAR(50) + sig: + nullable: true + primary: false + type: TEXT + stop_reason: + nullable: true + primary: false + type: VARCHAR(20) + verbatim_end_date: + nullable: true + primary: false + type: DATE + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + drug_strength: + columns: + amount_unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + amount_value: + nullable: true + primary: false + type: NUMERIC + box_size: + nullable: true + primary: false + type: BIGINT + denominator_unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + denominator_value: + nullable: true + primary: false + type: NUMERIC + drug_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + ingredient_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) + numerator_unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + numerator_value: + nullable: true + primary: false + type: NUMERIC + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + episode: + columns: + episode_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + episode_end_date: + nullable: true + primary: false + type: DATE + episode_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + episode_id: + nullable: false + primary: true + type: BIGINT + episode_number: + nullable: true + primary: false + type: BIGINT + episode_object_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + episode_parent_id: + nullable: true + primary: false + type: BIGINT + episode_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + episode_source_value: + nullable: true + primary: false + type: VARCHAR(50) + episode_start_date: + nullable: false + primary: false + type: DATE + episode_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + episode_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + episode_event: + columns: + episode_event_field_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + episode_id: + foreign_keys: + - episode.episode_id + nullable: false + primary: false + type: BIGINT + event_id: + nullable: false + primary: false + type: BIGINT + unique: [] + fact_relationship: + columns: + domain_concept_id_1: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + domain_concept_id_2: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + fact_id_1: + nullable: false + primary: false + type: BIGINT + fact_id_2: + nullable: false + primary: false + type: BIGINT + relationship_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + location: + columns: + address_1: + nullable: true + primary: false + type: VARCHAR(50) + address_2: + nullable: true + primary: false + type: VARCHAR(50) + city: + nullable: true + primary: false + type: VARCHAR(50) + county: + nullable: true + primary: false + type: VARCHAR(20) + location_id: + nullable: false + primary: true + type: BIGINT + location_source_value: + nullable: true + primary: false + type: VARCHAR(50) + state: + nullable: true + primary: false + type: VARCHAR(2) + zip: + nullable: true + primary: false + type: VARCHAR(9) + unique: [] + measurement: + columns: + measurement_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + measurement_date: + nullable: false + primary: false + type: DATE + measurement_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + measurement_id: + nullable: false + primary: true + type: BIGINT + measurement_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + measurement_source_value: + nullable: true + primary: false + type: VARCHAR(50) + measurement_time: + nullable: true + primary: false + type: VARCHAR(10) + measurement_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + operator_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + range_high: + nullable: true + primary: false + type: NUMERIC + range_low: + nullable: true + primary: false + type: NUMERIC + unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) + value_as_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC + value_source_value: + nullable: true + primary: false + type: VARCHAR(50) + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + metadata: + columns: + metadata_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + metadata_date: + nullable: true + primary: false + type: DATE + metadata_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + metadata_id: + nullable: false + primary: true + type: BIGINT + metadata_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + name: + nullable: false + primary: false + type: VARCHAR(250) + value_as_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC + value_as_string: + nullable: true + primary: false + type: VARCHAR(250) + unique: [] + note: + columns: + encoding_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + language_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + note_class_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + note_date: + nullable: false + primary: false + type: DATE + note_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + note_event_field_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + note_event_id: + nullable: true + primary: false + type: BIGINT + note_id: + nullable: false + primary: true + type: BIGINT + note_source_value: + nullable: true + primary: false + type: VARCHAR(50) + note_text: + nullable: false + primary: false + type: TEXT + note_title: + nullable: true + primary: false + type: VARCHAR(250) + note_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + note_nlp: + columns: + lexical_variant: + nullable: false + primary: false + type: VARCHAR(250) + nlp_date: + nullable: false + primary: false + type: DATE + nlp_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + nlp_system: + nullable: true + primary: false + type: VARCHAR(250) + note_id: + nullable: false + primary: false + type: BIGINT + note_nlp_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + note_nlp_id: + nullable: false + primary: true + type: BIGINT + note_nlp_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + offset: + nullable: true + primary: false + type: VARCHAR(50) + section_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + snippet: + nullable: true + primary: false + type: VARCHAR(250) + term_exists: + nullable: true + primary: false + type: VARCHAR(1) + term_modifiers: + nullable: true + primary: false + type: VARCHAR(2000) + term_temporal: + nullable: true + primary: false + type: VARCHAR(50) + unique: [] + observation: + columns: + observation_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + observation_date: + nullable: false + primary: false + type: DATE + observation_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + observation_id: + nullable: false + primary: true + type: BIGINT + observation_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + observation_source_value: + nullable: true + primary: false + type: VARCHAR(50) + observation_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + qualifier_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + qualifier_source_value: + nullable: true + primary: false + type: VARCHAR(50) + unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) + value_as_concept_id: + nullable: true + primary: false + type: BIGINT + value_as_number: + nullable: true + primary: false + type: NUMERIC + value_as_string: + nullable: true + primary: false + type: VARCHAR(120) + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + observation_period: + columns: + observation_period_end_date: + nullable: false + primary: false + type: DATE + observation_period_id: + nullable: false + primary: true + type: BIGINT + observation_period_start_date: + nullable: false + primary: false + type: DATE + period_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + unique: [] + payer_plan_period: + columns: + family_source_value: + nullable: true + primary: false + type: VARCHAR(50) + payer_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + payer_plan_period_end_date: + nullable: false + primary: false + type: DATE + payer_plan_period_id: + nullable: false + primary: true + type: BIGINT + payer_plan_period_start_date: + nullable: false + primary: false + type: DATE + payer_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + payer_source_value: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + plan_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + plan_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + plan_source_value: + nullable: true + primary: false + type: VARCHAR(50) + sponsor_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + sponsor_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + sponsor_source_value: + nullable: true + primary: false + type: VARCHAR(50) + stop_reason_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + stop_reason_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + stop_reason_source_value: + nullable: true + primary: false + type: VARCHAR(50) + unique: [] + person: + columns: + birth_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + care_site_id: + foreign_keys: + - care_site.care_site_id + nullable: true + primary: false + type: BIGINT + day_of_birth: + nullable: true + primary: false + type: BIGINT + ethnicity_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + ethnicity_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + ethnicity_source_value: + nullable: true + primary: false + type: VARCHAR(50) + gender_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + gender_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + gender_source_value: + nullable: true + primary: false + type: VARCHAR(50) + location_id: + foreign_keys: + - location.location_id + nullable: true + primary: false + type: BIGINT + month_of_birth: + nullable: true + primary: false + type: BIGINT + person_id: + nullable: false + primary: true + type: BIGINT + person_source_value: + nullable: true + primary: false + type: VARCHAR(50) + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + race_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + race_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + race_source_value: + nullable: true + primary: false + type: VARCHAR(50) + year_of_birth: + nullable: false + primary: false + type: BIGINT + unique: [] + procedure_occurrence: + columns: + modifier_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + modifier_source_value: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + procedure_concept_id: + nullable: false + primary: false + type: BIGINT + procedure_date: + nullable: false + primary: false + type: DATE + procedure_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + procedure_occurrence_id: + nullable: false + primary: true + type: BIGINT + procedure_source_concept_id: + nullable: true + primary: false + type: BIGINT + procedure_source_value: + nullable: true + primary: false + type: VARCHAR(50) + procedure_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: BIGINT + visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + unique: [] + provider: + columns: + care_site_id: + foreign_keys: + - care_site.care_site_id + nullable: true + primary: false + type: BIGINT + dea: + nullable: true + primary: false + type: VARCHAR(20) + gender_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + gender_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + gender_source_value: + nullable: true + primary: false + type: VARCHAR(50) + npi: + nullable: true + primary: false + type: VARCHAR(20) + provider_id: + nullable: false + primary: true + type: BIGINT + provider_name: + nullable: true + primary: false + type: VARCHAR(255) + provider_source_value: + nullable: true + primary: false + type: VARCHAR(50) + specialty_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + specialty_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + specialty_source_value: + nullable: true + primary: false + type: VARCHAR(50) + year_of_birth: + nullable: true + primary: false + type: BIGINT + unique: [] + relationship: + columns: + defines_ancestry: + nullable: false + primary: false + type: VARCHAR(1) + is_hierarchical: + nullable: false + primary: false + type: VARCHAR(1) + relationship_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + relationship_id: + nullable: false + primary: true + type: VARCHAR(20) + relationship_name: + nullable: false + primary: false + type: VARCHAR(255) + reverse_relationship_id: + nullable: false + primary: false + type: VARCHAR(20) + unique: [] + source_to_concept_map: + columns: + invalid_reason: + nullable: true + primary: false + type: VARCHAR(1) + source_code: + nullable: false + primary: false + type: VARCHAR(50) + source_code_description: + nullable: true + primary: false + type: VARCHAR(255) + source_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + source_vocabulary_id: + nullable: false + primary: false + type: VARCHAR(20) + target_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + target_vocabulary_id: + foreign_keys: + - vocabulary.vocabulary_id + nullable: false + primary: false + type: VARCHAR(20) + valid_end_date: + nullable: false + primary: false + type: DATE + valid_start_date: + nullable: false + primary: false + type: DATE + unique: [] + specimen: + columns: + anatomic_site_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + anatomic_site_source_value: + nullable: true + primary: false + type: VARCHAR(50) + disease_status_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + disease_status_source_value: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + quantity: + nullable: true + primary: false + type: NUMERIC + specimen_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + specimen_date: + nullable: false + primary: false + type: DATE + specimen_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + specimen_id: + nullable: false + primary: true + type: BIGINT + specimen_source_id: + nullable: true + primary: false + type: VARCHAR(255) + specimen_source_value: + nullable: true + primary: false + type: VARCHAR(50) + specimen_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unit_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + unit_source_value: + nullable: true + primary: false + type: VARCHAR(50) + unique: [] + visit_detail: + columns: + admitting_source_concept_id: + nullable: true + primary: false + type: BIGINT + admitting_source_value: + nullable: true + primary: false + type: VARCHAR(50) + care_site_id: + foreign_keys: + - care_site.care_site_id + nullable: true + primary: false + type: BIGINT + discharge_to_concept_id: + nullable: true + primary: false + type: BIGINT + discharge_to_source_value: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + preceding_visit_detail_id: + foreign_keys: + - visit_detail.visit_detail_id + nullable: true + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + visit_detail_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_detail_end_date: + nullable: false + primary: false + type: DATE + visit_detail_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + visit_detail_id: + nullable: false + primary: true + type: BIGINT + visit_detail_parent_id: + nullable: true + primary: false + type: VARCHAR(50) + visit_detail_source_concept_id: + nullable: true + primary: false + type: VARCHAR(50) + visit_detail_source_value: + nullable: true + primary: false + type: VARCHAR(120) + visit_detail_start_date: + nullable: false + primary: false + type: DATE + visit_detail_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + visit_detail_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: false + primary: false + type: BIGINT + unique: [] + visit_occurrence: + columns: + admitted_from_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + admitted_from_source_value: + nullable: true + primary: false + type: VARCHAR(50) + care_site_id: + foreign_keys: + - care_site.care_site_id + nullable: true + primary: false + type: BIGINT + discharged_to_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + discharged_to_source_value: + nullable: true + primary: false + type: VARCHAR(50) + person_id: + foreign_keys: + - person.person_id + nullable: false + primary: false + type: BIGINT + preceding_visit_occurrence_id: + foreign_keys: + - visit_occurrence.visit_occurrence_id + nullable: true + primary: false + type: BIGINT + provider_id: + foreign_keys: + - provider.provider_id + nullable: true + primary: false + type: BIGINT + visit_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + visit_end_date: + nullable: false + primary: false + type: DATE + visit_end_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + visit_occurrence_id: + nullable: false + primary: true + type: BIGINT + visit_source_concept_id: + foreign_keys: + - concept.concept_id + nullable: true + primary: false + type: BIGINT + visit_source_value: + nullable: true + primary: false + type: VARCHAR(50) + visit_start_date: + nullable: false + primary: false + type: DATE + visit_start_datetime: + nullable: true + primary: false + type: TIMESTAMP WITHOUT TIME ZONE + visit_type_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + unique: [] + vocabulary: + columns: + vocabulary_concept_id: + foreign_keys: + - concept.concept_id + nullable: false + primary: false + type: BIGINT + vocabulary_id: + nullable: false + primary: true + type: VARCHAR(30) + vocabulary_name: + nullable: false + primary: false + type: VARCHAR(255) + vocabulary_reference: + nullable: true + primary: false + type: VARCHAR(255) + vocabulary_version: + nullable: true + primary: false + type: VARCHAR(255) + unique: [] diff --git a/examples/omop-postgresql/src-stats.yaml b/examples/omop-postgresql/src-stats.yaml new file mode 100644 index 0000000..1f9fde3 --- /dev/null +++ b/examples/omop-postgresql/src-stats.yaml @@ -0,0 +1,193 @@ +auto__person__ethnicity_concept_id: + comments: + - All the values and their counts that appear in column ethnicity_concept_id of + table person + queries: + date: '2026-05-22 15:39:07' + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"ethnicity_concept_id\"\ + \ AS value, count(\"ethnicity_concept_id\") AS count \nFROM mimic.person \n\ + WHERE \"ethnicity_concept_id\" IS NOT NULL GROUP BY \"ethnicity_concept_id\"\ + ) AS _counted ORDER BY _counted.count DESC" + results: + - count: 95 + value: 0 + - count: 5 + value: 38003563 +auto__person__gender_concept_id: + comments: + - All the values and their counts that appear in column gender_concept_id of table + person + queries: + date: '2026-05-22 15:39:07' + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"gender_concept_id\"\ + \ AS value, count(\"gender_concept_id\") AS count \nFROM mimic.person \nWHERE\ + \ \"gender_concept_id\" IS NOT NULL GROUP BY \"gender_concept_id\") AS _counted\ + \ ORDER BY _counted.count DESC" + results: + - count: 57 + value: 8507 + - count: 43 + value: 8532 +auto__person__race_concept_id: + comments: + - All the values and their counts that appear in column race_concept_id of table + person + queries: + date: '2026-05-22 15:39:07' + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"race_concept_id\"\ + \ AS value, count(\"race_concept_id\") AS count \nFROM mimic.person \nWHERE\ + \ \"race_concept_id\" IS NOT NULL GROUP BY \"race_concept_id\") AS _counted\ + \ ORDER BY _counted.count DESC" + results: + - count: 64 + value: 8527 + - count: 13 + value: 2000001401 + - count: 10 + value: 8516 + - count: 5 + value: 0 + - count: 5 + value: 2000001402 + - count: 3 + value: 2000001405 +auto__person__year_of_birth: + comments: + - All the values and their counts that appear in column year_of_birth of table person + queries: + date: '2026-05-22 15:39:07' + query: "SELECT _counted.value, _counted.count \nFROM (SELECT \"year_of_birth\"\ + \ AS value, count(\"year_of_birth\") AS count \nFROM mimic.person \nWHERE \"\ + year_of_birth\" IS NOT NULL GROUP BY \"year_of_birth\") AS _counted ORDER BY\ + \ _counted.count DESC" + results: + - count: 4 + value: 2062 + - count: 3 + value: 2070 + - count: 3 + value: 2058 + - count: 3 + value: 2073 + - count: 3 + value: 2119 + - count: 3 + value: 2084 + - count: 3 + value: 2059 + - count: 2 + value: 2125 + - count: 2 + value: 2094 + - count: 2 + value: 2136 + - count: 2 + value: 2083 + - count: 2 + value: 2052 + - count: 2 + value: 2106 + - count: 2 + value: 2123 + - count: 2 + value: 2066 + - count: 2 + value: 2104 + - count: 2 + value: 2089 + - count: 2 + value: 2102 + - count: 2 + value: 2075 + - count: 2 + value: 2043 + - count: 2 + value: 2079 + - count: 2 + value: 2050 + - count: 2 + value: 2133 + - count: 2 + value: 2055 + - count: 2 + value: 2086 + - count: 2 + value: 2085 + - count: 2 + value: 2130 + - count: 1 + value: 2033 + - count: 1 + value: 2031 + - count: 1 + value: 2117 + - count: 1 + value: 2122 + - count: 1 + value: 2099 + - count: 1 + value: 2069 + - count: 1 + value: 2149 + - count: 1 + value: 2095 + - count: 1 + value: 2092 + - count: 1 + value: 2071 + - count: 1 + value: 2145 + - count: 1 + value: 2049 + - count: 1 + value: 2030 + - count: 1 + value: 2128 + - count: 1 + value: 2074 + - count: 1 + value: 2114 + - count: 1 + value: 2108 + - count: 1 + value: 2060 + - count: 1 + value: 2097 + - count: 1 + value: 2116 + - count: 1 + value: 2064 + - count: 1 + value: 2090 + - count: 1 + value: 2038 + - count: 1 + value: 2077 + - count: 1 + value: 2103 + - count: 1 + value: 2041 + - count: 1 + value: 2138 + - count: 1 + value: 2096 + - count: 1 + value: 2093 + - count: 1 + value: 2061 + - count: 1 + value: 2118 + - count: 1 + value: 2120 + - count: 1 + value: 2111 + - count: 1 + value: 2067 + - count: 1 + value: 2134 + - count: 1 + value: 2105 + - count: 1 + value: 2115 + - count: 1 + value: 2054 diff --git a/poetry.lock b/poetry.lock index a1a7356..6848430 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,19 @@ # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +[[package]] +name = "aioodbc" +version = "0.5.0" +description = "ODBC driver for asyncio." +optional = true +python-versions = ">=3.7" +files = [ + {file = "aioodbc-0.5.0-py3-none-any.whl", hash = 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["aioodbc", "pyodbc"] +postgres = ["psycopg2-binary"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.14" -content-hash = "e89f757d54ff2a3b3dfcfde7342b55e1394c114c7db337dcd8bc9a7c9dea37c1" +content-hash = "10e04ed26df40d14987fb7c9f55b24de4a1c252bdccb47cd293879d1e47e0c17" diff --git a/pyproject.toml b/pyproject.toml index b36b5dc..8b75a80 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,7 +17,9 @@ homepage = "https://github.com/SAFEHR-data/datafaker" [tool.poetry.dependencies] python = ">=3.10,<3.14" pydantic = {extras = ["dotenv"], version = "^1.10.2"} -psycopg2-binary = "^2.9.5" +psycopg2-binary = {version = "^2.9.5", optional = true} +pyodbc = {version = "^5.0.0", optional = true} +aioodbc = {version = "^0.5.0", optional = true} sqlalchemy-utils = "^0.41.2" mimesis = "^18.0.0" typer = "^0.15.4" @@ -54,12 +56,15 @@ duckdb = "^1.4.3" sphinx-rtd-theme = "^1.2.0" sphinxcontrib-napoleon = "^0.7" sphinxcontrib-mermaid = "^2.0.0" +pytest = "^9.0.3" 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Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (929, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (930, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (931, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (932, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (933, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (934, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (935, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (936, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (937, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (938, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (939, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (940, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (941, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (942, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (943, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (944, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (945, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (946, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (947, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (948, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (949, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (950, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (951, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (952, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (953, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (954, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (955, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (956, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (957, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (958, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (959, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (960, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (961, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (962, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (963, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (964, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (965, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (966, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (967, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (968, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (969, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (970, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (971, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (972, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (973, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (974, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (975, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (976, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (977, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (978, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (979, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (980, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (981, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (982, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (983, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (984, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (985, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (986, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (987, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (988, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (989, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (990, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (991, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (992, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (993, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (994, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (995, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (996, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (997, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (998, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (999, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (1000, 'Someone Random', true, '2023-03-01 00:00:00+00'); -- diff --git a/tests/examples/src2.dump b/tests/examples/src2.dump index 409622b..1e06d9b 100644 --- a/tests/examples/src2.dump +++ b/tests/examples/src2.dump @@ -226,1006 +226,1006 @@ INSERT INTO public.mitigation_type VALUES (2, 'panic', 'don''t hold back, flail -- Data for Name: person; Type: TABLE DATA; Schema: public; Owner: postgres -- -INSERT INTO public.person VALUES (1, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (2, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (3, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (4, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (5, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (6, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (7, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (8, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (9, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (10, 'Randy Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (1, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (2, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (3, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (4, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (5, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (6, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (7, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (8, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (9, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (10, 'Someone Random', true, '2023-03-01 00:00:00+00'); INSERT INTO public.person VALUES (11, 'Testfried Testermann', false, '2023-03-01 00:00:00+00'); INSERT INTO public.person VALUES (12, 'Veronica Fyre', false, '2023-03-01 00:00:00+00'); INSERT INTO public.person VALUES (13, 'Miranda Rando-Generata', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (14, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (15, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (16, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (17, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (18, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (19, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (20, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (21, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (22, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (23, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (24, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (25, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (26, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (27, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (28, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (29, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (30, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (31, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (32, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (33, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (34, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (35, 'Randy 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00:00:00+00'); -INSERT INTO public.person VALUES (47, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (48, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (49, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (50, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (51, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (52, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (53, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (54, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (55, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (56, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (57, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (58, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (59, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (60, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (61, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (62, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (63, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (64, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (65, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (66, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (67, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (68, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (69, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (70, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (71, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (72, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (73, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (74, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (75, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (76, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (77, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (78, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (79, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (80, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (81, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (82, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (83, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (84, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (85, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (86, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (87, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (88, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (89, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (90, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (91, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (92, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (93, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (94, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (95, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (96, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (97, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (98, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (99, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (100, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (101, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (102, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (103, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (104, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (105, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (106, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (107, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (108, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (109, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (110, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (111, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (112, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (113, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (114, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (115, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (116, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (117, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (118, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (119, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (120, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (121, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (122, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (123, 'Randy Random', true, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (124, 'Randy Random', false, '2023-03-01 00:00:00+00'); -INSERT INTO public.person VALUES (125, 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VALUES (978, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (979, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (980, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (981, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (982, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (983, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (984, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (985, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (986, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (987, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (988, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (989, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (990, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (991, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (992, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (993, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (994, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (995, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (996, 'Someone Random', true, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (997, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (998, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (999, 'Someone Random', false, '2023-03-01 00:00:00+00'); +INSERT INTO public.person VALUES (1000, 'Someone Random', true, '2023-03-01 00:00:00+00'); -- diff --git a/tests/test_create_mssql.py b/tests/test_create_mssql.py new file mode 100644 index 0000000..b7c42b3 --- /dev/null +++ b/tests/test_create_mssql.py @@ -0,0 +1,84 @@ +"""Tests for MS-SQL DDL compilation in datafaker.create.""" +import unittest + +from sqlalchemy import Column, ForeignKey, Integer, MetaData, String, Table +from sqlalchemy.dialects import mssql +from sqlalchemy.schema import CreateTable + +# Importing create registers the @compiles hooks globally. +import datafaker.create # noqa: F401 + + +def _compile_create_table(table: Table) -> str: + """Compile a CreateTable statement against the MS-SQL dialect.""" + return str(CreateTable(table).compile(dialect=mssql.dialect())) + + +class TestMSSQLIdentityPresent(unittest.TestCase): + """MS-SQL tables should have IDENTITY on autoincrement columns. + + The remove_mssql_identity hook was removed (issue #104): datafaker now lets + the database generate single-column integer PKs rather than supplying + explicit values and fighting with SET IDENTITY_INSERT. + """ + + def _make_table(self) -> Table: + meta = MetaData() + return Table( + "test_table", + meta, + Column("id", Integer(), primary_key=True, autoincrement=True), + Column("value", Integer(), nullable=True), + ) + + def test_identity_present_in_ddl(self) -> None: + """IDENTITY must be present so the DB generates PK values automatically.""" + ddl = _compile_create_table(self._make_table()) + self.assertIn("IDENTITY", ddl) + + def test_integer_type_preserved(self) -> None: + """The INTEGER type is preserved.""" + ddl = _compile_create_table(self._make_table()) + self.assertIn("INTEGER", ddl) + + def test_primary_key_constraint_preserved(self) -> None: + """PRIMARY KEY constraint is not affected.""" + ddl = _compile_create_table(self._make_table()) + self.assertIn("PRIMARY KEY", ddl) + + def test_non_autoincrement_column_unchanged(self) -> None: + """Non-autoincrement columns are not altered.""" + ddl = _compile_create_table(self._make_table()) + self.assertIn("value", ddl.lower()) + + +class TestMSSQLRemoveOnDeleteCascade(unittest.TestCase): + """@compiles(CreateTable, 'mssql') strips ON DELETE CASCADE to avoid error 1785.""" + + def _make_multi_fk_table(self) -> Table: + meta = MetaData() + concept = Table( + "concept", + meta, + Column("concept_id", Integer(), primary_key=True), + ) + return Table( + "person", + meta, + Column("person_id", Integer(), primary_key=True), + Column("gender_concept_id", Integer(), ForeignKey("concept.concept_id", ondelete="CASCADE")), + Column("race_concept_id", Integer(), ForeignKey("concept.concept_id", ondelete="CASCADE")), + ) + + def test_cascade_absent_from_mssql_ddl(self) -> None: + ddl = _compile_create_table(self._make_multi_fk_table()) + self.assertNotIn("ON DELETE CASCADE", ddl) + + def test_foreign_key_constraint_preserved(self) -> None: + ddl = _compile_create_table(self._make_multi_fk_table()) + self.assertIn("FOREIGN KEY", ddl) + + def test_duckdb_cascade_hook_still_works(self) -> None: + """Adding the mssql CASCADE hook does not break the DuckDB CASCADE hook.""" + self.assertTrue(callable(datafaker.create.remove_on_delete_cascade)) + self.assertTrue(callable(datafaker.create.remove_mssql_on_delete_cascade)) diff --git a/tests/test_functional_mssql.py b/tests/test_functional_mssql.py new file mode 100644 index 0000000..ce92847 --- /dev/null +++ b/tests/test_functional_mssql.py @@ -0,0 +1,284 @@ +"""End-to-end tests for the MS-SQL Server dialect. + +These tests require a running SQL Server instance. Set the ``MSSQL_TEST_DSN`` +environment variable to a ``mssql+pyodbc://`` connection string to enable them: + + export MSSQL_TEST_DSN="mssql+pyodbc://sa:Datafaker!Test123@localhost:1433/master?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes" + +With docker-compose: + + docker compose up -d mssql + # wait ~30 s for SQL Server to start +""" +import asyncio +import os +from tempfile import mkstemp + +from sqlalchemy import Column, DateTime, Float, ForeignKey, Integer, MetaData, String, Table, text +from sqlalchemy import create_engine as sa_create_engine +from sqlalchemy.schema import CreateTable + +import datafaker.create # noqa: F401 — registers @compiles hooks (e.g. strip ON DELETE CASCADE) +from datafaker.db_utils import create_db_engine, create_db_engine_dst, get_sync_engine +from datafaker.make import make_src_stats, make_tables_file +from tests.utils import DatafakerTestCase, GeneratesDBTestCase, TestMSSQL + +import yaml + + +# --------------------------------------------------------------------------- +# Instrument schema (mirrors tests/examples/instrument.sql in dialect-neutral +# SQLAlchemy — avoids the need for a T-SQL .sql fixture file). +# --------------------------------------------------------------------------- + +def _make_src_metadata() -> MetaData: + meta = MetaData() + manufacturer = Table( + "manufacturer", + meta, + Column("id", Integer, primary_key=True, autoincrement=False), + Column("name", String(200), nullable=False), + Column("founded", DateTime, nullable=False), + ) + model = Table( + "model", + meta, + Column("id", Integer, primary_key=True, autoincrement=False), + Column("name", String(200), nullable=False), + Column( + "manufacturer_id", + Integer, + ForeignKey("manufacturer.id", ondelete="CASCADE"), + nullable=False, + ), + Column("introduced", DateTime, nullable=False), + ) + string_table = Table( + "string", + meta, + Column("id", Integer, primary_key=True, autoincrement=False), + Column( + "model_id", + Integer, + ForeignKey("model.id", ondelete="CASCADE"), + nullable=False, + ), + Column("position", Integer, nullable=False), + Column("frequency", Float, nullable=False), + ) + player = Table( + "player", + meta, + Column("id", Integer, primary_key=True, autoincrement=False), + Column("given_name", String(200), nullable=False), + Column("family_name", String(200), nullable=False), + ) + Table( + "signature_model", + meta, + Column("id", Integer, primary_key=True, autoincrement=False), + Column("name", String(20), nullable=False), + Column("player_id", Integer, ForeignKey("player.id"), nullable=True), + Column("based_on", Integer, ForeignKey("model.id"), nullable=True), + ) + # suppress "unused variable" warnings + _ = manufacturer, model, string_table, player + return meta + + +_SRC_METADATA = _make_src_metadata() + +_EXPECTED_TABLES = frozenset( + {"manufacturer", "model", "string", "player", "signature_model"} +) + + +def _insert_sample_rows(engine) -> None: + """Insert a minimal set of rows so make-stats has data to summarise.""" + with engine.begin() as conn: + conn.execute( + _SRC_METADATA.tables["manufacturer"].insert(), + [ + {"id": 1, "name": "Blender", "founded": "1951-01-08 04:05:06"}, + {"id": 2, "name": "Gibbs", "founded": "1959-03-04 07:08:09"}, + ], + ) + conn.execute( + _SRC_METADATA.tables["model"].insert(), + [ + {"id": 1, "name": "S-Type", "manufacturer_id": 1, "introduced": "1952-04-20 04:05:06"}, + {"id": 2, "name": "Pulse", "manufacturer_id": 1, "introduced": "1953-12-02 02:15:06"}, + {"id": 3, "name": "Paul Leslie", "manufacturer_id": 2, "introduced": "1960-02-20 04:05:06"}, + ], + ) + conn.execute( + _SRC_METADATA.tables["string"].insert(), + [ + {"id": 1, "model_id": 1, "position": 1, "frequency": 329.6}, + {"id": 2, "model_id": 1, "position": 2, "frequency": 246.94}, + {"id": 3, "model_id": 2, "position": 1, "frequency": 98.0}, + {"id": 4, "model_id": 3, "position": 1, "frequency": 329.6}, + ], + ) + conn.execute( + _SRC_METADATA.tables["player"].insert(), + [ + {"id": 1, "given_name": "Mark", "family_name": "Samson"}, + {"id": 2, "given_name": "Tim", "family_name": "Friedman"}, + ], + ) + conn.execute( + _SRC_METADATA.tables["signature_model"].insert(), + [ + {"id": 1, "name": "Flame", "player_id": 1, "based_on": None}, + {"id": 2, "name": "Dragon", "player_id": None, "based_on": 1}, + {"id": 3, "name": "Veleno", "player_id": 2, "based_on": 2}, + ], + ) + + +# --------------------------------------------------------------------------- +# Test case +# --------------------------------------------------------------------------- + + +class MSSQLFunctionalTestCase(GeneratesDBTestCase): + """End-to-end tests exercising the full datafaker pipeline against SQL Server.""" + + database_type = TestMSSQL + dump_file_path = None # schema created in Python, not from a .sql file + + # Database names created inside SQL Server for this test run. + database_name = "datafaker_test_src" + _DST_DB = "dst" + + def setUp(self) -> None: + """Create the source schema programmatically and wire up test-case fields. + + Bypasses RequiresDBTestCase.setUp (which calls run_sql) and reimplements + the relevant parts so we can build the schema with SQLAlchemy MetaData. + """ + # DatafakerTestCase.setUp handles CWD bookkeeping without touching the DB. + DatafakerTestCase.setUp(self) + + TestMSSQL.setup() + self.database = TestMSSQL() + self.database.open() + + # Create the source database, build schema, and seed rows. + src_dsn = self.database.create_empty(self.database_name) + src_engine = sa_create_engine(src_dsn) + _SRC_METADATA.create_all(src_engine) + _insert_sample_rows(src_engine) + src_engine.dispose() + + # Engine used by GeneratesDBTestCase helper methods (create_tables, etc.). + self.engine = create_db_engine(src_dsn, schema_name=self.schema_name) + self.sync_engine = get_sync_engine(self.engine) + self.metadata = MetaData() + self.metadata.reflect(self.sync_engine) + + # Empty destination database — create-tables will build the schema there. + self.dst_database = TestMSSQL() + self.dst_database.open() + dst_dsn = self.dst_database.create_empty(self._DST_DB) + self.dst_name = self._DST_DB + self.dst_metadata = MetaData() + self.dst_engine = get_sync_engine( + create_db_engine_dst(dst_dsn, schema_name=self.dst_schema_name) + ) + + # Write orm.yaml so generate_data() has the file it expects. + (self.orm_fd, self.orm_file_path) = mkstemp(".yaml", "orm_", text=True) + with os.fdopen(self.orm_fd, "w", encoding="utf-8") as fh: + fh.write(make_tables_file(src_dsn, self.schema_name, engine=self.sync_engine)) + + # Initialise stats/config path attributes expected by generate_data(). + self.stats_fd = 0 + self.stats_file_path = "" + self.config_file_path = "" + self.config_fd = 0 + + def tearDown(self) -> None: + # Dispose connection pools so the next setUp can drop these databases. + if hasattr(self, "sync_engine"): + self.sync_engine.dispose() + if hasattr(self, "dst_engine") and self.dst_engine is not None: + self.dst_engine.dispose() + if self.database is not None: + self.database.close() + if self.dst_database is not None: + self.dst_database.close() + DatafakerTestCase.tearDown(self) + + # ------------------------------------------------------------------ + # Tests + # ------------------------------------------------------------------ + + def test_smoke_connect(self) -> None: + """ODBC driver can connect and run a trivial query.""" + engine = sa_create_engine(self.dsn) + with engine.connect() as conn: + row = conn.execute(text("SELECT 1 AS n")).fetchone() + self.assertIsNotNone(row) + self.assertEqual(row[0], 1) + + def test_make_tables(self) -> None: + """make_tables_file produces an orm.yaml listing the expected tables.""" + # setUp already called make_tables_file and wrote the result to orm_file_path + with open(self.orm_file_path, encoding="utf-8") as fh: + orm = yaml.safe_load(fh) + # orm["tables"] is a dict keyed by table name + table_names = set(orm.get("tables", {}).keys()) + self.assert_subset(_EXPECTED_TABLES, table_names) + + def test_make_stats(self) -> None: + """make_src_stats runs without error against SQL Server. + + With an empty config there are no src-stats query blocks to run, so the + function returns an empty dict — that is the correct behaviour. + """ + loop = asyncio.new_event_loop() + try: + src_stats = loop.run_until_complete( + make_src_stats(self.dsn, {}, self.schema_name) + ) + finally: + loop.close() + self.assertIsInstance(src_stats, dict) + + def test_create_data(self) -> None: + """Full pipeline: make-stats → create-tables → create-data inserts rows.""" + self.generate_data({}) + + # Verify that at least the manufacturer table received rows. + assert self.dst_engine is not None + with self.dst_engine.connect() as conn: + count = conn.execute(text("SELECT COUNT(*) FROM manufacturer")).scalar() + self.assertGreater(count, 0, "Expected rows in manufacturer after create-data") + + def test_dialect_newid(self) -> None: + """ChoiceProposer compiles its query with NEWID() not RANDOM() for mssql.""" + from sqlalchemy.dialects import mssql as mssql_dialect # noqa: PLC0415 + from datafaker.proposers.choice import ZipfChoiceProposer # noqa: PLC0415 + + dialect = mssql_dialect.dialect() + proposer = ZipfChoiceProposer( + table_name="manufacturer", + column_name="name", + values=["Blender", "Gibbs"], + counts=[5, 5], + sample_count=2, + dialect=dialect, + ) + self.assertIn("newid()", proposer._query.lower()) + self.assertNotIn("random()", proposer._query.lower()) + + def test_cascade_stripped(self) -> None: + """The @compiles(CreateTable, 'mssql') hook strips ON DELETE CASCADE.""" + from sqlalchemy.dialects import mssql as mssql_dialect # noqa: PLC0415 + + model_table = _SRC_METADATA.tables["model"] + ddl = str(CreateTable(model_table).compile(dialect=mssql_dialect.dialect())) + self.assertIn("FOREIGN KEY", ddl) + self.assertNotIn("ON DELETE CASCADE", ddl) diff --git a/tests/test_generators_dialect.py b/tests/test_generators_dialect.py new file mode 100644 index 0000000..ff6c6c1 --- /dev/null +++ b/tests/test_generators_dialect.py @@ -0,0 +1,539 @@ +"""Tests for dialect-correct SQL in generator classes.""" +import unittest +import unittest.mock +from unittest.mock import MagicMock + +from sqlalchemy import Column, Integer, MetaData, Table +from sqlalchemy.dialects import mssql, postgresql +from sqlalchemy.types import DateTime + + +class TestMimesisDateTimeDialect(unittest.TestCase): + """MimesisDateTimeGenerator.make_singleton compiles year expressions per dialect.""" + + def _make_column(self) -> Column: + meta = MetaData() + t = Table("person", meta, Column("birth_datetime", DateTime())) + return t.c.birth_datetime + + def _make_engine(self, dialect) -> MagicMock: + engine = MagicMock() + engine.dialect = dialect() + result = MagicMock() + result.start = 1950 + result.end = 2000 + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + conn.execute.return_value.first.return_value = result + engine.connect.return_value = conn + return engine + + def test_postgresql_uses_extract(self) -> None: + """PostgreSQL year clause uses EXTRACT.""" + from datafaker.proposers.mimesis import MimesisDateTimeProposer + + column = self._make_column() + engine = self._make_engine(postgresql.dialect) + gens = MimesisDateTimeProposer.make_singleton(column, engine, "datetime.datetime") + self.assertEqual(len(gens), 1) + clauses = gens[0].select_aggregate_clauses() + min_clause = clauses["birth_datetime__start"]["clause"] + max_clause = clauses["birth_datetime__end"]["clause"] + self.assertIn("EXTRACT", min_clause.upper()) + self.assertIn("EXTRACT", max_clause.upper()) + self.assertNotIn("DATEPART", min_clause.upper()) + + def test_mssql_uses_datepart(self) -> None: + """MS-SQL year clause uses DATEPART.""" + from datafaker.proposers.mimesis import MimesisDateTimeProposer + + column = self._make_column() + engine = self._make_engine(mssql.dialect) + gens = MimesisDateTimeProposer.make_singleton(column, engine, "datetime.datetime") + self.assertEqual(len(gens), 1) + clauses = gens[0].select_aggregate_clauses() + min_clause = clauses["birth_datetime__start"]["clause"] + max_clause = clauses["birth_datetime__end"]["clause"] + self.assertIn("DATEPART", min_clause.upper()) + self.assertIn("DATEPART", max_clause.upper()) + self.assertNotIn("EXTRACT", min_clause.upper()) + + +class TestBucketsStddevDialect(unittest.TestCase): + """Buckets.make_buckets uses STDEV on MS-SQL and STDDEV on other dialects.""" + + def _make_engine_with_dialect_name(self, dialect_name: str) -> MagicMock: + engine = MagicMock() + engine.dialect.name = dialect_name + result = MagicMock() + result.stddev = 5.0 + result.mean = 42.0 + # count attribute via getattr + result.configure_mock(**{"count": 100}) + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + conn.execute.return_value.first.return_value = result + engine.connect.return_value = conn + return engine + + def _get_executed_sql(self, dialect_name: str) -> str: + from datafaker.proposers.base import Buckets + + engine = self._make_engine_with_dialect_name(dialect_name) + # make_buckets will call engine.connect().execute(stmt) + # We patch it to capture the compiled SQL + executed_stmts = [] + orig_execute = engine.connect.return_value.execute + + def capture_execute(stmt, *args, **kwargs): + executed_stmts.append(stmt) + return orig_execute(stmt, *args, **kwargs) + + engine.connect.return_value.execute = capture_execute + # Prevent the Buckets constructor from running (it uses a separate query) + tbl = Table("person", MetaData(), Column("age", Integer())) + with unittest.mock.patch.object(Buckets, "__init__", return_value=None): + Buckets.make_buckets(engine, tbl, tbl.c.age) + + self.assertEqual(len(executed_stmts), 1) + compiled = str(executed_stmts[0].compile( + dialect=mssql.dialect() if dialect_name == "mssql" else postgresql.dialect(), + compile_kwargs={"literal_binds": True}, + )) + return compiled.upper() + + def test_postgresql_uses_stddev(self) -> None: + """PostgreSQL query uses STDDEV function.""" + import unittest.mock + sql = self._get_executed_sql("postgresql") + self.assertIn("STDDEV(", sql) # function call form + + def test_mssql_uses_stdev(self) -> None: + """MS-SQL query uses STDEV function (no trailing D).""" + sql = self._get_executed_sql("mssql") + self.assertIn("STDEV(", sql) + self.assertNotIn("STDDEV(", sql) # function call form only, not the alias + + +class TestChoiceGeneratorStoredQuery(unittest.TestCase): + """ChoiceGenerator._query is compiled to dialect-correct SQL at construction time.""" + + def _make_gen(self, dialect, sample_count=None, suppress_count=0): + from datafaker.proposers.choice import ZipfChoiceProposer + return ZipfChoiceProposer( + table_name="patient", + column_name="gender", + values=["M", "F"], + counts=[70, 30], + sample_count=sample_count, + suppress_count=suppress_count, + dialect=dialect, + ) + + def test_postgresql_sample_uses_random_and_limit(self) -> None: + """PostgreSQL stored query uses random() and LIMIT for sampled path.""" + gen = self._make_gen(postgresql.dialect(), sample_count=500) + sql = gen._query.upper() + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn(" TOP ", sql) + + def test_mssql_sample_uses_newid_and_top(self) -> None: + """MS-SQL stored query uses newid() and TOP for sampled path.""" + gen = self._make_gen(mssql.dialect(), sample_count=500) + sql = gen._query.upper() + self.assertIn("NEWID()", sql) + self.assertIn(" TOP ", sql) + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("LIMIT", sql) + + def test_mssql_suppress_has_no_order_by(self) -> None: + """MS-SQL suppress-only path emits no ORDER BY (was rejected without TOP).""" + gen = self._make_gen(mssql.dialect(), suppress_count=7) + sql = gen._query.upper() + self.assertNotIn("ORDER BY", sql) + + def test_mssql_sample_and_suppress_uses_newid_and_top(self) -> None: + """MS-SQL sample+suppress path uses newid()/TOP and no LIMIT/RANDOM.""" + gen = self._make_gen(mssql.dialect(), sample_count=500, suppress_count=7) + sql = gen._query.upper() + self.assertIn("NEWID()", sql) + self.assertIn(" TOP ", sql) + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("LIMIT", sql) + + def test_no_sample_no_suppress_has_no_random_or_limit(self) -> None: + """No-sample path never includes RANDOM/LIMIT regardless of dialect.""" + for dialect in (postgresql.dialect(), mssql.dialect()): + with self.subTest(dialect=dialect.name): + gen = self._make_gen(dialect) + sql = gen._query.upper() + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn("LIMIT", sql) + self.assertNotIn(" TOP ", sql) + + +class TestChoiceGeneratorFactoryLiveQueries(unittest.TestCase): + """ChoiceGeneratorFactory.get_generators executes dialect-correct live SQL.""" + + def _captured_sqls(self, dialect, schema=None) -> list[str]: + """Run get_proposers with a mocked engine and return compiled SQL strings.""" + from datafaker.proposers.choice import ChoiceProposerFactory + + engine = MagicMock() + engine.dialect = dialect + + row_count = MagicMock() + row_count.v = "M" + row_count.f = 70 + result_count = MagicMock() + result_count.rowcount = 1 + result_count.__iter__ = MagicMock(return_value=iter([row_count])) + + row_sample = MagicMock() + row_sample.v = "M" + row_sample.f = 70 + result_sample = MagicMock() + result_sample.__iter__ = MagicMock(return_value=iter([row_sample])) + + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + engine.connect.return_value = conn + + executed = [] + results_queue = [result_count, result_sample] + + def capture(stmt, *args, **kwargs): + executed.append(stmt) + return results_queue[len(executed) - 1] + + conn.execute.side_effect = capture + + meta = MetaData() + tbl = Table("patient", meta, Column("gender", Integer()), schema=schema) + ChoiceProposerFactory().get_proposers([tbl.c.gender], engine) + + return [ + str(s.compile(dialect=dialect, compile_kwargs={"literal_binds": True})).upper() + for s in executed + ] + + def test_mssql_live_queries_use_top_and_newid(self) -> None: + """MS-SQL live queries use TOP (not LIMIT) and newid() (not random()).""" + sqls = self._captured_sqls(mssql.dialect()) + self.assertIn(" TOP ", sqls[0]) + self.assertNotIn("LIMIT", sqls[0]) + self.assertIn(" TOP ", sqls[1]) + self.assertIn("NEWID()", sqls[1]) + self.assertNotIn("LIMIT", sqls[1]) + self.assertNotIn("RANDOM()", sqls[1]) + + def test_postgresql_live_queries_use_limit_and_random(self) -> None: + """PostgreSQL live queries use LIMIT and random().""" + sqls = self._captured_sqls(postgresql.dialect()) + self.assertIn("LIMIT", sqls[0]) + self.assertNotIn(" TOP ", sqls[0]) + self.assertIn("LIMIT", sqls[1]) + self.assertIn("RANDOM()", sqls[1]) + self.assertNotIn(" TOP ", sqls[1]) + self.assertNotIn("NEWID()", sqls[1]) + + def test_schema_qualified_table_appears_in_from(self) -> None: + """Schema-qualified table name is included in the FROM clause on both dialects.""" + for dialect in (mssql.dialect(), postgresql.dialect()): + with self.subTest(dialect=dialect.name): + sqls = self._captured_sqls(dialect, schema="myschema") + for sql in sqls: + self.assertIn("MYSCHEMA", sql) + + +class TestBucketsSchemaQualified(unittest.TestCase): + """Buckets.make_buckets respects the schema of the src_table argument.""" + + def _make_engine(self, dialect_name: str) -> MagicMock: + engine = MagicMock() + engine.dialect.name = dialect_name + result = MagicMock() + result.stddev = 5.0 + result.mean = 42.0 + result.configure_mock(**{"count": 100}) + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + conn.execute.return_value.first.return_value = result + conn.execute.return_value.__iter__ = MagicMock(return_value=iter([])) + engine.connect.return_value = conn + return engine + + def _get_make_buckets_sql(self, dialect_name: str, schema: str | None) -> str: + from datafaker.proposers.base import Buckets + + engine = self._make_engine(dialect_name) + meta = MetaData() + tbl = Table("person", meta, Column("age", Integer()), schema=schema) + + executed_stmts = [] + orig_execute = engine.connect.return_value.execute + + def capture_execute(stmt, *args, **kwargs): + executed_stmts.append(stmt) + return orig_execute(stmt, *args, **kwargs) + + engine.connect.return_value.execute = capture_execute + + with unittest.mock.patch.object(Buckets, "__init__", return_value=None): + Buckets.make_buckets(engine, tbl, tbl.c.age) + + self.assertGreaterEqual(len(executed_stmts), 1) + dialect = mssql.dialect() if dialect_name == "mssql" else postgresql.dialect() + return str(executed_stmts[0].compile( + dialect=dialect, + compile_kwargs={"literal_binds": True}, + )).upper() + + def test_schema_appears_in_from_mssql(self) -> None: + """MS-SQL make_buckets query includes schema in FROM clause.""" + sql = self._get_make_buckets_sql("mssql", schema="myschema") + self.assertIn("MYSCHEMA", sql) + + def test_schema_appears_in_from_postgresql(self) -> None: + """PostgreSQL make_buckets query includes schema in FROM clause.""" + sql = self._get_make_buckets_sql("postgresql", schema="myschema") + self.assertIn("MYSCHEMA", sql) + + def test_no_schema_omits_qualifier(self) -> None: + """Without schema, FROM clause has no schema.table qualifier.""" + sql = self._get_make_buckets_sql("postgresql", schema=None) + # A schema qualifier would appear as "SCHEMA.PERSON"; no dot before the table name. + self.assertNotIn(".PERSON", sql) + + +class TestCovariateQueryDialect(unittest.TestCase): + """CovariateQuery._inner_query() uses TOP/NEWID on MS-SQL and RANDOM/LIMIT elsewhere.""" + + def _make_factory(self) -> MagicMock: + factory = MagicMock() + factory.query_predicate.return_value = "" + return factory + + def _inner_query(self, dialect_name: str) -> str: + from datafaker.proposers.continuous import CovariateQuery + + cq = ( + CovariateQuery("person", self._make_factory(), dialect_name=dialect_name) + .sample_count(500) + ) + return cq._inner_query().upper() + + def test_mssql_uses_top_and_newid(self) -> None: + """MS-SQL inner query uses SELECT TOP n … ORDER BY NEWID().""" + sql = self._inner_query("mssql") + self.assertIn("TOP 500", sql) + self.assertIn("NEWID()", sql) + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("LIMIT", sql) + + def test_postgresql_uses_random_and_limit(self) -> None: + """PostgreSQL inner query uses ORDER BY RANDOM() LIMIT n.""" + sql = self._inner_query("postgresql") + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT 500", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn("TOP", sql) + + def test_no_sample_count_has_no_random_or_limit(self) -> None: + """When sample_count is None no random ordering is emitted.""" + from datafaker.proposers.continuous import CovariateQuery + + for dialect in ("mssql", "postgresql", ""): + with self.subTest(dialect=dialect): + cq = CovariateQuery("person", self._make_factory(), dialect_name=dialect) + sql = cq._inner_query().upper() + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn("LIMIT", sql) + self.assertNotIn("TOP", sql) + + +class TestMissingnessQueryDialect(unittest.TestCase): + """MissingnessType.sampled_query() produces dialect-correct SQL.""" + + def test_mssql_uses_top_and_newid(self) -> None: + """MS-SQL sampled query uses SELECT TOP n … ORDER BY NEWID().""" + from datafaker.interactive.missingness import MissingnessType + + sql = MissingnessType.sampled_query( + "person", 1000, ["col_a", "col_b"], dialect_name="mssql" + ).upper() + self.assertIn("TOP 1000", sql) + self.assertIn("NEWID()", sql) + self.assertNotIn("RANDOM()", sql) + self.assertNotIn("LIMIT", sql) + + def test_default_uses_random_and_limit(self) -> None: + """Default (no dialect) sampled query uses RANDOM() and LIMIT.""" + from datafaker.interactive.missingness import MissingnessType + + sql = MissingnessType.sampled_query("person", 1000, ["col_a"]).upper() + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT 1000", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn("TOP", sql) + + def test_mssql_result_contains_column_null_checks(self) -> None: + """MS-SQL sampled query retains IS NULL expressions for the named columns.""" + from datafaker.interactive.missingness import MissingnessType + + sql = MissingnessType.sampled_query( + "person", 500, ["gender_concept_id"], dialect_name="mssql" + ) + self.assertIn("gender_concept_id IS NULL", sql) + self.assertIn("gender_concept_id__is_null", sql) + + +class TestLogNormalGeneratorSchemaQualified(unittest.TestCase): + """ContinuousLogDistributionGeneratorFactory respects src_table schema.""" + + def _get_sql(self, schema: str | None) -> str: + from datafaker.proposers.continuous import ContinuousLogDistributionProposerFactory + + meta = MetaData() + tbl = Table("person", meta, Column("age", Integer()), schema=schema) + + executed_stmts = [] + result = MagicMock() + result.logmean = 1.0 + result.logstddev = 0.5 + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + orig_execute = MagicMock(return_value=MagicMock(first=MagicMock(return_value=result))) + + def capture(stmt, *args, **kwargs): + executed_stmts.append(stmt) + return orig_execute(stmt, *args, **kwargs) + + conn.execute.side_effect = capture + engine = MagicMock() + engine.connect.return_value = conn + + from datafaker.proposers.base import Buckets + import unittest.mock + + buckets = MagicMock(spec=Buckets) + factory = ContinuousLogDistributionProposerFactory() + with unittest.mock.patch.object(Buckets, "make_buckets", return_value=buckets): + factory._get_generators_from_buckets(engine, tbl, "age", buckets) + + self.assertEqual(len(executed_stmts), 1) + dialect = postgresql.dialect() + return str(executed_stmts[0].compile( + dialect=dialect, + compile_kwargs={"literal_binds": True}, + )).upper() + + def test_schema_appears_in_from(self) -> None: + """_get_generators_from_buckets includes schema in FROM clause.""" + sql = self._get_sql(schema="myschema") + self.assertIn("MYSCHEMA", sql) + + def test_no_schema_omits_qualifier(self) -> None: + """Without schema, FROM clause has no schema prefix.""" + sql = self._get_sql(schema=None) + self.assertIn("FROM PERSON", sql) + self.assertNotIn("FROM MYSCHEMA", sql) + + +class TestPredefinedGeneratorSchemaQualified(unittest.TestCase): + """PredefinedGenerator parses aggregate clauses from schema-qualified SQL.""" + + def _make_config(self, table_sql_name: str) -> dict: + return { + "tables": { + "person": { + "row_generators": [ + { + "name": "dist_gen.gaussian", + "columns_assigned": ["age"], + "kwargs": { + "mean": f'SRC_STATS["auto__person"]["results"][0]["mean__age"]', + "sd": f'SRC_STATS["auto__person"]["results"][0]["sd__age"]', + }, + } + ] + } + }, + "src-stats": [ + { + "name": "auto__person", + "query": f"SELECT AVG(age) AS mean__age, STDDEV(age) AS sd__age FROM {table_sql_name}", + "comments": [], + } + ], + } + + def test_unqualified_name_parses_clauses(self) -> None: + """PredefinedProposer parses select_aggregate_clauses from unqualified FROM.""" + from datafaker.proposers.base import PredefinedProposer + + config = self._make_config("person") + rg = config["tables"]["person"]["row_generators"][0] + gen = PredefinedProposer("person", rg, config) + self.assertIn("mean__age", gen.select_aggregate_clauses()) + self.assertIn("sd__age", gen.select_aggregate_clauses()) + + def test_schema_qualified_name_parses_clauses(self) -> None: + """PredefinedProposer parses select_aggregate_clauses from schema-qualified FROM.""" + from datafaker.proposers.base import PredefinedProposer + + config = self._make_config("myschema.person") + rg = config["tables"]["person"]["row_generators"][0] + gen = PredefinedProposer("person", rg, config) + self.assertIn("mean__age", gen.select_aggregate_clauses()) + self.assertIn("sd__age", gen.select_aggregate_clauses()) + + +class TestAggregateQuerySchemaQualified(unittest.TestCase): + """_get_aggregate_query qualifies table names using the engine's schema_translate_map.""" + + def _make_engine(self, schema: str | None) -> MagicMock: + engine = MagicMock() + schema_map = {None: schema} if schema else {} + engine.get_execution_options.return_value = {"schema_translate_map": schema_map} + return engine + + def _make_gen(self) -> MagicMock: + from datafaker.proposers.base import Proposer + + gen = MagicMock(spec=Proposer) + gen.select_aggregate_clauses.return_value = { + "mean__age": {"clause": "AVG(age)", "comment": None} + } + return gen + + def test_aggregate_query_includes_schema(self) -> None: + """get_aggregate_query qualifies the bare table name when engine has a schema map.""" + from datafaker.interactive.generators import get_aggregate_query + + engine = self._make_engine("myschema") + gen = self._make_gen() + result = get_aggregate_query([gen], "person", engine) + self.assertIsNotNone(result) + self.assertIn("myschema.person", result) + + def test_aggregate_query_no_schema(self) -> None: + """get_aggregate_query uses the bare name when no schema is set.""" + from datafaker.interactive.generators import get_aggregate_query + + engine = self._make_engine(None) + gen = self._make_gen() + result = get_aggregate_query([gen], "person", engine) + self.assertIsNotNone(result) + self.assertIn("person", result) + # No schema qualifier (schema.table) should appear after FROM + self.assertNotIn(".", result.split("FROM ")[-1].strip('"').strip()) diff --git a/tests/test_interactive_dialect.py b/tests/test_interactive_dialect.py new file mode 100644 index 0000000..4c38db8 --- /dev/null +++ b/tests/test_interactive_dialect.py @@ -0,0 +1,215 @@ +"""Tests for dialect-correct SQL in interactive shell methods.""" +import unittest +from unittest.mock import MagicMock + +from sqlalchemy import Column, Integer, MetaData, Table +from sqlalchemy.dialects import mssql, postgresql + + +def _make_engine(dialect) -> MagicMock: + """Return a mock engine whose dialect is the given SQLAlchemy dialect instance.""" + engine = MagicMock() + engine.dialect = dialect + conn = MagicMock() + conn.__enter__ = MagicMock(return_value=conn) + conn.__exit__ = MagicMock(return_value=False) + executed = [] + + def capture(stmt, *args, **kwargs): + executed.append(stmt) + result = MagicMock() + result.keys.return_value = [] + result.fetchmany.return_value = [] + result.all.return_value = [] + return result + + conn.execute.side_effect = capture + engine.connect.return_value = conn + engine._executed = executed + return engine + + +def _make_table(schema=None) -> Table: + meta = MetaData() + return Table("person", meta, Column("gender_concept_id", Integer()), schema=schema) + + +def _compiled(stmt, dialect) -> str: + return str(stmt.compile(dialect=dialect, compile_kwargs={"literal_binds": True})).upper() + + +class TestPeekDialect(unittest.TestCase): + """DbCmd.do_peek() uses NEWID/TOP on MS-SQL and RANDOM/LIMIT on PostgreSQL.""" + + def _run_peek(self, dialect_instance, col_names=None, schema=None): + from datafaker.interactive.base import DbCmd + + engine = _make_engine(dialect_instance) + shell = MagicMock(spec=DbCmd) + shell.sync_engine = engine + shell.table_index = 0 + shell._table_entries = [MagicMock()] + shell.table_name.return_value = "person" + shell._get_column_names.return_value = col_names or ["gender_concept_id"] + shell.table_metadata.return_value = _make_table(schema=schema) + shell.print_table = MagicMock() + shell.print = MagicMock() + + DbCmd.do_peek(shell, " ".join(col_names) if col_names else "") + return engine._executed, dialect_instance + + def test_mssql_peek_uses_newid_and_top(self) -> None: + """MS-SQL do_peek compiles to TOP … NEWID().""" + executed, dialect = self._run_peek(mssql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("TOP", sql) + self.assertIn("NEWID()", sql) + self.assertNotIn("LIMIT", sql) + self.assertNotIn("RANDOM()", sql) + + def test_postgresql_peek_uses_random_and_limit(self) -> None: + """PostgreSQL do_peek compiles to RANDOM() … LIMIT.""" + executed, dialect = self._run_peek(postgresql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn(" TOP ", sql) + + def test_schema_appears_in_from(self) -> None: + """Schema-qualified table name appears in the FROM clause on both dialects.""" + for dialect in (mssql.dialect(), postgresql.dialect()): + with self.subTest(dialect=dialect.name): + executed, d = self._run_peek(dialect, schema="myschema") + sql = _compiled(executed[0], d) + self.assertIn("MYSCHEMA", sql) + + +class TestGetColumnDataDialect(unittest.TestCase): + """GeneratorCmd._get_column_data() uses NEWID/TOP on MS-SQL and RANDOM/LIMIT on PostgreSQL.""" + + def _run_get_column_data(self, dialect_instance, schema=None): + from datafaker.interactive.generators import GeneratorCmd + + engine = _make_engine(dialect_instance) + shell = MagicMock(spec=GeneratorCmd) + shell.sync_engine = engine + shell.table_name.return_value = "person" + shell._get_column_names.return_value = ["gender_concept_id"] + shell.table_metadata.return_value = _make_table(schema=schema) + + GeneratorCmd._get_column_data(shell, 5) + return engine._executed, dialect_instance + + def test_mssql_uses_newid_and_top(self) -> None: + """MS-SQL _get_column_data compiles to TOP … NEWID().""" + executed, dialect = self._run_get_column_data(mssql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("TOP", sql) + self.assertIn("NEWID()", sql) + self.assertNotIn("LIMIT", sql) + self.assertNotIn("RANDOM()", sql) + + def test_postgresql_uses_random_and_limit(self) -> None: + """PostgreSQL _get_column_data compiles to RANDOM() … LIMIT.""" + executed, dialect = self._run_get_column_data(postgresql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn(" TOP ", sql) + + def test_schema_appears_in_from(self) -> None: + """Schema-qualified table name appears in the FROM clause on both dialects.""" + for dialect in (mssql.dialect(), postgresql.dialect()): + with self.subTest(dialect=dialect.name): + executed, d = self._run_get_column_data(dialect, schema="myschema") + sql = _compiled(executed[0], d) + self.assertIn("MYSCHEMA", sql) + + +class TestPrintColumnDataDialect(unittest.TestCase): + """TableCmd.print_column_data() uses NEWID/TOP on MS-SQL and RANDOM/LIMIT on PostgreSQL.""" + + def _run_print_column_data(self, dialect_instance, schema=None): + from datafaker.interactive.table import TableCmd + + engine = _make_engine(dialect_instance) + shell = MagicMock(spec=TableCmd) + shell.sync_engine = engine + shell.table_name.return_value = "person" + shell.table_metadata.return_value = _make_table(schema=schema) + shell.columnize = MagicMock() + + TableCmd.print_column_data(shell, "gender_concept_id", 10, 0) + return engine._executed, dialect_instance + + def test_mssql_uses_newid_and_top(self) -> None: + """MS-SQL print_column_data compiles to TOP … NEWID().""" + executed, dialect = self._run_print_column_data(mssql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("TOP", sql) + self.assertIn("NEWID()", sql) + self.assertNotIn("LIMIT", sql) + self.assertNotIn("RANDOM()", sql) + + def test_postgresql_uses_random_and_limit(self) -> None: + """PostgreSQL print_column_data compiles to RANDOM() … LIMIT.""" + executed, dialect = self._run_print_column_data(postgresql.dialect()) + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], dialect) + self.assertIn("RANDOM()", sql) + self.assertIn("LIMIT", sql) + self.assertNotIn("NEWID()", sql) + self.assertNotIn(" TOP ", sql) + + def test_schema_appears_in_from(self) -> None: + """Schema-qualified table name appears in the FROM clause on both dialects.""" + for dialect in (mssql.dialect(), postgresql.dialect()): + with self.subTest(dialect=dialect.name): + executed, d = self._run_print_column_data(dialect, schema="myschema") + sql = _compiled(executed[0], d) + self.assertIn("MYSCHEMA", sql) + + +class TestCountsDialect(unittest.TestCase): + """DbCmd.do_counts() compiles a schema-qualified COUNT query.""" + + def _run_counts(self, dialect_instance, schema=None): + from datafaker.interactive.base import DbCmd + + engine = _make_engine(dialect_instance) + tbl = _make_table(schema=schema) + shell = MagicMock(spec=DbCmd) + shell.sync_engine = engine + shell._table_entries = [MagicMock()] + shell.table_index = 0 + shell.table_name.return_value = "person" + shell.get_nullable_columns.return_value = ["gender_concept_id"] + shell.table_metadata.return_value = tbl + shell.print = MagicMock() + shell.print_table = MagicMock() + + DbCmd.do_counts(shell, "") + return engine._executed, dialect_instance + + def test_counts_schema_appears_in_from(self) -> None: + """do_counts FROM clause includes the schema when one is set.""" + for dialect in (mssql.dialect(), postgresql.dialect()): + with self.subTest(dialect=dialect.name): + executed, d = self._run_counts(dialect, schema="myschema") + self.assertEqual(len(executed), 1) + sql = _compiled(executed[0], d) + self.assertIn("MYSCHEMA", sql) + + def test_counts_no_schema_omits_qualifier(self) -> None: + """do_counts FROM clause has no schema prefix when schema is None.""" + executed, d = self._run_counts(postgresql.dialect(), schema=None) + sql = _compiled(executed[0], d) + self.assertIn("FROM PERSON", sql) + self.assertNotIn("FROM MYSCHEMA", sql) diff --git a/tests/test_main.py b/tests/test_main.py index 8d80ed6..21fdb47 100644 --- a/tests/test_main.py +++ b/tests/test_main.py @@ -142,7 +142,10 @@ def test_make_tables_errors_if_file_exists( @patch.dict(os.environ, {"SRC_SCHEMA": "myschema"}, clear=True) def test_make_tables_errors_if_src_dsn_missing(self) -> None: """Test the make-tables sub-command refuses to work if SRC_DSN is not set.""" - + self.assertFalse( + Path("tests/examples/does-not-exist.yaml").exists(), + "Precondition failed: tests/examples/does-not-exist.yaml must not exist", + ) self.assertRaises( SettingsError, runner.invoke, diff --git a/tests/test_make.py b/tests/test_make.py index d8f99a7..c01c15f 100644 --- a/tests/test_make.py +++ b/tests/test_make.py @@ -2,20 +2,77 @@ import asyncio import os import tempfile +import unittest from pathlib import Path from typing import Any from unittest.mock import MagicMock, patch import pandas as pd import yaml -from sqlalchemy import BigInteger, Column, String, select +from sqlalchemy import BigInteger, Column, ForeignKey, Integer, MetaData, String, Table, select from sqlalchemy.dialects.mysql.types import INTEGER from sqlalchemy.dialects.postgresql import UUID -from datafaker.make import _get_provider_for_column, make_src_stats +from datafaker.make import _get_default_generator, _get_provider_for_column, make_src_stats from tests.utils import DatafakerTestCase, GeneratesDBTestCase, RequiresDBTestCase +class TestGetDefaultGenerator(unittest.TestCase): + """Unit tests for _get_default_generator.""" + + def _make_table(self, *columns: Column) -> Table: + meta = MetaData() + return Table("t", meta, *columns) + + def test_simple_integer_pk_returns_none(self) -> None: + """Single-column INTEGER PK with no FK → DB generates it on mssql, skip in df.py.""" + table = self._make_table( + Column("id", Integer(), primary_key=True), + Column("val", String()), + ) + self.assertIsNone(_get_default_generator(table.c.id, dialect_name="mssql")) + + def test_simple_biginteger_pk_returns_none(self) -> None: + """BigInteger (BIGINT) single-column PK is also DB-generated on mssql.""" + table = self._make_table( + Column("id", BigInteger(), primary_key=True), + Column("val", String()), + ) + self.assertIsNone(_get_default_generator(table.c.id, dialect_name="mssql")) + + def test_composite_pk_not_skipped(self) -> None: + """Columns in a composite PK are not DB-generated and must have a generator.""" + table = self._make_table( + Column("a", Integer(), primary_key=True), + Column("b", Integer(), primary_key=True), + ) + self.assertIsNotNone(_get_default_generator(table.c.a)) + self.assertIsNotNone(_get_default_generator(table.c.b)) + + def test_fk_pk_not_skipped(self) -> None: + """A column that is both PK and FK gets a FK generator, not skipped.""" + meta = MetaData() + parent = Table("parent", meta, Column("id", Integer(), primary_key=True)) + child = Table( + "child", + meta, + Column("parent_id", Integer(), ForeignKey("parent.id"), primary_key=True), + ) + result = _get_default_generator(child.c.parent_id) + self.assertIsNotNone(result) + self.assertIn("column_value", result.function_call.function_name) + + def test_non_pk_integer_returns_generator(self) -> None: + """Plain INTEGER column (not a PK) gets a numeric generator.""" + table = self._make_table( + Column("id", Integer(), primary_key=True), + Column("count", Integer()), + ) + result = _get_default_generator(table.c.count) + self.assertIsNotNone(result) + self.assertIn("integer_number", result.function_call.function_name) + + class TestMakeGenerators(GeneratesDBTestCase): """Test the make_table_generators function.""" @@ -158,7 +215,7 @@ def check_make_stats_output(self, src_stats: dict) -> None: count_names, [ {"num": 1, "name": "Miranda Rando-Generata"}, - {"num": 997, "name": "Randy Random"}, + {"num": 997, "name": "Someone Random"}, {"num": 1, "name": "Testfried Testermann"}, {"num": 1, "name": "Veronica Fyre"}, ], diff --git a/tests/test_providers.py b/tests/test_providers.py index 68e591e..3c0007e 100644 --- a/tests/test_providers.py +++ b/tests/test_providers.py @@ -1,6 +1,7 @@ """Tests for the providers module.""" import datetime as dt from typing import Any +from unittest.mock import MagicMock, patch from sqlalchemy import Column, Integer, MetaData, Text, insert from sqlalchemy.ext.declarative import declarative_base @@ -67,6 +68,34 @@ def test_column_value_missing(self) -> None: self.assertIsNone(generated_value) +class ColumnValueRandomFunctionTestCase(DatafakerTestCase): + """column_value uses the correct random function for each dialect.""" + + def _make_connection(self, dialect_name: str) -> MagicMock: + conn = MagicMock() + conn.dialect.name = dialect_name + conn.execute.return_value.first.return_value = None + return conn + + def _get_order_by_sql(self, dialect_name: str) -> str: + conn = self._make_connection(dialect_name) + providers.ColumnValueProvider.column_value(conn, Person, "sex") + query = conn.execute.call_args[0][0] + from sqlalchemy.dialects import mssql, postgresql + dialect = mssql.dialect() if dialect_name == "mssql" else postgresql.dialect() + return str(query.compile(dialect=dialect)) + + def test_mssql_uses_newid(self) -> None: + sql = self._get_order_by_sql("mssql") + self.assertIn("newid()", sql.lower()) + self.assertNotIn("random()", sql.lower()) + + def test_postgresql_uses_random(self) -> None: + sql = self._get_order_by_sql("postgresql") + self.assertIn("random()", sql.lower()) + self.assertNotIn("newid()", sql.lower()) + + class TimedeltaProvider(DatafakerTestCase): """Tests for TimedeltaProvider""" diff --git a/tests/test_serialize_metadata_mssql.py b/tests/test_serialize_metadata_mssql.py new file mode 100644 index 0000000..69e3268 --- /dev/null +++ b/tests/test_serialize_metadata_mssql.py @@ -0,0 +1,303 @@ +"""Tests for MS-SQL type support in datafaker.serialize_metadata.""" +import unittest + +from sqlalchemy.dialects import mssql, postgresql +from sqlalchemy.sql import sqltypes + +from datafaker.serialize_metadata import _unqualify_fk_target, dict_to_metadata, type_parser + + +def parse(type_str: str): + """Shorthand: parse a type string and return the resulting SQLAlchemy type.""" + return type_parser.parse(type_str) + + +class TestMSSQLTypeParser(unittest.TestCase): + """New MS-SQL-specific type strings are parsed correctly.""" + + def test_uniqueidentifier(self) -> None: + result = parse("UNIQUEIDENTIFIER") + self.assertIs(result, mssql.UNIQUEIDENTIFIER) + + def test_datetimeoffset_bare(self) -> None: + result = parse("DATETIMEOFFSET") + self.assertIsInstance(result, mssql.DATETIMEOFFSET) + + def test_datetimeoffset_with_precision(self) -> None: + result = parse("DATETIMEOFFSET(7)") + self.assertIsInstance(result, mssql.DATETIMEOFFSET) + self.assertEqual(result.precision, 7) + + def test_datetime2_bare(self) -> None: + result = parse("DATETIME2") + self.assertIsInstance(result, mssql.DATETIME2) + + def test_datetime2_with_precision(self) -> None: + result = parse("DATETIME2(3)") + self.assertIsInstance(result, mssql.DATETIME2) + self.assertEqual(result.precision, 3) + + def test_varbinary_bare(self) -> None: + result = parse("VARBINARY") + self.assertIsInstance(result, mssql.VARBINARY) + + def test_varbinary_with_length(self) -> None: + result = parse("VARBINARY(8000)") + self.assertIsInstance(result, mssql.VARBINARY) + self.assertEqual(result.length, 8000) + + def test_varbinary_max_lowercase(self) -> None: + result = parse("VARBINARY(max)") + self.assertIsInstance(result, mssql.VARBINARY) + self.assertIsNone(result.length) + + def test_varbinary_max_uppercase(self) -> None: + result = parse("VARBINARY(MAX)") + self.assertIsInstance(result, mssql.VARBINARY) + self.assertIsNone(result.length) + + def test_binary_bare(self) -> None: + result = parse("BINARY") + self.assertIsInstance(result, mssql.BINARY) + + def test_binary_with_length(self) -> None: + result = parse("BINARY(16)") + self.assertIsInstance(result, mssql.BINARY) + self.assertEqual(result.length, 16) + + def test_money(self) -> None: + self.assertIs(parse("MONEY"), mssql.MONEY) + + def test_smallmoney(self) -> None: + self.assertIs(parse("SMALLMONEY"), mssql.SMALLMONEY) + + def test_image(self) -> None: + self.assertIs(parse("IMAGE"), mssql.IMAGE) + + def test_tinyint(self) -> None: + self.assertIs(parse("TINYINT"), mssql.TINYINT) + + def test_smalldatetime(self) -> None: + self.assertIs(parse("SMALLDATETIME"), mssql.SMALLDATETIME) + + def test_ntext(self) -> None: + self.assertIs(parse("NTEXT"), mssql.NTEXT) + + def test_sql_variant(self) -> None: + self.assertIs(parse("SQL_VARIANT"), mssql.SQL_VARIANT) + + def test_rowversion(self) -> None: + self.assertIs(parse("ROWVERSION"), mssql.ROWVERSION) + + +class TestPostgreSQLTypeDegradation(unittest.TestCase): + """PostgreSQL-specific type strings degrade to cross-dialect equivalents.""" + + def test_tsvector_maps_to_text(self) -> None: + result = parse("TSVECTOR") + self.assertIs(result, sqltypes.Text) + + def test_bytea_maps_to_largebinary(self) -> None: + result = parse("BYTEA") + self.assertIs(result, sqltypes.LargeBinary) + + def test_cidr_maps_to_string_43(self) -> None: + result = parse("CIDR") + self.assertIsInstance(result, sqltypes.String) + self.assertEqual(result.length, 43) + + def test_serial_maps_to_integer(self) -> None: + self.assertIs(parse("SERIAL"), sqltypes.INTEGER) + + def test_bigserial_maps_to_bigint(self) -> None: + self.assertIs(parse("BIGSERIAL"), sqltypes.BIGINT) + + def test_smallserial_maps_to_smallint(self) -> None: + self.assertIs(parse("SMALLSERIAL"), sqltypes.SMALLINT) + + +class TestExistingPostgreSQLTypesRoundTrip(unittest.TestCase): + """Pre-existing PostgreSQL type strings still parse correctly (regression tests).""" + + def test_integer(self) -> None: + self.assertIs(parse("INTEGER"), sqltypes.INTEGER) + + def test_bigint(self) -> None: + self.assertIs(parse("BIGINT"), sqltypes.BIGINT) + + def test_smallint(self) -> None: + self.assertIs(parse("SMALLINT"), sqltypes.SMALLINT) + + def test_boolean(self) -> None: + self.assertIs(parse("BOOLEAN"), sqltypes.BOOLEAN) + + def test_float(self) -> None: + self.assertIsInstance(parse("FLOAT"), sqltypes.FLOAT) + + def test_double_precision(self) -> None: + self.assertIs(parse("DOUBLE PRECISION"), sqltypes.DOUBLE_PRECISION) + + def test_numeric_bare(self) -> None: + result = parse("NUMERIC") + self.assertIsInstance(result, sqltypes.NUMERIC) + + def test_numeric_with_args(self) -> None: + result = parse("NUMERIC(10, 2)") + self.assertIsInstance(result, sqltypes.NUMERIC) + self.assertEqual(result.precision, 10) + self.assertEqual(result.scale, 2) + + def test_varchar(self) -> None: + result = parse("VARCHAR(255)") + self.assertIsInstance(result, sqltypes.VARCHAR) + self.assertEqual(result.length, 255) + + def test_varchar_with_mssql_collation(self) -> None: + result = parse("VARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AS") + self.assertIsInstance(result, sqltypes.VARCHAR) + self.assertEqual(result.length, 50) + self.assertEqual(result.collation, "SQL_Latin1_General_CP1_CI_AS") + + def test_nvarchar_with_mssql_collation(self) -> None: + result = parse("NVARCHAR(100) COLLATE Latin1_General_CI_AS") + self.assertIsInstance(result, sqltypes.NVARCHAR) + self.assertEqual(result.length, 100) + self.assertEqual(result.collation, "Latin1_General_CI_AS") + + def test_char_with_mssql_collation(self) -> None: + result = parse("CHAR(10) COLLATE SQL_Latin1_General_CP1_CI_AS") + self.assertIsInstance(result, sqltypes.CHAR) + self.assertEqual(result.collation, "SQL_Latin1_General_CP1_CI_AS") + + def test_varchar_with_quoted_collation_still_works(self) -> None: + result = parse('VARCHAR(255) COLLATE "fr"') + self.assertIsInstance(result, sqltypes.VARCHAR) + self.assertEqual(result.collation, "fr") + + def test_nvarchar(self) -> None: + result = parse("NVARCHAR(100)") + self.assertIsInstance(result, sqltypes.NVARCHAR) + self.assertEqual(result.length, 100) + + def test_text(self) -> None: + result = parse("TEXT") + self.assertIsInstance(result, sqltypes.TEXT) + + def test_uuid(self) -> None: + self.assertIs(parse("UUID"), sqltypes.UUID) + + def test_date(self) -> None: + self.assertIs(parse("DATE"), sqltypes.DATE) + + def test_datetime(self) -> None: + self.assertIs(parse("DATETIME"), sqltypes.DATETIME) + + def test_timestamp_bare(self) -> None: + self.assertIs(parse("TIMESTAMP"), sqltypes.TIMESTAMP) + + def test_timestamp_with_timezone(self) -> None: + result = parse("TIMESTAMP WITH TIME ZONE") + self.assertIsInstance(result, postgresql.types.TIMESTAMP) + self.assertTrue(result.timezone) + + def test_timestamp_with_precision_and_timezone(self) -> None: + result = parse("TIMESTAMP(6) WITH TIME ZONE") + self.assertIsInstance(result, postgresql.types.TIMESTAMP) + self.assertEqual(result.precision, 6) + self.assertTrue(result.timezone) + + def test_timestamp_without_timezone(self) -> None: + # WITHOUT TIME ZONE means timezone=False; the parser returns the plain + # sqltypes.TIMESTAMP class (not a pg-specific instance) in this case. + result = parse("TIMESTAMP WITHOUT TIME ZONE") + self.assertIs(result, sqltypes.TIMESTAMP) + + def test_time_bare(self) -> None: + self.assertIs(parse("TIME"), sqltypes.TIME) + + def test_time_with_timezone(self) -> None: + result = parse("TIME WITH TIME ZONE") + self.assertIsInstance(result, postgresql.types.TIME) + self.assertTrue(result.timezone) + + def test_bit_bare(self) -> None: + result = parse("BIT") + self.assertIsInstance(result, postgresql.BIT) + + def test_bit_with_length(self) -> None: + result = parse("BIT(8)") + self.assertIsInstance(result, postgresql.BIT) + self.assertEqual(result.length, 8) + + def test_real_bare(self) -> None: + result = parse("REAL") + self.assertIsInstance(result, sqltypes.REAL) + + def test_blob(self) -> None: + self.assertIs(parse("BLOB"), sqltypes.BLOB) + + def test_clob(self) -> None: + self.assertIs(parse("CLOB"), sqltypes.CLOB) + + +class TestArrayType(unittest.TestCase): + """Array types (PostgreSQL-specific) still parse correctly.""" + + def test_integer_array(self) -> None: + result = parse("INTEGER[]") + self.assertIsInstance(result, postgresql.ARRAY) + self.assertEqual(result.dimensions, 1) + + def test_text_array(self) -> None: + result = parse("TEXT[]") + self.assertIsInstance(result, postgresql.ARRAY) + + def test_multidimensional_array(self) -> None: + result = parse("INTEGER[][]") + self.assertIsInstance(result, postgresql.ARRAY) + self.assertEqual(result.dimensions, 2) + + +class TestUnqualifyFkTarget(unittest.TestCase): + """Schema prefix is stripped from 3-part FK targets.""" + + def test_three_part_target_drops_schema(self) -> None: + self.assertEqual(_unqualify_fk_target("mimic100.concept.concept_id"), "concept.concept_id") + + def test_two_part_target_unchanged(self) -> None: + self.assertEqual(_unqualify_fk_target("concept.concept_id"), "concept.concept_id") + + def test_single_part_unchanged(self) -> None: + self.assertEqual(_unqualify_fk_target("concept_id"), "concept_id") + + +class TestSchemaQualifiedFKResolution(unittest.TestCase): + """Schema-qualified FK targets resolve correctly when building MetaData.""" + + def test_schema_qualified_fk_resolves_in_metadata(self) -> None: + orm_dict = { + "tables": { + "concept": { + "columns": { + "concept_id": {"type": "BIGINT", "primary": True, "nullable": False}, + } + }, + "person": { + "columns": { + "person_id": {"type": "BIGINT", "primary": True, "nullable": False}, + "gender_concept_id": { + "type": "BIGINT", + "primary": False, + "nullable": False, + "foreign_keys": ["myschema.concept.concept_id"], + }, + } + }, + } + } + meta = dict_to_metadata(orm_dict) + person = meta.tables["person"] + fks = list(person.c.gender_concept_id.foreign_keys) + self.assertEqual(len(fks), 1) + # FK target should resolve to the concept table without raising NoReferencedTableError + self.assertEqual(fks[0].column.table.name, "concept") diff --git a/tests/test_utils_mssql.py b/tests/test_utils_mssql.py new file mode 100644 index 0000000..1984a44 --- /dev/null +++ b/tests/test_utils_mssql.py @@ -0,0 +1,239 @@ +"""Tests for MS-SQL driver support helpers in datafaker.utils.""" +import sys +import unittest +from unittest.mock import MagicMock, call, patch +from datafaker.db_utils import create_db_engine, get_metadata, get_sync_engine + +class TestMakeAsyncDsn(unittest.TestCase): + """Tests for make_async_dsn.""" + + def _call(self, dsn: str) -> str: + from datafaker.utils import make_async_dsn + + return make_async_dsn(dsn) + + def test_postgresql_bare_dialect(self) -> None: + """postgresql:// is rewritten to use asyncpg.""" + result = self._call("postgresql://user:pass@host:5432/db") + self.assertTrue( + result.startswith("postgresql+asyncpg://"), + f"Expected asyncpg driver, got: {result}", + ) + + def test_postgresql_with_existing_driver(self) -> None: + """postgresql+psycopg2:// is also rewritten to asyncpg.""" + result = self._call("postgresql+psycopg2://user:pass@host:5432/db") + self.assertTrue(result.startswith("postgresql+asyncpg://")) + + def test_postgresql_preserves_credentials_and_path(self) -> None: + """Host, port and database name are preserved (password is masked in repr).""" + from sqlalchemy.engine import make_url + + result_url = make_url(self._call("postgresql://alice:secret@dbhost:5433/mydb")) + self.assertEqual(result_url.host, "dbhost") + self.assertEqual(result_url.port, 5433) + self.assertEqual(result_url.database, "mydb") + self.assertEqual(result_url.username, "alice") + + def test_mssql_bare_dialect(self) -> None: + """mssql:// is rewritten to use aioodbc.""" + result = self._call("mssql://user:pass@host:1433/db") + self.assertTrue( + result.startswith("mssql+aioodbc://"), + f"Expected aioodbc driver, got: {result}", + ) + + def test_mssql_with_existing_driver(self) -> None: + """mssql+pyodbc:// is rewritten to aioodbc.""" + result = self._call("mssql+pyodbc://user:pass@host:1433/db") + self.assertTrue(result.startswith("mssql+aioodbc://")) + + def test_unknown_dialect_raises(self) -> None: + """An unknown dialect raises ValueError rather than silently producing a bad DSN.""" + with self.assertRaises(ValueError) as ctx: + self._call("oracle://user:pass@host:1521/db") + self.assertIn("oracle", str(ctx.exception)) + + def test_duckdb_raises(self) -> None: + """DuckDB DSNs are not async-capable and should raise.""" + with self.assertRaises(ValueError): + self._call("duckdb:///path/to/file.db") + + +class TestIsUndefinedObjectError(unittest.TestCase): + """Tests for _is_undefined_object_error.""" + + def _call(self, exc: Exception) -> bool: + from datafaker.utils import _is_undefined_object_error + + return _is_undefined_object_error(exc) + + def test_pgcode_42704_returns_true(self) -> None: + """Any exception with pgcode 42704 is treated as UndefinedObject.""" + exc = Exception("undefined object") + exc.pgcode = "42704" # type: ignore[attr-defined] + self.assertTrue(self._call(exc)) + + def test_other_pgcode_returns_false(self) -> None: + """Exceptions with a different pgcode are not matched.""" + exc = Exception("some other error") + exc.pgcode = "23505" # type: ignore[attr-defined] + self.assertFalse(self._call(exc)) + + def test_no_pgcode_returns_false(self) -> None: + """Exceptions without a pgcode attribute are not matched.""" + self.assertFalse(self._call(ValueError("no pgcode here"))) + + def test_psycopg2_undefined_object_returns_true(self) -> None: + """A real psycopg2 UndefinedObject exception is matched (if psycopg2 installed).""" + try: + import psycopg2.errors # type: ignore[import] + except ImportError: + self.skipTest("psycopg2 not installed") + + exc = psycopg2.errors.UndefinedObject("constraint does not exist") + self.assertTrue(self._call(exc)) + + def test_works_without_psycopg2(self) -> None: + """_is_undefined_object_error falls back to pgcode check when psycopg2 is absent.""" + with patch.dict(sys.modules, {"psycopg2": None, "psycopg2.errors": None}): + exc = Exception("constraint does not exist") + exc.pgcode = "42704" # type: ignore[attr-defined] + from datafaker.utils import _is_undefined_object_error + + self.assertTrue(_is_undefined_object_error(exc)) + + def test_import_does_not_require_psycopg2(self) -> None: + """datafaker.utils can be imported even when psycopg2 is unavailable.""" + with patch.dict(sys.modules, {"psycopg2": None, "psycopg2.errors": None}): + import importlib + + import datafaker.utils as utils_mod + + importlib.reload(utils_mod) + + def test_pyodbc_style_error_without_pgcode_returns_false(self) -> None: + """A pyodbc-style error has SQLSTATE in args[0] but no pgcode attribute. + + pyodbc does not set pgcode, so the current implementation cannot + distinguish a 'constraint does not exist' pyodbc error from any other + exception without pgcode. This test documents that known limitation. + """ + exc = Exception("constraint does not exist") + # pyodbc puts SQLSTATE in args[0]; MS-SQL error 3728 maps to SQLSTATE 42000 + exc.args = ("42000", "[42000] [SQL Server] ... is not a constraint. (3728)") + self.assertFalse(self._call(exc)) + + def test_pgcode_none_returns_false(self) -> None: + """pgcode=None is not treated as a match.""" + exc = Exception("undefined object") + exc.pgcode = None # type: ignore[attr-defined] + self.assertFalse(self._call(exc)) + + def test_sqlalchemy_wrapper_not_matched_only_orig_is(self) -> None: + """The helper expects the unwrapped DBAPI error (e.orig), not the SQLAlchemy wrapper. + + The call site in utils.py passes e.orig, not e, so the SQLAlchemy + ProgrammingError itself should not match even when e.orig would. + """ + from sqlalchemy.exc import ProgrammingError + + orig = Exception("underlying DBAPI error") + orig.pgcode = "42704" # type: ignore[attr-defined] + sa_exc = ProgrammingError("statement", {}, orig) + + # The SQLAlchemy exception itself has no pgcode. + self.assertFalse(self._call(sa_exc)) + # Passing e.orig directly does match. + self.assertTrue(self._call(sa_exc.orig)) + + +class TestSchemaTranslateMap(unittest.TestCase): + """Tests for the cross-dialect schema routing in create_db_engine.""" + + def _make_engine(self, dsn: str, schema_name: str | None = None): + return get_sync_engine(create_db_engine(dsn, schema_name=schema_name)) + + def test_no_schema_no_translate_map(self) -> None: + """Without a schema_name, schema_translate_map is absent from execution options.""" + engine = self._make_engine("duckdb:///:memory:") + opts = engine.get_execution_options() + self.assertNotIn("schema_translate_map", opts) + + def test_schema_sets_translate_map(self) -> None: + """When schema_name is given, MSSQL uses schema_translate_map (not search_path).""" + try: + engine = self._make_engine( + "mssql+pyodbc://user:pass@host/db", schema_name="myschema" + ) + except Exception: + self.skipTest("mssql+pyodbc driver not available in this environment") + opts = engine.get_execution_options() + self.assertIn("schema_translate_map", opts) + self.assertEqual(opts["schema_translate_map"], {None: "myschema"}) + + def test_duckdb_schema_sets_search_path(self) -> None: + """For non-MSSQL dialects, schema_name is applied via search_path session setting.""" + + with patch("datafaker.db_utils.set_db_settings") as mock_set: + engine = get_sync_engine( + create_db_engine("duckdb:///:memory:", schema_name="myschema") + ) + # Force a connection so the connect-event handler fires + with engine.connect() as conn: + conn.execute(__import__("sqlalchemy").text("SELECT 1")) + + calls = mock_set.call_args_list + self.assertTrue(calls, "set_db_settings should have been called at least once") + settings_passed = calls[0].args[1] if len(calls[0].args) > 1 else calls[0].kwargs.get("settings", {}) + self.assertIn("search_path", settings_passed) + self.assertEqual(settings_passed["search_path"], "myschema") + + def test_mssql_dsn_schema_sets_translate_map(self) -> None: + """schema_translate_map is set even for an MS-SQL DSN (engine creation, no connect).""" + + # create_engine with mssql+pyodbc does not connect at construction time, + # so this is safe to run even without an ODBC driver installed. + try: + engine = get_sync_engine( + create_db_engine("mssql+pyodbc://user:pass@host/db", schema_name="dbo") + ) + except Exception: + self.skipTest("mssql+pyodbc driver not available in this environment") + + opts = engine.get_execution_options() + self.assertEqual(opts.get("schema_translate_map"), {None: "dbo"}) + + +class TestGetMetadataSchema(unittest.TestCase): + """Tests for the schema_name parameter on get_metadata.""" + + def test_reflect_called_with_schema(self) -> None: + """get_metadata passes schema_name to MetaData.reflect.""" + + mock_engine = MagicMock() + mock_engine.connect.return_value.__enter__ = MagicMock(return_value=MagicMock()) + mock_engine.connect.return_value.__exit__ = MagicMock(return_value=False) + + with patch("datafaker.db_utils.MetaData") as MockMetaData: + mock_md = MagicMock() + MockMetaData.return_value = mock_md + mock_md.reflect.return_value = None + + get_metadata(mock_engine, schema_name="myschema") + + mock_md.reflect.assert_called_once_with(mock_engine, schema="myschema") + + def test_reflect_called_without_schema_when_none(self) -> None: + """get_metadata passes schema=None to reflect when no schema_name is given.""" + + mock_engine = MagicMock() + + with patch("datafaker.db_utils.MetaData") as MockMetaData: + mock_md = MagicMock() + MockMetaData.return_value = mock_md + mock_md.reflect.return_value = None + + get_metadata(mock_engine) + + mock_md.reflect.assert_called_once_with(mock_engine, schema=None) diff --git a/tests/utils.py b/tests/utils.py index 427ba67..d937ded 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -246,6 +246,122 @@ def create_empty(self, name: str) -> str: return self.get_dsn(name) +class TestMSSQL(TestDatabaseBase): + """MS-SQL Server test database. + + Requires the ``MSSQL_TEST_DSN`` environment variable to be set to a + ``mssql+pyodbc://`` connection string pointing at a running SQL Server + instance (e.g. the docker-compose ``mssql`` service). + + Tests that use this class are skipped automatically when the variable is + absent or when a connection cannot be established. + """ + + _ENV_VAR = "MSSQL_TEST_DSN" + _base_dsn: str = "" + + @classmethod + def skip(cls) -> str | None: + """Return a skip message if SQL Server is not reachable.""" + dsn = os.environ.get(cls._ENV_VAR) + if not dsn: + return f"set {cls._ENV_VAR} to enable MS-SQL tests" + try: + import pyodbc as _pyodbc # noqa: F401 + except ImportError: + return "pyodbc not installed; run: poetry install --extras mssql" + try: + from sqlalchemy import create_engine as _ce + + with _ce(dsn).connect(): + pass + except Exception as exc: # pylint: disable=broad-except + return f"cannot connect to MS-SQL ({exc})" + return None + + @classmethod + def setup(cls) -> None: + """Store the base DSN for use by all instances.""" + cls._base_dsn = os.environ[cls._ENV_VAR] + + def open(self) -> None: + """Nothing to open — SQL Server runs externally.""" + + def close(self) -> None: + """Nothing to close — SQL Server runs externally.""" + + def get_dsn(self, database_name: str | None) -> str: + """Return a DSN pointing at ``database_name`` within the SQL Server instance.""" + if not database_name: + return self._base_dsn + from sqlalchemy.engine import make_url + + url = make_url(self._base_dsn) + return url.set(database=database_name).render_as_string(hide_password=False) + + def create_empty(self, name: str) -> str: + """Drop (if exists) and create a fresh SQL Server database named ``name``.""" + import pyodbc # pylint: disable=import-outside-toplevel + from sqlalchemy.engine import make_url # pylint: disable=import-outside-toplevel + + url = make_url(self._base_dsn) + conn_str = ( + f"DRIVER={{ODBC Driver 18 for SQL Server}};" + f"SERVER={url.host},{url.port or 1433};" + f"DATABASE=master;" + f"UID={url.username};PWD={url.password};" + "TrustServerCertificate=yes;" + ) + with pyodbc.connect(conn_str, autocommit=True) as conn: + conn.execute( + f"IF EXISTS (SELECT name FROM sys.databases WHERE name = N'{name}') " + f"ALTER DATABASE [{name}] SET SINGLE_USER WITH ROLLBACK IMMEDIATE" + ) + conn.execute( + f"IF EXISTS (SELECT name FROM sys.databases WHERE name = N'{name}') " + f"DROP DATABASE [{name}]" + ) + conn.execute(f"CREATE DATABASE [{name}]") + + # SQL Server can take a moment to bring the new database fully online. + # Poll until a connection succeeds rather than returning a DSN that + # immediately produces TCP resets. + dsn = self.get_dsn(name) + db_conn_str = conn_str.replace("DATABASE=master;", f"DATABASE={name};") + deadline = time.monotonic() + 30 + while True: + try: + with pyodbc.connect(db_conn_str, autocommit=True, timeout=5) as probe: + probe.execute("SELECT 1") + break + except pyodbc.Error: + if time.monotonic() > deadline: + raise + time.sleep(0.5) + return dsn + + def run_sql(self, sql_file: Path) -> None: + """Execute a T-SQL file via pyodbc, splitting batches on GO.""" + import pyodbc # pylint: disable=import-outside-toplevel + + from sqlalchemy.engine import make_url # pylint: disable=import-outside-toplevel + + url = make_url(self._base_dsn) + conn_str = ( + f"DRIVER={{ODBC Driver 18 for SQL Server}};" + f"SERVER={url.host},{url.port or 1433};" + f"DATABASE={url.database or 'master'};" + f"UID={url.username};PWD={url.password};" + "TrustServerCertificate=yes;" + ) + sql = sql_file.read_text(encoding="utf-8") + with pyodbc.connect(conn_str, autocommit=True) as conn: + for batch in re.split(r"^\s*GO\s*$", sql, flags=re.MULTILINE): + batch = batch.strip() + if batch: + conn.execute(batch) + + class DatafakerTestCase(TestCase): """Parent class for all TestCases in datafaker.""" @@ -446,6 +562,10 @@ def make_destination_database(self, name: str) -> None: def tearDown(self) -> None: assert self.database is not None + if hasattr(self, "sync_engine"): + self.sync_engine.dispose() + if self.dst_engine is not None: + self.dst_engine.dispose() self.database.close() if self.dst_database is not None: self.dst_database.close()