From b0d9621a6bf609e41920eae92aa9b9687c3de582 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 17 Sep 2024 15:46:16 +0200 Subject: [PATCH 01/25] Simplified configuration files --- metasyn/config.py | 41 ++++++++++++++++++----------------------- metasyn/metaframe.py | 44 +++++++++++++++++++++++++++++++++++++++++++- metasyn/provider.py | 3 +-- metasyn/var.py | 7 ++++++- metasyn/varspec.py | 14 +++++++++++++- pyproject.toml | 2 +- 6 files changed, 82 insertions(+), 29 deletions(-) diff --git a/metasyn/config.py b/metasyn/config.py index 30d86cb7..abb51194 100644 --- a/metasyn/config.py +++ b/metasyn/config.py @@ -11,7 +11,7 @@ from metasyn.privacy import BasePrivacy, BasicPrivacy, get_privacy from metasyn.provider import DistributionProviderList -from metasyn.varspec import VarSpec +from metasyn.varspec import VarDefaults, VarSpec, DistributionSpec class MetaConfig(): @@ -44,12 +44,12 @@ def __init__( self, var_specs: Union[list[dict], list[VarSpec]], dist_providers: Union[DistributionProviderList, list[str], str, None], - privacy: Optional[Union[BasePrivacy, dict]], + defaults: Optional[dict] = None, n_rows: Optional[int] = None): self.var_specs = [self._parse_var_spec(v) for v in var_specs] self.dist_providers = dist_providers # type: ignore - self.privacy = privacy # type: ignore self.n_rows = n_rows + self.defaults = VarDefaults(**defaults) @staticmethod def _parse_var_spec(var_spec): @@ -57,20 +57,6 @@ def _parse_var_spec(var_spec): return var_spec return VarSpec.from_dict(var_spec) - @property - def privacy(self) -> BasePrivacy: - """Return default privacy for generating the metaframe.""" - return self._privacy - - @privacy.setter - def privacy(self, privacy: Optional[Union[dict, BasePrivacy]]): - if privacy is None: - self._privacy: BasePrivacy = BasicPrivacy() - elif isinstance(privacy, dict): - self._privacy = get_privacy(**privacy) - else: - self._privacy = privacy - @property def dist_providers(self) -> DistributionProviderList: """Return the distribution provider list to be used for the metaframe.""" @@ -115,11 +101,11 @@ def from_toml(cls, config_fp: Union[str, Path]) -> MetaConfig: var_list = config_dict.pop("var", []) n_rows = config_dict.pop("n_rows", None) dist_providers = config_dict.pop("dist_providers", ["builtin"]) - privacy = config_dict.pop("privacy", {"name": "none", "parameters": {}}) + defaults = config_dict.pop("defaults", None) if len(config_dict) > 0: raise ValueError(f"Error parsing configuration file '{config_fp}'." f" Unknown keys detected: '{list(config_dict)}'") - return cls(var_list, dist_providers, privacy, n_rows=n_rows) + return cls(var_list, dist_providers, defaults, n_rows=n_rows) def to_dict(self) -> dict: """Convert the configuration to a dictionary. @@ -197,10 +183,19 @@ def __init__(self, var_spec: VarSpec, meta_config: MetaConfig): self.meta_config = meta_config def __getattribute__(self, attr): - if attr == "privacy": - if self.var_spec.privacy is None: - return self.meta_config.privacy - return self.var_spec.privacy + if attr in ["privacy", "data_free", "prop_missing", "privacy"]: + if getattr(self.var_spec, attr) is None: + return getattr(self.meta_config.defaults, attr) + return getattr(self.var_spec, attr) + if attr == "dist_spec": + if self.data_free and self.var_spec.dist_spec.implements is None: + if self.var_type not in self.meta_config.defaults.distribution: + raise ValueError(f"Please supply distribution for variable with name {self.name}" + "that is datafree or set a default for the variable type" + f"{self.var_type}") + return DistributionSpec.parse(self.meta_config.defaults.distribution[self.var_type]) + return self.var_spec.dist_spec + if attr not in ("var_spec", "meta_config") and hasattr(self.var_spec, attr): return getattr(self.var_spec, attr) return super().__getattribute__(attr) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index 5114539e..c13de0a0 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -10,10 +10,12 @@ import numpy as np import polars as pl +import tomlkit +import tomllib from tqdm import tqdm from metasyn.config import MetaConfig -from metasyn.privacy import BasePrivacy +from metasyn.privacy import BasePrivacy, get_privacy from metasyn.validation import validate_gmf_dict from metasyn.var import MetaVar from metasyn.varspec import VarSpec @@ -295,6 +297,46 @@ def from_json(cls, fp: Union[pathlib.Path, str], meta_vars = [MetaVar.from_dict(d) for d in self_dict["vars"]] return cls(meta_vars, n_rows) + def to_toml(self, fp: Optional[Union[pathlib.Path, str]], + validate: bool = True) -> None: + self_dict = _jsonify(self.to_dict()) + if validate: + validate_gmf_dict(self_dict) + + doc = tomlkit.loads(tomlkit.dumps(self_dict)) + doc["n_rows"].comment("Number of rows") + doc["n_columns"].comment("Number of columns") + for i in range(self.n_columns): + var = self.meta_vars[i] + doc["vars"][i].comment(f"Metadata for column with name {var.name}") + doc["vars"][i]["prop_missing"].comment( + f"Based on {round(self.n_rows*(1-var.prop_missing))} values") + if "privacy" in var.creation_method: + privacy = get_privacy(**var.creation_method["privacy"]) + doc["vars"][i]["creation_method"].add(tomlkit.comment(privacy.comment(var.name))) + if var.distribution.matches_name("multinoulli"): + counts = (var.distribution.probs*(1-var.prop_missing)*self.n_rows).round() + doc["vars"][i]["distribution"].add(tomlkit.comment(f"Counts: {counts.astype(int)}\n")) + + if fp is None: + print(tomlkit.dumps(doc)) + else: + with open(fp, "w", encoding="utf-8") as f: + tomlkit.dump(doc, f) + + @classmethod + def from_toml(cls, fp: Union[pathlib.Path, str], + validate: bool = True) -> MetaFrame: + with open(fp, "rb") as f: + self_dict = tomllib.load(f) + + if validate: + validate_gmf_dict(self_dict) + + n_rows = self_dict["n_rows"] + meta_vars = [MetaVar.from_dict(d) for d in self_dict["vars"]] + return cls(meta_vars, n_rows) + def synthesize(self, n: Optional[int] = None) -> pl.DataFrame: """Create a synthetic Polars dataframe. diff --git a/metasyn/provider.py b/metasyn/provider.py index a3d39411..1af39da6 100644 --- a/metasyn/provider.py +++ b/metasyn/provider.py @@ -241,7 +241,6 @@ def create(self, var_spec: Union[VarSpec, VarSpecAccess]) -> BaseDistribution: """ dist_spec = var_spec.dist_spec unique = dist_spec.unique if dist_spec.unique else False - assert dist_spec.implements is not None and var_spec.var_type is not None dist_class = self.find_distribution( dist_spec.implements, var_spec.var_type, privacy=BasicPrivacy(), unique=unique) @@ -298,7 +297,7 @@ def _find_best_fit(self, series: pl.Series, var_type: str, def find_distribution(self, dist_name: str, - var_type: str, + var_type: Optional[str], privacy: Optional[BasePrivacy] = BasicPrivacy(), unique: bool = False, version: Optional[str] = None) -> type[BaseDistribution]: diff --git a/metasyn/var.py b/metasyn/var.py index 6ae081e7..8051b37a 100644 --- a/metasyn/var.py +++ b/metasyn/var.py @@ -53,7 +53,7 @@ class MetaVar: def __init__( # noqa: PLR0913 self, name: str, - var_type: str, + var_type: Optional[str], distribution: BaseDistribution, dtype: str = "unknown", description: Optional[str] = None, @@ -61,6 +61,11 @@ def __init__( # noqa: PLR0913 creation_method: Optional[dict] = None, ): self.name = name + if var_type is None: + if not isinstance(distribution.var_type, str): + raise ValueError("Failed to infer variable type for variable {name}" + " supply var_type or a different distribution.") + var_type = distribution.var_type self.var_type = var_type self.distribution = distribution self.dtype = dtype diff --git a/metasyn/varspec.py b/metasyn/varspec.py index 68dec429..a22738bc 100644 --- a/metasyn/varspec.py +++ b/metasyn/varspec.py @@ -164,7 +164,7 @@ def __init__( privacy: Optional[BasePrivacy] = None, prop_missing: Optional[float] = None, description: Optional[str] = None, - data_free: bool = False, + data_free: Optional[bool] = None, var_type: Optional[str] = None): self.name = name @@ -198,3 +198,15 @@ def from_dict(cls, var_dict: dict) -> VarSpec: A VarSpec instance. """ return cls(**var_dict) + + +@dataclass +class VarDefaults(): + data_free: bool = False + prop_missing: Optional[float] = None + distribution: Optional[dict] = None + privacy: Optional[BasePrivacy] = None + + def __post_init__(self): + if isinstance(self.privacy, dict): + self.privacy = get_privacy(**self.privacy) diff --git a/pyproject.toml b/pyproject.toml index 76e4a6ed..c3f5c6b5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,7 +48,7 @@ GitHub = "https://github.com/sodascience/metasyn" documentation = "https://metasyn.readthedocs.io/en/latest/index.html" [project.optional-dependencies] -extra = ["xlsxwriter", "pandas"] +extra = ["xlsxwriter", "pandas", "tomlkit"] check = ["ruff", "mypy", "types-tqdm", "types-regex"] test = ["pytest", "nbval"] docs = [ From 708bb31dccb6e278a4034452bcf35c85f94611cf Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Wed, 18 Sep 2024 16:18:51 +0200 Subject: [PATCH 02/25] Improve error messages and fix dtype bugs --- metasyn/config.py | 30 ++++++++++++++++++++---------- metasyn/util.py | 2 ++ metasyn/var.py | 7 +++++-- metasyn/varspec.py | 4 ++++ 4 files changed, 31 insertions(+), 12 deletions(-) diff --git a/metasyn/config.py b/metasyn/config.py index abb51194..d13b3d90 100644 --- a/metasyn/config.py +++ b/metasyn/config.py @@ -1,6 +1,7 @@ """Module defining configuration classes for creating MetaFrames.""" from __future__ import annotations +import warnings from pathlib import Path from typing import Iterable, Optional, Union @@ -9,9 +10,8 @@ except ImportError: import tomli as tomllib # type: ignore # noqa -from metasyn.privacy import BasePrivacy, BasicPrivacy, get_privacy from metasyn.provider import DistributionProviderList -from metasyn.varspec import VarDefaults, VarSpec, DistributionSpec +from metasyn.varspec import DistributionSpec, VarDefaults, VarSpec class MetaConfig(): @@ -90,18 +90,27 @@ def from_toml(cls, config_fp: Union[str, Path]) -> MetaConfig: raise FileNotFoundError(f"It appears '{config_fp}' is not a valid filepath." f" Please provide a path to a .toml file to load a MetaConfig" f" from.") from fnf_error - except ValueError as value_error: - if Path(config_fp).suffix == ".toml": + except tomllib.TOMLDecodeError as value_error: + if Path(config_fp).suffix != ".toml": raise ValueError(f"It appears '{Path(config_fp).name}' is a" f" '{Path(config_fp).suffix}' file." f" To load a MetaConfig, " - f"provide it as a .toml file.") from value_error - raise ValueError(f"An error occured while parsing the configuration file \n" - f"('{Path(config_fp).name}').") from value_error + f"provide the configuration as a .toml file.") from value_error + raise value_error var_list = config_dict.pop("var", []) n_rows = config_dict.pop("n_rows", None) dist_providers = config_dict.pop("dist_providers", ["builtin"]) defaults = config_dict.pop("defaults", None) + privacy = config_dict.pop("privacy", None) + config_version = config_dict.pop("config_version", "1.0") + if config_version not in ["1.0", "1.1"]: + warnings.warn(f"Trying to read configuration file with version {config_version}, " + "this version of metasyn only supports 1.0 and 1.1.") + if privacy is not None: + if defaults is not None: + raise ValueError("Error parsing configuration file: cannot have both [privacy]" + " and [defaults] tables.") + defaults = {"privacy": privacy} if len(config_dict) > 0: raise ValueError(f"Error parsing configuration file '{config_fp}'." f" Unknown keys detected: '{list(config_dict)}'") @@ -190,9 +199,10 @@ def __getattribute__(self, attr): if attr == "dist_spec": if self.data_free and self.var_spec.dist_spec.implements is None: if self.var_type not in self.meta_config.defaults.distribution: - raise ValueError(f"Please supply distribution for variable with name {self.name}" - "that is datafree or set a default for the variable type" - f"{self.var_type}") + raise ValueError( + f"Variable with name '{self.name}' is declared datafree and a distribution " + f"cannot be inferred. You can set the distribution for '{self.name}' or set" + f" a default distribution for variable type '{self.var_type}'.") return DistributionSpec.parse(self.meta_config.defaults.distribution[self.var_type]) return self.var_spec.dist_spec diff --git a/metasyn/util.py b/metasyn/util.py index 187e3c33..983179f1 100644 --- a/metasyn/util.py +++ b/metasyn/util.py @@ -12,6 +12,8 @@ from importlib.resources import files # type: ignore +ALL_VAR_TYPES = ["discrete", "continuous", "time", "date", "datetime", "string", "categorical"] + def get_registry() -> dict: """Get the registry dictionary from the package. diff --git a/metasyn/var.py b/metasyn/var.py index 8051b37a..a96d9d8a 100644 --- a/metasyn/var.py +++ b/metasyn/var.py @@ -63,7 +63,7 @@ def __init__( # noqa: PLR0913 self.name = name if var_type is None: if not isinstance(distribution.var_type, str): - raise ValueError("Failed to infer variable type for variable {name}" + raise ValueError("Failed to infer variable type for variable '{name}'" " supply var_type or a different distribution.") var_type = distribution.var_type self.var_type = var_type @@ -80,7 +80,10 @@ def __init__( # noqa: PLR0913 "outside range [0, 1]" ) if self.dtype == "unknown": - self.dtype = str(pl.Series([self.draw()]).dtype) + if self.var_type == "categorical": + self.dtype = "Categorical" + else: + self.dtype = str(pl.Series([self.distribution.draw()]).dtype) @staticmethod def get_var_type(series: pl.Series) -> str: diff --git a/metasyn/varspec.py b/metasyn/varspec.py index a22738bc..43b8fceb 100644 --- a/metasyn/varspec.py +++ b/metasyn/varspec.py @@ -7,6 +7,7 @@ from metasyn.distribution.base import BaseDistribution from metasyn.privacy import BasePrivacy, BasicPrivacy, get_privacy +from metasyn.util import ALL_VAR_TYPES @dataclass @@ -183,6 +184,9 @@ def __post_init__(self): if self.data_free and not self.dist_spec.fully_specified: raise ValueError("Error creating variable specification: data free variable should have" f" 'implements' and 'parameters'. {self}") + if self.var_type is not None and self.var_type not in ALL_VAR_TYPES: + raise ValueError(f"Cannot create variable '{self.name}': unknown variable type " + f"'{self.var_type}'. Choose from {ALL_VAR_TYPES}.") @classmethod def from_dict(cls, var_dict: dict) -> VarSpec: From 50e5a9d105de7c9e709b283e47ad644ed9512294 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 19 Sep 2024 12:04:19 +0200 Subject: [PATCH 03/25] Fix tests --- metasyn/config.py | 16 ++++++++++------ metasyn/metaframe.py | 9 +++++---- metasyn/privacy.py | 13 +++++++++++++ metasyn/provider.py | 2 ++ metasyn/varspec.py | 3 +++ 5 files changed, 33 insertions(+), 10 deletions(-) diff --git a/metasyn/config.py b/metasyn/config.py index d13b3d90..59149d15 100644 --- a/metasyn/config.py +++ b/metasyn/config.py @@ -45,11 +45,14 @@ def __init__( var_specs: Union[list[dict], list[VarSpec]], dist_providers: Union[DistributionProviderList, list[str], str, None], defaults: Optional[dict] = None, - n_rows: Optional[int] = None): + n_rows: Optional[int] = None, + config_version: str = "1.1"): self.var_specs = [self._parse_var_spec(v) for v in var_specs] self.dist_providers = dist_providers # type: ignore self.n_rows = n_rows + defaults = {} if defaults is None else defaults self.defaults = VarDefaults(**defaults) + self.config_version = config_version @staticmethod def _parse_var_spec(var_spec): @@ -114,7 +117,8 @@ def from_toml(cls, config_fp: Union[str, Path]) -> MetaConfig: if len(config_dict) > 0: raise ValueError(f"Error parsing configuration file '{config_fp}'." f" Unknown keys detected: '{list(config_dict)}'") - return cls(var_list, dist_providers, defaults, n_rows=n_rows) + return cls(var_list, dist_providers, defaults, n_rows=n_rows, + config_version=config_version) def to_dict(self) -> dict: """Convert the configuration to a dictionary. @@ -125,10 +129,10 @@ def to_dict(self) -> dict: Configuration in dictionary form. """ return { - "general": { - "privacy": self.privacy, - "dist_providers": self.dist_providers, - }, + "config_version": self.config_version, + "dist_providers": self.dist_providers, + "n_rows": self.n_rows, + "defaults": self.defaults, "var": self.var_specs } diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index c13de0a0..68d44561 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -6,7 +6,7 @@ import pathlib from datetime import datetime from importlib.metadata import version -from typing import Any, Dict, List, Optional, Sequence, Union +from typing import Any, Dict, List, Optional, Sequence, Union, no_type_check import numpy as np import polars as pl @@ -106,13 +106,13 @@ def fit_dataframe( # noqa: PLR0912 elif isinstance(var_specs, MetaConfig): meta_config = var_specs elif var_specs is None: - meta_config = MetaConfig([], dist_providers, privacy) + meta_config = MetaConfig([], dist_providers, defaults = {"privacy": privacy}) else: - meta_config = MetaConfig(var_specs, dist_providers, privacy) + meta_config = MetaConfig(var_specs, dist_providers, defaults = {"privacy": privacy}) if dist_providers is not None: meta_config.dist_providers = dist_providers # type: ignore if privacy is not None: - meta_config.privacy = privacy # type: ignore + meta_config.defaults["privacy"] = privacy # type: ignore if df is not None and not isinstance(df, pl.DataFrame): if isinstance(df, (str, pathlib.Path)): @@ -297,6 +297,7 @@ def from_json(cls, fp: Union[pathlib.Path, str], meta_vars = [MetaVar.from_dict(d) for d in self_dict["vars"]] return cls(meta_vars, n_rows) + @no_type_check def to_toml(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: self_dict = _jsonify(self.to_dict()) diff --git a/metasyn/privacy.py b/metasyn/privacy.py index bb16280a..45c37440 100644 --- a/metasyn/privacy.py +++ b/metasyn/privacy.py @@ -51,6 +51,19 @@ def fit_kwargs(self): """ return self.to_dict()["parameters"] + def comment(self, col_name): # noqa + """Comment on the privacy features for the TOML GMF file. + + Parameters + ---------- + col_name + Name of the column. + + Returns + ------- + A comment on the privacy features. + """ + return "" class BasicPrivacy(BasePrivacy): """Class representing no privacy level. diff --git a/metasyn/provider.py b/metasyn/provider.py index 1af39da6..9753e968 100644 --- a/metasyn/provider.py +++ b/metasyn/provider.py @@ -241,6 +241,8 @@ def create(self, var_spec: Union[VarSpec, VarSpecAccess]) -> BaseDistribution: """ dist_spec = var_spec.dist_spec unique = dist_spec.unique if dist_spec.unique else False + if dist_spec.implements is None: + raise ValueError("Cannot create distribution without specifying the 'implements' key.") dist_class = self.find_distribution( dist_spec.implements, var_spec.var_type, privacy=BasicPrivacy(), unique=unique) diff --git a/metasyn/varspec.py b/metasyn/varspec.py index 43b8fceb..5f7af2f5 100644 --- a/metasyn/varspec.py +++ b/metasyn/varspec.py @@ -214,3 +214,6 @@ class VarDefaults(): def __post_init__(self): if isinstance(self.privacy, dict): self.privacy = get_privacy(**self.privacy) + else: + self.privacy = get_privacy("none") + From a3baa211a98c473f274769687d98d34f76b67944 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 19 Sep 2024 13:04:13 +0200 Subject: [PATCH 04/25] Fix CI tests --- metasyn/metaframe.py | 16 +++++++++++++--- metasyn/varspec.py | 16 +++++++++++++++- 2 files changed, 28 insertions(+), 4 deletions(-) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index 68d44561..7c3ebc0e 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -10,8 +10,12 @@ import numpy as np import polars as pl -import tomlkit -import tomllib + +try: + import tomllib +except ImportError: + import tomli as tomllib # type: ignore # noqa + from tqdm import tqdm from metasyn.config import MetaConfig @@ -300,6 +304,11 @@ def from_json(cls, fp: Union[pathlib.Path, str], @no_type_check def to_toml(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: + try: + import tomlkit + except ImportError: + raise ValueError("Please install tomlkit (pip install tomlkit) to " + "enable support for exporting to toml.") self_dict = _jsonify(self.to_dict()) if validate: validate_gmf_dict(self_dict) @@ -317,7 +326,8 @@ def to_toml(self, fp: Optional[Union[pathlib.Path, str]], doc["vars"][i]["creation_method"].add(tomlkit.comment(privacy.comment(var.name))) if var.distribution.matches_name("multinoulli"): counts = (var.distribution.probs*(1-var.prop_missing)*self.n_rows).round() - doc["vars"][i]["distribution"].add(tomlkit.comment(f"Counts: {counts.astype(int)}\n")) + doc["vars"][i]["distribution"].add(tomlkit.comment( + f"Counts: {counts.astype(int)}\n")) if fp is None: print(tomlkit.dumps(doc)) diff --git a/metasyn/varspec.py b/metasyn/varspec.py index 5f7af2f5..74027da1 100644 --- a/metasyn/varspec.py +++ b/metasyn/varspec.py @@ -206,6 +206,20 @@ def from_dict(cls, var_dict: dict) -> VarSpec: @dataclass class VarDefaults(): + """Dataclass for variable defaults. + + Parameters + ---------- + data_free: + Whether the variable is completely synthetic or is based on real data. + prop_missing: + Proportion of missing values. + distribution: + Dictionary containing default distributions for each variable type. + privacy: + Privacy to be used by default for estimating distributions. + """ + data_free: bool = False prop_missing: Optional[float] = None distribution: Optional[dict] = None @@ -214,6 +228,6 @@ class VarDefaults(): def __post_init__(self): if isinstance(self.privacy, dict): self.privacy = get_privacy(**self.privacy) - else: + elif not isinstance(self.privacy, BasePrivacy): self.privacy = get_privacy("none") From c26faecf4c4dddd8cf4910b35ff7b2630db7df43 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 19 Sep 2024 13:09:47 +0200 Subject: [PATCH 05/25] Fix tests --- .github/workflows/core-ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/core-ci.yml b/.github/workflows/core-ci.yml index c56a0fb1..944b6cc5 100644 --- a/.github/workflows/core-ci.yml +++ b/.github/workflows/core-ci.yml @@ -21,7 +21,7 @@ jobs: - name: Install dependencies run: | python -m pip install --upgrade pip - python -m pip install ".[check]" + python -m pip install ".[check]" tomlkit - name: Lint with Ruff run: ruff check - name: Check types with MyPy From 869ec9652f98185cec5dbe1c5755c09a66eedb01 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 10:06:52 +0200 Subject: [PATCH 06/25] Add tests and move gmf/config files --- examples/basic_example.py | 7 +- examples/config_files/example_all.toml | 331 +++++ .../{ => config_files}/example_config.toml | 0 examples/config_files/example_datafree.toml | 53 + examples/demonstration.csv | 892 ------------- examples/getting_started.ipynb | 1167 +---------------- .../{ => gmf_files}/example_gmf_simple.json | 4 +- .../{ => gmf_files}/example_gmf_titanic.json | 0 metasyn/testutils.py | 116 ++ tests/data/bad_config.toml | 1 + tests/test_dataset.py | 7 + tests/test_toml.py | 49 + 12 files changed, 614 insertions(+), 2013 deletions(-) create mode 100644 examples/config_files/example_all.toml rename examples/{ => config_files}/example_config.toml (100%) create mode 100644 examples/config_files/example_datafree.toml delete mode 100644 examples/demonstration.csv rename examples/{ => gmf_files}/example_gmf_simple.json (97%) rename examples/{ => gmf_files}/example_gmf_titanic.json (100%) create mode 100644 tests/data/bad_config.toml create mode 100644 tests/test_toml.py diff --git a/examples/basic_example.py b/examples/basic_example.py index 6541c6ba..95dac63e 100644 --- a/examples/basic_example.py +++ b/examples/basic_example.py @@ -1,3 +1,5 @@ +from pathlib import Path + from metasyn import MetaFrame, demo_dataframe from metasyn.config import VarSpec @@ -14,12 +16,13 @@ mf = MetaFrame.fit_dataframe(df, var_specs=specs) # write to json -mf.export("example_gmf_simple.json") +gmf_path = Path("gmf_files", "example_gmf_simple.json") +mf.export(gmf_path) # then, export json from secure environment # outside secure environment, load json -mf_out = MetaFrame.from_json("example_gmf_simple.json") +mf_out = MetaFrame.from_json(gmf_path) # create a fake dataset df_syn = mf_out.synthesize(10) diff --git a/examples/config_files/example_all.toml b/examples/config_files/example_all.toml new file mode 100644 index 00000000..c4bfd61f --- /dev/null +++ b/examples/config_files/example_all.toml @@ -0,0 +1,331 @@ +config_version = "1.1" +dist_providers = ["builtin"] +n_rows = 100 + +[defaults] +data_free = true +prop_missing = 0.1 + +[[var]] +name = "DiscreteNormalDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.normal" +unique = false + +[var.distribution.parameters] +mean = 0 +sd = 1 + + +[[var]] +name = "DiscreteTruncatedNormalDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.truncated_normal" +unique = false + +[var.distribution.parameters] +lower = -1 +upper = 2 +mean = 0 +sd = 1 + + +[[var]] +name = "DiscreteUniformDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.uniform" +unique = false + +[var.distribution.parameters] +lower = 0 +upper = 10 + + +[[var]] +name = "PoissonDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.poisson" +unique = false + +[var.distribution.parameters] +rate = 0.5 + + +[[var]] +name = "UniqueKeyDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.unique_key" +unique = true + +[var.distribution.parameters] +lower = 0 +consecutive = false + + +[[var]] +name = "UniformDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.uniform" +unique = false + +[var.distribution.parameters] +lower = 0 +upper = 1 + + +[[var]] +name = "NormalDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.normal" +unique = false + +[var.distribution.parameters] +mean = 0 +sd = 1 + + +[[var]] +name = "LogNormalDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.lognormal" +unique = false + +[var.distribution.parameters] +mean = 0 +sd = 1 + + +[[var]] +name = "TruncatedNormalDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.truncated_normal" +unique = false + +[var.distribution.parameters] +lower = -1 +upper = 2 +mean = 0 +sd = 1 + + +[[var]] +name = "ExponentialDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.exponential" +unique = false + +[var.distribution.parameters] +rate = 1.0 + + +[[var]] +name = "MultinoulliDistribution" +var_type = "categorical" + +[var.distribution] +implements = "core.multinoulli" +unique = false + +[var.distribution.parameters] +labels = ["a", "b", "c"] +probs = [0.1, 0.3, 0.6] + + +[[var]] +name = "RegexDistribution" +var_type = "string" + +[var.distribution] +implements = "core.regex" +unique = false + +[var.distribution.parameters.regex_data] +regex = "[ABC][0-9]{3,4}" +counts = [1, 1, 1] + + +[[var]] +name = "UniqueRegexDistribution" +var_type = "string" + +[var.distribution] +implements = "core.regex" +unique = true + +[var.distribution.parameters.regex_data] +regex = "[ABC][0-9]{3,4}" +counts = [1, 1, 1] + + +[[var]] +name = "FakerDistribution" +var_type = "string" + +[var.distribution] +implements = "core.faker" +unique = false + +[var.distribution.parameters] +faker_type = "city" +locale = "en_US" + + +[[var]] +name = "UniqueFakerDistribution" +var_type = "string" + +[var.distribution] +implements = "core.faker" +unique = true + +[var.distribution.parameters] +faker_type = "city" +locale = "en_US" + + +[[var]] +name = "FreeTextDistribution" +var_type = "string" + +[var.distribution] +implements = "core.freetext" +unique = false + +[var.distribution.parameters] +locale = "en_US" +avg_sentences = 3 +avg_words = 6 + + +[[var]] +name = "DateUniformDistribution" +var_type = "date" + +[var.distribution] +implements = "core.uniform" +unique = false + +[var.distribution.parameters] +lower = "1903-07-15" +upper = "1940-07-16" + + +[[var]] +name = "TimeUniformDistribution" +var_type = "time" + +[var.distribution] +implements = "core.uniform" +unique = false + +[var.distribution.parameters] +lower = "10:39:36" +upper = "18:39:36" +precision = "seconds" + + +[[var]] +name = "DateTimeUniformDistribution" +var_type = "datetime" + +[var.distribution] +implements = "core.uniform" +unique = false + +[var.distribution.parameters] +lower = "2022-07-15T10:39:36" +upper = "2022-08-15T10:39:36" +precision = "seconds" + + +[[var]] +name = "ConstantDistribution" +var_type = "continuous" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = 0.0 + + +[[var]] +name = "DiscreteConstantDistribution" +var_type = "discrete" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = 0 + + +[[var]] +name = "StringConstantDistribution" +var_type = "string" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = "text" + + +[[var]] +name = "DateTimeConstantDistribution" +var_type = "datetime" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = "2022-07-15T10:39:36" + + +[[var]] +name = "DateConstantDistribution" +var_type = "date" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = "1903-07-15" + + +[[var]] +name = "TimeConstantDistribution" +var_type = "time" + +[var.distribution] +implements = "core.constant" +unique = false + +[var.distribution.parameters] +value = "10:39:36" + diff --git a/examples/example_config.toml b/examples/config_files/example_config.toml similarity index 100% rename from examples/example_config.toml rename to examples/config_files/example_config.toml diff --git a/examples/config_files/example_datafree.toml b/examples/config_files/example_datafree.toml new file mode 100644 index 00000000..412dcf0a --- /dev/null +++ b/examples/config_files/example_datafree.toml @@ -0,0 +1,53 @@ +# Example toml file as input for metasyn + +config_version = "1.1" +dist_providers = ["builtin"] +n_rows = 100 + +[defaults] + +data_free = true +prop_missing = 0.1 + +[defaults.distribution] +discrete = {implements = "core.uniform", parameters = {lower = 1, upper = 30}} +continuous = {implements = "core.normal", parameters = {mean = 0, stdev = 1}} +string = {implements = "core.faker", parameters = {faker_type = "name", locale = "en_US"}} + +[[var]] +name = "PassengerId" +var_type = "discrete" +distribution = {implements = "core.unique_key", unique = true, parameters = {"consecutive" = true, lower=1}} # Notice booleans are lower case in .toml files. +prop_missing = 0.0 + +[[var]] +name = "Name" +description = "Name of the unfortunate passenger of the titanic." +distribution = {implements = "core.faker", parameters = {faker_type = "name", locale = "en_US"}} + +[[var]] +name = "Fare" +distribution = {implements = "core.exponential", parameters = {rate = 0.4}} + +[[var]] +name = "Age" +var_type = "discrete" +distribution = {implements = "core.uniform", parameters = {lower = 20, upper = 40}} + +[[var]] +name = "Cabin" +distribution = {implements = "core.regex", parameters = {regex_data = "[A-F][0-9]{2,3}"}} + +[[var]] +name = "Secret" +var_type = "discrete" + + +[[var]] +name = "Anotherone" +var_type = "string" + +[[var]] +name = "cats" +var_type = "categorical" +distribution = {implements = "core.multinoulli", parameters= {labels = ["male", "female"], probs=[0.45, 0.55]}} diff --git a/examples/demonstration.csv b/examples/demonstration.csv deleted file mode 100644 index e3fb9159..00000000 --- a/examples/demonstration.csv +++ /dev/null @@ -1,892 +0,0 @@ -PassengerId,Name,Sex,Age,Parch,Fare,Cabin,Embarked,Birthday,Board time,Married since,all_NA -1,"Braund, Mr. Owen Harris",male,22,0,7.25,,S,1937-10-28,15:53:04,2022-08-05 04:43:34, -2,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,0,71.2833,C85,C,,12:26:00,2022-08-07 01:56:33, -3,"Heikkinen, Miss. Laina",female,26,0,7.925,,S,1931-09-24,16:08:25,2022-08-04 20:27:37, -4,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,0,53.1,C123,S,1936-11-30,,2022-08-07 07:05:55, -5,"Allen, Mr. William Henry",male,35,0,8.05,,S,1918-11-07,10:59:08,2022-08-02 15:13:34, -6,"Moran, Mr. James",male,,0,8.4583,,Q,1923-06-02,16:28:33,2022-07-28 14:37:30, -7,"McCarthy, Mr. Timothy J",male,54,0,51.8625,E46,S,1928-07-02,17:20:04,2022-07-18 20:20:09, -8,"Palsson, Master. Gosta Leonard",male,2,1,21.075,,S,1918-03-12,17:56:40,2022-08-02 03:42:58, -9,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,2,11.1333,,S,1909-11-16,16:33:50,2022-08-07 04:06:24, -10,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,0,30.0708,,C,,17:28:21,2022-07-17 22:55:10, -11,"Sandstrom, Miss. Marguerite Rut",female,4,1,16.7,G6,S,1903-10-30,16:41:34,2022-07-24 19:18:18, -12,"Bonnell, Miss. Elizabeth",female,58,0,26.55,C103,S,1938-12-31,17:32:25,2022-07-23 03:46:49, -13,"Saundercock, Mr. William Henry",male,20,0,8.05,,S,1932-05-01,11:09:30,2022-07-27 10:47:33, -14,"Andersson, Mr. Anders Johan",male,39,5,31.275,,S,1933-03-06,14:16:15,2022-08-04 18:49:36, -15,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,7.8542,,S,1908-05-26,18:36:24,2022-08-10 22:17:32, -16,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,16.0,,S,1906-05-01,17:46:34,, -17,"Rice, Master. Eugene",male,2,1,29.125,,Q,1909-05-19,15:39:25,2022-08-06 22:46:12, -18,"Williams, Mr. Charles Eugene",male,,0,13.0,,S,1916-12-15,15:00:45,2022-07-24 10:54:46, -19,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,0,18.0,,S,1938-02-27,17:27:11,2022-08-15 03:39:59, -20,"Masselmani, Mrs. Fatima",female,,0,7.225,,C,1921-08-01,13:01:05,2022-08-09 03:06:51, -21,"Fynney, Mr. Joseph J",male,35,0,26.0,,S,1920-09-17,12:11:48,2022-07-31 12:30:35, -22,"Beesley, Mr. Lawrence",male,34,0,13.0,D56,S,1928-09-03,18:30:54,2022-07-15 12:58:08, -23,"McGowan, Miss. Anna ""Annie""",female,15,0,8.0292,,Q,1939-03-28,14:10:42,, -24,"Sloper, Mr. William Thompson",male,28,0,35.5,A6,S,1926-03-20,12:19:12,2022-07-25 06:31:32, -25,"Palsson, Miss. Torborg Danira",female,8,1,21.075,,S,1938-06-17,,2022-07-25 00:25:51, -26,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,5,31.3875,,S,,18:15:57,2022-08-10 05:31:28, -27,"Emir, Mr. Farred Chehab",male,,0,7.225,,C,1921-12-24,,2022-08-09 15:16:19, -28,"Fortune, Mr. Charles Alexander",male,19,2,263.0,C23 C25 C27,S,1934-06-08,11:47:08,2022-07-22 07:34:41, -29,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,7.8792,,Q,1938-03-20,,2022-07-17 12:20:31, -30,"Todoroff, Mr. Lalio",male,,0,7.8958,,S,1928-02-07,11:06:55,2022-07-17 11:29:11, -31,"Uruchurtu, Don. Manuel E",male,40,0,27.7208,,C,,11:18:08,2022-08-01 09:00:50, -32,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,0,146.5208,B78,C,1904-05-23,17:38:32,2022-08-12 00:23:17, -33,"Glynn, Miss. Mary Agatha",female,,0,7.75,,Q,1939-10-03,15:15:06,2022-07-26 20:12:13, -34,"Wheadon, Mr. Edward H",male,66,0,10.5,,S,1907-10-10,18:15:37,2022-07-16 14:14:18, -35,"Meyer, Mr. Edgar Joseph",male,28,0,82.1708,,C,1919-08-24,15:49:03,2022-07-19 00:44:15, -36,"Holverson, Mr. Alexander Oskar",male,42,0,52.0,,S,1939-05-24,17:33:36,2022-08-12 14:24:05, -37,"Mamee, Mr. Hanna",male,,0,7.2292,,C,1917-04-14,17:14:57,2022-08-08 22:40:30, -38,"Cann, Mr. Ernest Charles",male,21,0,8.05,,S,1934-11-16,11:51:09,2022-08-03 22:37:37, -39,"Vander Planke, Miss. Augusta Maria",female,18,0,18.0,,S,1914-04-19,15:05:30,2022-08-14 13:54:54, -40,"Nicola-Yarred, Miss. Jamila",female,14,0,11.2417,,C,1927-09-20,14:07:06,2022-07-18 02:10:45, -41,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,0,9.475,,S,1907-08-06,15:09:05,, -42,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,0,21.0,,S,1909-04-06,18:17:30,2022-08-11 18:57:36, -43,"Kraeff, Mr. Theodor",male,,0,7.8958,,C,1929-01-19,,2022-07-30 02:04:47, -44,"Laroche, Miss. Simonne Marie Anne Andree",female,3,2,41.5792,,C,1939-01-23,,2022-07-25 17:40:43, -45,"Devaney, Miss. Margaret Delia",female,19,0,7.8792,,Q,1910-09-23,18:36:50,2022-07-16 21:31:16, -46,"Rogers, Mr. William John",male,,0,8.05,,S,1913-06-12,10:48:51,2022-08-01 00:12:07, -47,"Lennon, Mr. Denis",male,,0,15.5,,Q,1908-08-05,13:24:32,2022-07-19 06:11:27, -48,"O'Driscoll, Miss. Bridget",female,,0,7.75,,Q,,16:00:34,2022-07-27 09:24:55, -49,"Samaan, Mr. Youssef",male,,0,21.6792,,C,1920-09-13,,2022-07-19 15:04:12, -50,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,0,17.8,,S,1907-07-30,13:47:45,2022-08-02 04:21:34, -51,"Panula, Master. Juha Niilo",male,7,1,39.6875,,S,1923-04-26,14:59:39,2022-07-21 06:35:49, -52,"Nosworthy, Mr. Richard Cater",male,21,0,7.8,,S,,18:15:31,2022-08-09 08:14:03, -53,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,0,76.7292,D33,C,1929-11-03,,2022-08-14 16:38:12, -54,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,0,26.0,,S,1930-11-19,,2022-08-04 07:10:22, -55,"Ostby, Mr. Engelhart Cornelius",male,65,1,61.9792,B30,C,1919-04-01,12:29:33,2022-08-13 13:54:25, -56,"Woolner, Mr. Hugh",male,,0,35.5,C52,S,1905-08-28,18:06:13,2022-08-04 18:15:31, -57,"Rugg, Miss. Emily",female,21,0,10.5,,S,1905-04-01,10:40:18,2022-07-23 20:19:47, -58,"Novel, Mr. Mansouer",male,28,0,7.2292,,C,,,2022-07-21 05:22:04, -59,"West, Miss. Constance Mirium",female,5,2,27.75,,S,1907-07-04,12:45:12,2022-07-22 14:30:14, -60,"Goodwin, Master. William Frederick",male,11,2,46.9,,S,1910-12-18,15:39:59,2022-07-26 03:24:34, -61,"Sirayanian, Mr. Orsen",male,22,0,7.2292,,C,1923-11-01,13:27:13,2022-07-23 20:39:22, -62,"Icard, Miss. Amelie",female,38,0,80.0,B28,,1918-11-02,11:37:34,2022-07-29 05:50:51, -63,"Harris, Mr. Henry Birkhardt",male,45,0,83.475,C83,S,1939-04-18,13:08:10,2022-08-08 21:01:36, -64,"Skoog, Master. Harald",male,4,2,27.9,,S,1922-12-21,16:39:09,2022-08-03 20:21:38, -65,"Stewart, Mr. Albert A",male,,0,27.7208,,C,1913-02-11,11:48:25,2022-07-23 13:46:04, -66,"Moubarek, Master. Gerios",male,,1,15.2458,,C,,11:20:44,2022-07-16 04:33:36, -67,"Nye, Mrs. (Elizabeth Ramell)",female,29,0,10.5,F33,S,1912-03-27,14:31:49,2022-07-31 10:35:43, -68,"Crease, Mr. Ernest James",male,19,0,8.1583,,S,1904-11-07,13:24:11,2022-07-21 01:10:14, -69,"Andersson, Miss. Erna Alexandra",female,17,2,7.925,,S,1938-08-02,12:15:38,2022-07-26 13:20:55, -70,"Kink, Mr. Vincenz",male,26,0,8.6625,,S,1939-05-29,,2022-07-23 11:39:22, -71,"Jenkin, Mr. Stephen Curnow",male,32,0,10.5,,S,1918-12-28,14:40:44,2022-08-15 09:36:35, -72,"Goodwin, Miss. Lillian Amy",female,16,2,46.9,,S,1927-04-25,14:11:50,2022-07-27 15:43:59, -73,"Hood, Mr. Ambrose Jr",male,21,0,73.5,,S,1917-12-20,11:50:14,2022-08-08 03:54:50, -74,"Chronopoulos, Mr. Apostolos",male,26,0,14.4542,,C,1927-01-27,11:35:57,, -75,"Bing, Mr. Lee",male,32,0,56.4958,,S,1913-03-03,14:24:40,2022-07-19 11:26:13, -76,"Moen, Mr. Sigurd Hansen",male,25,0,7.65,F G73,S,1930-05-05,,2022-07-29 15:38:10, -77,"Staneff, Mr. Ivan",male,,0,7.8958,,S,1930-11-08,15:39:49,2022-07-18 07:39:55, -78,"Moutal, Mr. Rahamin Haim",male,,0,8.05,,S,1938-01-25,15:50:46,2022-07-26 11:25:26, -79,"Caldwell, Master. Alden Gates",male,1,2,29.0,,S,1922-06-09,15:00:24,2022-08-05 22:45:56, -80,"Dowdell, Miss. Elizabeth",female,30,0,12.475,,S,1913-04-10,18:38:14,2022-08-10 02:27:56, -81,"Waelens, Mr. Achille",male,22,0,9.0,,S,1925-07-10,15:40:23,, -82,"Sheerlinck, Mr. Jan Baptist",male,29,0,9.5,,S,1917-04-21,11:31:25,2022-08-15 09:31:02, -83,"McDermott, Miss. Brigdet Delia",female,,0,7.7875,,Q,1923-08-06,,2022-07-31 12:54:26, -84,"Carrau, Mr. Francisco M",male,28,0,47.1,,S,1918-03-28,10:55:34,, -85,"Ilett, Miss. Bertha",female,17,0,10.5,,S,1913-02-25,16:23:05,, -86,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",female,33,0,15.85,,S,1908-12-25,14:02:29,2022-08-10 17:00:53, -87,"Ford, Mr. William Neal",male,16,3,34.375,,S,1909-03-12,11:39:17,2022-08-10 17:51:51, -88,"Slocovski, Mr. Selman Francis",male,,0,8.05,,S,1905-08-24,15:29:07,2022-07-22 07:59:40, -89,"Fortune, Miss. 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Augusta",female,30,0,31.0,,C,1906-09-16,11:15:05,2022-07-24 01:02:07, -844,"Lemberopolous, Mr. Peter L",male,34,0,6.4375,,C,1932-05-27,18:08:39,, -845,"Culumovic, Mr. Jeso",male,17,0,8.6625,,S,1925-04-22,12:03:39,, -846,"Abbing, Mr. Anthony",male,42,0,7.55,,S,,14:02:53,2022-07-31 04:10:32, -847,"Sage, Mr. Douglas Bullen",male,,2,69.55,,S,1904-08-29,13:08:15,, -848,"Markoff, Mr. Marin",male,35,0,7.8958,,C,1939-04-14,17:47:02,2022-08-09 01:53:59, -849,"Harper, Rev. John",male,28,1,33.0,,S,1905-06-20,14:19:47,2022-08-05 04:59:39, -850,"Goldenberg, Mrs. Samuel L (Edwiga Grabowska)",female,,0,89.1042,C92,C,1919-02-15,18:10:45,2022-07-29 07:54:52, -851,"Andersson, Master. Sigvard Harald Elias",male,4,2,31.275,,S,1922-12-06,,2022-07-17 16:16:07, -852,"Svensson, Mr. Johan",male,74,0,7.775,,S,1928-06-17,13:40:30,2022-08-04 10:45:32, -853,"Boulos, Miss. Nourelain",female,9,1,15.2458,,C,1908-02-05,11:12:58,2022-08-06 16:16:17, -854,"Lines, Miss. Mary Conover",female,16,1,39.4,D28,S,1916-04-20,13:05:42,2022-08-09 03:43:58, -855,"Carter, Mrs. Ernest Courtenay (Lilian Hughes)",female,44,0,26.0,,S,1938-09-02,13:39:12,2022-08-09 03:06:29, -856,"Aks, Mrs. Sam (Leah Rosen)",female,18,1,9.35,,S,1927-10-06,18:20:35,2022-08-14 23:58:10, -857,"Wick, Mrs. George Dennick (Mary Hitchcock)",female,45,1,164.8667,,S,1908-11-15,12:55:23,2022-08-08 19:08:35, -858,"Daly, Mr. Peter Denis ",male,51,0,26.55,E17,S,1926-08-15,,2022-07-15 18:30:07, -859,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,3,19.2583,,C,1924-03-15,17:34:19,2022-08-08 22:16:32, -860,"Razi, Mr. Raihed",male,,0,7.2292,,C,1927-01-04,,2022-07-22 06:07:51, -861,"Hansen, Mr. Claus Peter",male,41,0,14.1083,,S,1914-04-20,18:38:11,2022-07-27 02:23:17, -862,"Giles, Mr. Frederick Edward",male,21,0,11.5,,S,1923-09-16,16:11:31,2022-08-11 12:10:55, -863,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,25.9292,D17,S,1918-06-11,13:24:06,2022-08-12 01:59:41, -864,"Sage, Miss. Dorothy Edith ""Dolly""",female,,2,69.55,,S,1922-06-20,,2022-08-05 23:57:19, -865,"Gill, Mr. John William",male,24,0,13.0,,S,1903-12-31,18:04:53,2022-08-12 17:56:13, -866,"Bystrom, Mrs. (Karolina)",female,42,0,13.0,,S,1905-06-17,17:55:39,, -867,"Duran y More, Miss. Asuncion",female,27,0,13.8583,,C,1908-04-17,14:07:05,2022-07-28 08:03:10, -868,"Roebling, Mr. Washington Augustus II",male,31,0,50.4958,A24,S,1924-05-15,14:04:48,2022-07-31 16:36:50, -869,"van Melkebeke, Mr. Philemon",male,,0,9.5,,S,1919-02-20,13:57:20,2022-07-19 04:52:58, -870,"Johnson, Master. Harold Theodor",male,4,1,11.1333,,S,1922-01-05,11:08:30,2022-07-15 19:00:57, -871,"Balkic, Mr. Cerin",male,26,0,7.8958,,S,1907-04-18,11:37:04,2022-08-12 07:11:23, -872,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,52.5542,D35,S,1906-09-22,,2022-08-06 23:54:08, -873,"Carlsson, Mr. Frans Olof",male,33,0,5.0,B51 B53 B55,S,1935-05-02,13:53:42,2022-08-03 08:57:03, -874,"Vander Cruyssen, Mr. Victor",male,47,0,9.0,,S,1923-02-25,11:06:07,2022-07-21 13:38:28, -875,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,0,24.0,,C,1930-08-29,15:26:37,2022-07-18 09:35:23, -876,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,7.225,,C,1924-10-01,17:31:01,2022-08-07 05:17:34, -877,"Gustafsson, Mr. Alfred Ossian",male,20,0,9.8458,,S,1908-12-07,13:58:03,2022-08-04 20:00:38, -878,"Petroff, Mr. Nedelio",male,19,0,7.8958,,S,1906-05-24,11:13:04,2022-08-13 15:51:37, -879,"Laleff, Mr. Kristo",male,,0,7.8958,,S,1922-11-19,10:43:39,2022-07-17 13:00:02, -880,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,1,83.1583,C50,C,1931-11-15,14:37:49,2022-07-19 19:15:57, -881,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,1,26.0,,S,1915-06-06,14:08:17,2022-08-15 06:11:18, -882,"Markun, Mr. Johann",male,33,0,7.8958,,S,1921-11-12,15:55:36,2022-07-18 04:28:15, -883,"Dahlberg, Miss. Gerda Ulrika",female,22,0,10.5167,,S,,15:36:36,2022-08-05 13:26:26, -884,"Banfield, Mr. Frederick James",male,28,0,10.5,,S,1934-09-04,16:10:24,2022-08-06 03:44:50, -885,"Sutehall, Mr. Henry Jr",male,25,0,7.05,,S,1938-03-07,17:36:02,2022-08-02 02:29:17, -886,"Rice, Mrs. William (Margaret Norton)",female,39,5,29.125,,Q,1923-05-27,15:55:39,, -887,"Montvila, Rev. Juozas",male,27,0,13.0,,S,1918-09-16,13:58:18,2022-08-02 17:29:12, -888,"Graham, Miss. Margaret Edith",female,19,0,30.0,B42,S,1911-04-28,11:43:34,2022-07-30 03:35:42, -889,"Johnston, Miss. Catherine Helen ""Carrie""",female,,2,23.45,,S,1939-03-18,14:41:36,, -890,"Behr, Mr. Karl Howell",male,26,0,30.0,C148,C,1905-04-16,13:37:08,2022-07-23 08:04:22, -891,"Dooley, Mr. Patrick",male,32,0,7.75,,Q,,17:21:32,2022-08-01 11:07:59, diff --git a/examples/getting_started.ipynb b/examples/getting_started.ipynb index f05fa9aa..cc680b5b 100644 --- a/examples/getting_started.ipynb +++ b/examples/getting_started.ipynb @@ -57,12 +57,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "2442cb34", "metadata": {}, "outputs": [], "source": [ "# import required packages\n", + "from pathlib import Path\n", + "\n", "import polars as pl\n", "\n", "from metasyn import MetaFrame, VarSpec, demo_file" @@ -86,50 +88,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "3c2a44b7", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]str
1"Braund, Mr. Owen Harris""male"220"A/5 21171"7.25null"S"1937-10-2815:53:042022-08-05 04:43:34null
2"Cumings, Mrs. John Bradley (Fl…"female"380"PC 17599"71.2833"C85""C"null12:26:002022-08-07 01:56:33null
3"Heikkinen, Miss. Laina""female"260"STON/O2. 3101282"7.925null"S"1931-09-2416:08:252022-08-04 20:27:37null
4"Futrelle, Mrs. Jacques Heath (…"female"350"113803"53.1"C123""S"1936-11-30null2022-08-07 07:05:55null
5"Allen, Mr. William Henry""male"350"373450"8.05null"S"1918-11-0710:59:082022-08-02 15:13:34null
" - ], - "text/plain": [ - "shape: (5, 13)\n", - "┌─────────────┬───────────────┬────────┬─────┬───┬────────────┬────────────┬──────────────┬────────┐\n", - "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", - "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", - "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ --- ┆ str │\n", - "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ datetime[μs] ┆ │\n", - "╞═════════════╪═══════════════╪════════╪═════╪═══╪════════════╪════════════╪══════════════╪════════╡\n", - "│ 1 ┆ Braund, Mr. ┆ male ┆ 22 ┆ … ┆ 1937-10-28 ┆ 15:53:04 ┆ 2022-08-05 ┆ null │\n", - "│ ┆ Owen Harris ┆ ┆ ┆ ┆ ┆ ┆ 04:43:34 ┆ │\n", - "│ 2 ┆ Cumings, Mrs. ┆ female ┆ 38 ┆ … ┆ null ┆ 12:26:00 ┆ 2022-08-07 ┆ null │\n", - "│ ┆ John Bradley ┆ ┆ ┆ ┆ ┆ ┆ 01:56:33 ┆ │\n", - "│ ┆ (Fl… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "│ 3 ┆ Heikkinen, ┆ female ┆ 26 ┆ … ┆ 1931-09-24 ┆ 16:08:25 ┆ 2022-08-04 ┆ null │\n", - "│ ┆ Miss. Laina ┆ ┆ ┆ ┆ ┆ ┆ 20:27:37 ┆ │\n", - "│ 4 ┆ Futrelle, ┆ female ┆ 35 ┆ … ┆ 1936-11-30 ┆ null ┆ 2022-08-07 ┆ null │\n", - "│ ┆ Mrs. Jacques ┆ ┆ ┆ ┆ ┆ ┆ 07:05:55 ┆ │\n", - "│ ┆ Heath (… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "│ 5 ┆ Allen, Mr. ┆ male ┆ 35 ┆ … ┆ 1918-11-07 ┆ 10:59:08 ┆ 2022-08-02 ┆ null │\n", - "│ ┆ William Henry ┆ ┆ ┆ ┆ ┆ ┆ 15:13:34 ┆ │\n", - "└─────────────┴───────────────┴────────┴─────┴───┴────────────┴────────────┴──────────────┴────────┘" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# get the demonstration data file\n", "csv_path = demo_file(\"titanic\")\n", @@ -154,33 +116,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "0a5a1aa2", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Schema([('PassengerId', Int64),\n", - " ('Name', String),\n", - " ('Sex', Categorical(ordering='physical')),\n", - " ('Age', Int64),\n", - " ('Parch', Int64),\n", - " ('Ticket', String),\n", - " ('Fare', Float64),\n", - " ('Cabin', String),\n", - " ('Embarked', Categorical(ordering='physical')),\n", - " ('Birthday', Date),\n", - " ('Board time', Time),\n", - " ('Married since', Datetime(time_unit='us', time_zone=None)),\n", - " ('all_NA', String)])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df.schema" ] @@ -195,59 +134,12 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "c72c2acb55fca193", "metadata": { "collapsed": false }, - "outputs": [ - { - "data": { - "text/html": [ - "
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statisticPassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
strf64strstrf64f64strf64strstrstrstrstrstr
"count"891.0"891""891"714.0891.0"891"891.0"204""889""813""812""799""0"
"null_count"0.0"0""0"177.00.0"0"0.0"687""2""78""79""92""891"
"mean"446.0nullnull29.6932770.381594null32.204208nullnull"1921-07-27 22:08:24.798000""14:38:10.014778""2022-07-31 03:43:48.767209"null
"std"257.353842nullnull14.5245270.806057null49.693429nullnullnullnullnullnull
"min"1.0"Abbing, Mr. Anthony"null0.00.0"110152"0.0"A10"null"1903-07-28""10:39:40""2022-07-15 12:21:15"null
"25%"224.0nullnull20.00.0null7.925nullnull"1911-09-18""12:39:02""2022-07-23 11:16:56"null
"50%"446.0nullnull28.00.0null14.4542nullnull"1922-03-26""14:29:34""2022-07-31 00:36:56"null
"75%"669.0nullnull38.00.0null31.0nullnull"1930-08-29""16:40:12""2022-08-08 03:35:52"null
"max"891.0"van Melkebeke, Mr. Philemon"null80.06.0"WE/P 5735"512.3292"T"null"1940-05-27""18:39:28""2022-08-15 10:32:05"null
" - ], - "text/plain": [ - "shape: (9, 14)\n", - "┌────────────┬─────────────┬────────────┬──────┬───┬────────────┬────────────┬────────────┬────────┐\n", - "│ statistic ┆ PassengerId ┆ Name ┆ Sex ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", - "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", - "│ str ┆ f64 ┆ str ┆ str ┆ ┆ str ┆ str ┆ --- ┆ str │\n", - "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ str ┆ │\n", - "╞════════════╪═════════════╪════════════╪══════╪═══╪════════════╪════════════╪════════════╪════════╡\n", - "│ count ┆ 891.0 ┆ 891 ┆ 891 ┆ … ┆ 813 ┆ 812 ┆ 799 ┆ 0 │\n", - "│ null_count ┆ 0.0 ┆ 0 ┆ 0 ┆ … ┆ 78 ┆ 79 ┆ 92 ┆ 891 │\n", - "│ mean ┆ 446.0 ┆ null ┆ null ┆ … ┆ 1921-07-27 ┆ 14:38:10.0 ┆ 2022-07-31 ┆ null │\n", - "│ ┆ ┆ ┆ ┆ ┆ 22:08:24.7 ┆ 14778 ┆ 03:43:48.7 ┆ │\n", - "│ ┆ ┆ ┆ ┆ ┆ 98000 ┆ ┆ 67209 ┆ │\n", - "│ std ┆ 257.353842 ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │\n", - "│ min ┆ 1.0 ┆ Abbing, ┆ null ┆ … ┆ 1903-07-28 ┆ 10:39:40 ┆ 2022-07-15 ┆ null │\n", - "│ ┆ ┆ Mr. ┆ ┆ ┆ ┆ ┆ 12:21:15 ┆ │\n", - "│ ┆ ┆ Anthony ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "│ 25% ┆ 224.0 ┆ null ┆ null ┆ … ┆ 1911-09-18 ┆ 12:39:02 ┆ 2022-07-23 ┆ null │\n", - "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 11:16:56 ┆ │\n", - "│ 50% ┆ 446.0 ┆ null ┆ null ┆ … ┆ 1922-03-26 ┆ 14:29:34 ┆ 2022-07-31 ┆ null │\n", - "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 00:36:56 ┆ │\n", - "│ 75% ┆ 669.0 ┆ null ┆ null ┆ … ┆ 1930-08-29 ┆ 16:40:12 ┆ 2022-08-08 ┆ null │\n", - "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 03:35:52 ┆ │\n", - "│ max ┆ 891.0 ┆ van ┆ null ┆ … ┆ 1940-05-27 ┆ 18:39:28 ┆ 2022-08-15 ┆ null │\n", - "│ ┆ ┆ Melkebeke, ┆ ┆ ┆ ┆ ┆ 10:32:05 ┆ │\n", - "│ ┆ ┆ Mr. ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "│ ┆ ┆ Philemon ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "└────────────┴─────────────┴────────────┴──────┴───┴────────────┴────────────┴────────────┴────────┘" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df.describe()" ] @@ -280,23 +172,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "e0c58473", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/13 [00:00\n", - "shape: (5, 13)
PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]null
724"Street.""female"430"86225"103.760852null"C"1916-11-1815:57:462022-08-15 06:43:52null
389"Poor. Tend. Loss. Fill.""male"51"167975"5.074021null"S"1908-12-2915:00:562022-08-04 01:26:06null
128"Force.""male"370"50570"1.347821null"S"1930-08-3114:44:022022-07-24 23:16:53null
646"Line. Enter. Financial arrive.…"female"null0"8018"42.809746"E7""S"1934-09-2116:26:082022-08-13 16:23:17null
324"Tax sit. Benefit. Money.""male"270"803170"22.745622null"S"1914-05-1918:07:532022-07-16 14:24:41null
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1"Officer. Together. These.""male"510"38742"15.804912null"S"1932-06-2018:20:222022-07-29 05:37:46null
2"Seven claim. Assume statement.…"male"null0"3418"9.587488null"S"1934-01-1215:17:182022-07-24 03:51:51null
3"Act seek and.""male"170"8129"5.366794null"S"1932-04-0911:54:052022-07-24 05:24:06null
4"Building. Occur. Century.""male"110"121137"27.170373null"C"1919-12-1611:08:08nullnull
5"Big. Financial.""female"500"506091"3.406364null"S"1915-05-27null2022-08-01 16:27:03null
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PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]null
1"Laura Carter""male"230"802304"4.320629null"S"1909-12-1114:37:392022-07-27 09:10:07null
2"Brian Meadows""male"null0"9274"37.57741"F551""S"1904-02-2413:10:502022-07-22 17:18:33null
3"Matthew Leon""male"null0"6217"149.902722null"S"1932-12-0915:11:172022-08-11 01:01:23null
4"Edward Thomas""female"270"635722"31.938827null"S"1909-03-2516:47:522022-07-21 23:19:18null
5"Richard Shepard III""male"null0"2007"132.868876null"S"1930-05-0815:47:512022-07-25 02:54:31null
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i64strcati64i64strf64strcatdatetimedatetime[μs]null
1"Nicole Sims""male"null0"3805"1.348719null"Q"1906-07-0317:27:592022-07-21 23:26:20null
2"Dr. David Taylor""female"272"581310"1.257062null"S"1916-01-3014:02:152022-07-28 03:25:30null
3"Brian Kelly""female"null0"285450"1.870011"G6 ""C"1931-10-0914:07:412022-08-14 14:23:07null
4"Jennifer Flores""female"220"951612"0.843858null"S"1934-12-0816:12:262022-08-15 02:10:52null
5"Grace Gutierrez""female"300"4978"1.145782null"S"1917-02-2812:19:202022-07-18 16:00:16null
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PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]null
1"Kathy Crawford""male"330"36003"1.797109null"C"1928-07-1917:40:172022-07-23 02:35:47null
2"Toni Rodriguez""female"370"7260"1.832633null"S"1915-01-1717:06:542022-07-29 08:50:29null
3"Jesse Lopez""female"260"265335"0.598759null"S"1935-10-1612:27:442022-08-09 13:10:57null
4"Ashley Wheeler""female"null0"41223"0.121366"F635""S"1935-08-2714:44:392022-08-12 10:31:37null
5"Edward Jones""female"270"4287"0.685862null"S"1929-07-0213:57:052022-07-23 09:33:00null
6"Scott Abbott""female"null0"5060"2.251193null"C"1915-07-0514:30:592022-08-07 17:07:11null
7"Samantha Reyes""female"280"74697"0.813593"C06""S"1938-11-2816:23:542022-07-27 06:23:42null
8"Danielle Chaney""male"310"848674"1.765307null"S"1922-12-1315:33:102022-07-21 04:47:26null
9"Rebecca Wade""female"310"OR 00654"0.398557"D488""S"1939-07-1013:27:52nullnull
10"Steven Rice""male"230"223076"0.906104null"S"null12:59:282022-08-09 03:06:18null
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PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
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"100%|██████████| 13/13 [00:00<00:00, 14.49it/s]\n" - ] - } - ], + "outputs": [], "source": [ "var_specs = [\n", " # Ensure unique values for the `PassengerId` column\n", @@ -1695,20 +660,12 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "id": "694d4474707f7950", "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'Cabin': 'The cabin number of the passenger.'}\n" - ] - } - ], + "outputs": [], "source": [ "print(mf.descriptions)" ] @@ -1725,20 +682,12 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "34a8aafc95c0219f", "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'PassengerId': 'The ID of each passenger, as assigned by Pandas.', 'Cabin': 'The cabin number of the passenger.'}\n" - ] - } - ], + "outputs": [], "source": [ "mf[\"PassengerId\"].description = \"The ID of each passenger, as assigned by Pandas.\"\n", "\n", @@ -1757,20 +706,12 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "3b2e873f7362160a", "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'PassengerId': 'The ID of each passenger, as assigned by Pandas.', 'Name': 'Name of the passenger', 'Age': 'Age of the passenger in years', 'Cabin': 'The cabin number of the passenger.'}\n" - ] - } - ], + "outputs": [], "source": [ "mf.descriptions = {\"Name\": \"Name of the passenger\", \"Age\": \"Age of the passenger in years\"}\n", "\n", @@ -1793,20 +734,12 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "ab2b34ed6b11578c", "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'PassengerId': 'Placeholder description for PassengerId', 'Name': 'Placeholder description for Name', 'Sex': 'Placeholder description for Sex', 'Age': 'Placeholder description for Age', 'Parch': 'Placeholder description for Parch', 'Ticket': 'Placeholder description for Ticket', 'Fare': 'Placeholder description for Fare', 'Cabin': 'Placeholder description for Cabin', 'Embarked': 'Placeholder description for Embarked', 'Birthday': 'Placeholder description for Birthday', 'Board time': 'Placeholder description for Board time', 'Married since': 'Placeholder description for Married since', 'all_NA': 'Placeholder description for all_NA'}\n" - ] - } - ], + "outputs": [], "source": [ "mf.descriptions = [f\"Placeholder description for {var.name}\" for var in mf.meta_vars]\n", "\n", @@ -1845,7 +778,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.11.6" }, "vscode": { "interpreter": { diff --git a/examples/example_gmf_simple.json b/examples/gmf_files/example_gmf_simple.json similarity index 97% rename from examples/example_gmf_simple.json rename to examples/gmf_files/example_gmf_simple.json index 901acaef..b7cf5001 100644 --- a/examples/example_gmf_simple.json +++ b/examples/gmf_files/example_gmf_simple.json @@ -4,9 +4,9 @@ "provenance": { "created by": { "name": "metasyn", - "version": "0.8.1.dev0+ge481025.d20240325" + "version": "1.0.2.dev34+gd68929e" }, - "creation time": "2024-03-25T17:06:53.455575" + "creation time": "2024-10-01T09:57:15.595769" }, "vars": [ { diff --git a/examples/example_gmf_titanic.json b/examples/gmf_files/example_gmf_titanic.json similarity index 100% rename from examples/example_gmf_titanic.json rename to examples/gmf_files/example_gmf_titanic.json diff --git a/metasyn/testutils.py b/metasyn/testutils.py index 017028b5..6403cda5 100644 --- a/metasyn/testutils.py +++ b/metasyn/testutils.py @@ -7,10 +7,14 @@ from __future__ import annotations +import json + import jsonschema +import numpy as np import polars as pl from jsonschema.exceptions import SchemaError +from metasyn.distribution import MultinoulliDistribution, NADistribution from metasyn.distribution.base import BaseDistribution from metasyn.metaframe import _jsonify from metasyn.privacy import BasePrivacy @@ -19,6 +23,7 @@ DistributionProviderList, get_distribution_provider, ) +from metasyn.var import MetaVar def check_distribution_provider(provider_name: str): @@ -81,3 +86,114 @@ def check_distribution(distribution: type[BaseDistribution], privacy: BasePrivac assert isinstance(new_dist, distribution) assert set(list(new_dist.to_dict())) >= set( ("implements", "provenance", "class_name", "parameters")) + + + +HEADER_TEMPLATE = """ +# Metasyn report for {file_name} + +## General + +- Number of rows: {n_rows} +- Number of columns: {n_columns} +- Generated by {program_name} version {program_version} at {generation_time} + +## Variables / columns + +""" + + +VAR_TEMPLATE = """ +### {var_name} + +- Distribution {class_name} with parameters: +{parameters} +- Variable type {var_type} +- Based on {n_based_on} values{disclosure} +- Percentage missing: {missing_perc} % +- Generated examples: {example_list} + + +""" + +def create_md_report(file_name, out_md_file): + with open(file_name, "r") as handle: + gmf_dict = json.load(handle) + + header = HEADER_TEMPLATE.format( + file_name=file_name, + n_rows=gmf_dict["n_rows"], + n_columns=gmf_dict["n_columns"], + program_name=gmf_dict["provenance"]["created by"]["name"], + program_version=gmf_dict["provenance"]["created by"]["version"], + generation_time=gmf_dict["provenance"]["creation time"], + ) + variables = "" + + for var_dict in gmf_dict["vars"]: + var = MetaVar.from_dict(var_dict) + if isinstance(var.distribution, MultinoulliDistribution): + parameters = [f"\t- {label}: {round(prob*gmf_dict['n_rows']*(1-var.prop_missing))}\n" + for label, prob in zip(var.distribution.labels, var.distribution.probs)] + elif isinstance(var.distribution, NADistribution): + variables += (f"### {var.name}\n- Distribution NADistribution\n- Only missing values" + "\n- Examples: NA, NA, NA, ...\n") + continue + else: + parameters = [f"\t - {name}: {value}\n" + for name, value in var.distribution._param_dict().items()] + parameter_str = "".join(parameters) + if var.prop_missing > 0: + examples = np.random.permutation([str(var.distribution.draw()) for _ in range(3)] + + ["NA", "NA"]) + else: + examples = [str(x) for x in var.draw_series(5)] + + if "privacy" in var_dict["creation_method"]: + partition_size = var_dict["creation_method"]["privacy"]["parameters"]["partition_size"] + disclosure = f" using micro aggregation with a partition size of {partition_size}" + else: + disclosure = "" + variables += VAR_TEMPLATE.format( + var_name = var.name, + var_type=var.var_type, + class_name=var.distribution.__class__.__name__, + n_based_on=round(gmf_dict["n_rows"]*(1-var.prop_missing)), + example_list=", ".join(examples) + ", ...", + parameters=parameter_str, + missing_perc=f"{100*var.prop_missing:.2f}", + disclosure=disclosure, + ) + with open(out_md_file, "w", encoding="utf-8") as handle: + handle.write(header + variables) + + +def create_input_toml(file_name): + import tomlkit + + prov = get_distribution_provider("builtin") + doc = tomlkit.document() + doc.add("config_version", "1.1") + doc.add("dist_providers", ["builtin"]) + doc.add("n_rows", 100) + doc.add("defaults", {"data_free": True, "prop_missing": 0.1}) + var_array = tomlkit.aot() + for dist in prov.distributions: + var = tomlkit.table() + var.add("name", dist.__name__) + if isinstance(dist.var_type, str): + var_type = dist.var_type + else: + var_type = dist.var_type[0] + var.add("var_type", var_type) + dist_dict = _jsonify(dist.default_distribution().to_dict()) + dist_dict.pop("version") + dist_dict.pop("class_name") + dist_dict.pop("provenance") + var.add("distribution", dist_dict) + var.add(tomlkit.nl()) + var_array.append(var) + doc.add("var", var_array) + + with open(file_name, "w", encoding="utf-8") as handle: + tomlkit.dump(doc, handle) diff --git a/tests/data/bad_config.toml b/tests/data/bad_config.toml new file mode 100644 index 00000000..3790ef5e --- /dev/null +++ b/tests/data/bad_config.toml @@ -0,0 +1 @@ +This is not a toml file \ No newline at end of file diff --git a/tests/test_dataset.py b/tests/test_dataset.py index 819c40d7..278d435a 100644 --- a/tests/test_dataset.py +++ b/tests/test_dataset.py @@ -143,3 +143,10 @@ def test_demo_datasets(tmp_path, dataset_name): def test_demo_non_exist(): with pytest.raises(ValueError): demo_file("non-existing-dataset") + + +def test_create_dataset(tmpdir): + test_class = _get_demo_class("test") + test_class.create(tmpdir/"test.csv") + df = pl.read_csv(Path(tmpdir/"test.csv")) + assert isinstance(df, pl.DataFrame) diff --git a/tests/test_toml.py b/tests/test_toml.py new file mode 100644 index 00000000..efc90551 --- /dev/null +++ b/tests/test_toml.py @@ -0,0 +1,49 @@ +from metasyn.testutils import create_input_toml, create_md_report +from metasyn.metaframe import MetaFrame +from metasyn.provider import BuiltinDistributionProvider +from metasyn.demo import demo_dataframe +from filecmp import cmp +from pathlib import Path +from pytest import mark + + +def test_datafree_create(tmpdir): + + temp_toml = tmpdir / "test.toml" + create_input_toml(temp_toml) + assert cmp(temp_toml, Path("examples", "config_files", "example_all.toml")) + mf = MetaFrame.fit_dataframe(None, var_specs=Path(temp_toml)) + + assert isinstance(mf, MetaFrame) + assert mf.n_columns == len(BuiltinDistributionProvider.distributions) + +@mark.parametrize( + "toml_input,data", [ + (Path("examples", "config_files", "example_all.toml"), None), + (Path("examples", "config_files", "example_config.toml"), demo_dataframe("titanic")), + (Path("examples", "config_files", "example_datafree.toml"), None), + ] +) +def test_toml_store_load(tmpdir, toml_input, data): + mf = MetaFrame.fit_dataframe(data, toml_input) + mf.to_toml(tmpdir/"test.toml") + new_mf = mf.from_toml(tmpdir/"test.toml") + assert mf.n_columns == new_mf.n_columns + +@mark.parametrize( + "gmf_file", [ + Path("examples", "gmf_files", "example_gmf_simple.json"), + Path("examples", "gmf_files", "example_gmf_titanic.json"), + ] +) +def test_md_output(tmpdir, gmf_file): + create_md_report(gmf_file, tmpdir/"test.md") + assert Path(tmpdir/"test.md").is_file() + assert isinstance(MetaFrame.from_json(gmf_file), MetaFrame) + +def test_toml_err(): + with pytest.raises(FileNotFoundError): + MetaFrame.from_config("doesnotexist.toml") + + with pytest.raises(tomllib.TOMLDecodeError): + MetaFrame.from_config(Path("tests", "data", "bad_config.toml")) \ No newline at end of file From a380e48e1a83b8ca52d7026f5dbd1a1b07f56f2e Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 10:08:20 +0200 Subject: [PATCH 07/25] Fix missing docstring --- metasyn/testutils.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/metasyn/testutils.py b/metasyn/testutils.py index 6403cda5..10daa15a 100644 --- a/metasyn/testutils.py +++ b/metasyn/testutils.py @@ -117,6 +117,7 @@ def check_distribution(distribution: type[BaseDistribution], privacy: BasePrivac """ def create_md_report(file_name, out_md_file): + """Create markdown report from GMF file.""" with open(file_name, "r") as handle: gmf_dict = json.load(handle) @@ -169,6 +170,7 @@ def create_md_report(file_name, out_md_file): def create_input_toml(file_name): + """Create input toml with all distribution in builtin.""" import tomlkit prov = get_distribution_provider("builtin") From 828e75373f1269a07519b96e9b46f2b64ebd8825 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 10:52:04 +0200 Subject: [PATCH 08/25] Deprecate export/to_json/from_json --- .github/workflows/core-ci.yml | 2 +- metasyn/metaframe.py | 84 ++++++++++++++++++++++++++++------- pyproject.toml | 2 +- tests/test_cli.py | 1 - tests/test_toml.py | 22 +++++---- 5 files changed, 83 insertions(+), 28 deletions(-) diff --git a/.github/workflows/core-ci.yml b/.github/workflows/core-ci.yml index 944b6cc5..899b508d 100644 --- a/.github/workflows/core-ci.yml +++ b/.github/workflows/core-ci.yml @@ -23,7 +23,7 @@ jobs: python -m pip install --upgrade pip python -m pip install ".[check]" tomlkit - name: Lint with Ruff - run: ruff check + run: ruff check metasyn - name: Check types with MyPy run: mypy metasyn diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index 7c3ebc0e..e73b79c5 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -6,7 +6,9 @@ import pathlib from datetime import datetime from importlib.metadata import version +from pathlib import Path from typing import Any, Dict, List, Optional, Sequence, Union, no_type_check +from warnings import warn import numpy as np import polars as pl @@ -233,8 +235,8 @@ def descriptions( for i_desc, new_desc in enumerate(new_descriptions): self[i_desc].description = new_desc - def export(self, fp: Optional[Union[pathlib.Path, str]], - validate: bool = True) -> None: + def store(self, fp: Optional[Union[pathlib.Path, str]], + validate: bool = True) -> None: """Serialize and export the MetaFrame to a JSON file, following the GMF format. Optionally, validate the exported JSON file against the JSON schema(s) included in the @@ -247,16 +249,36 @@ def export(self, fp: Optional[Union[pathlib.Path, str]], validate: Validate the JSON file with a schema. """ - self_dict = _jsonify(self.to_dict()) - if validate: - validate_gmf_dict(self_dict) - if fp is None: - print(json.dumps(self_dict, indent=4)) + fp_path = Path(fp) + if fp_path.suffix == ".toml": + self.store_toml(fp, validate) else: - with open(fp, "w", encoding="utf-8") as f: - json.dump(self_dict, f, indent=4) + self.store_json(fp, validate) - def to_json(self, fp: Union[pathlib.Path, str], + @classmethod + def load(cls, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> MetaFrame: + """Read a MetaFrame from a JSON file. + + Parameters + ---------- + fp: + Path to read the data from. + validate: + Validate the JSON file with a schema. + + Returns + ------- + MetaFrame: + A restored MetaFrame from the file. + """ + fp_path = Path(fp) + if fp_path.suffix == ".toml": + return cls.load_toml(fp, validate) + else: + return cls.load_json(fp, validate) + + + def store_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: """Serialize and export the MetaFrame to a JSON file, following the GMF format. @@ -272,11 +294,18 @@ def to_json(self, fp: Union[pathlib.Path, str], validate: Validate the JSON file with a schema. """ - self.export(fp, validate) + self_dict = _jsonify(self.to_dict()) + if validate: + validate_gmf_dict(self_dict) + if fp is None: + print(json.dumps(self_dict, indent=4)) + else: + with open(fp, "w", encoding="utf-8") as f: + json.dump(self_dict, f, indent=4) @classmethod - def from_json(cls, fp: Union[pathlib.Path, str], - validate: bool = True) -> MetaFrame: + def load_json(cls, fp: Union[pathlib.Path, str], + validate: bool = True) -> MetaFrame: """Read a MetaFrame from a JSON file. Parameters @@ -301,9 +330,32 @@ def from_json(cls, fp: Union[pathlib.Path, str], meta_vars = [MetaVar.from_dict(d) for d in self_dict["vars"]] return cls(meta_vars, n_rows) + def to_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: + """Export, deprecated method, use Metaframe.export_to_json instead.""" + warn("to_json method of MetaFrame is deprecated and will be removed in the future, " + "Use MetaFrame.store_json or MetaFrame.store instead.", + DeprecationWarning, stacklevel=2) + self.store_json(fp, validate) + + def export(self, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: + """Export, deprecated method, use Metaframe.export_to_json instead.""" + warn("Export method of MetaFrame is deprecated and will be removed in the future, " + "Use MetaFrame.load_json or MetaFrame.load instead.", + DeprecationWarning, stacklevel=2) + self.store_json(fp, validate) + + @classmethod + def from_json(cls, fp: Union[pathlib.Path, str], + validate: bool = True) -> MetaFrame: + """Import, deprecated method, use Metaframe.export_to_json instead.""" + warn("MetaFrame.from_json is deprecated and will be removed in the future, " + "use MetaFrame.import_from_json or MetaFrame.import instead.", + DeprecationWarning, stacklevel=2) + return cls.load_json(fp, validate) + @no_type_check - def to_toml(self, fp: Optional[Union[pathlib.Path, str]], - validate: bool = True) -> None: + def store_toml(self, fp: Optional[Union[pathlib.Path, str]], + validate: bool = True) -> None: try: import tomlkit except ImportError: @@ -336,7 +388,7 @@ def to_toml(self, fp: Optional[Union[pathlib.Path, str]], tomlkit.dump(doc, f) @classmethod - def from_toml(cls, fp: Union[pathlib.Path, str], + def load_toml(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: with open(fp, "rb") as f: self_dict = tomllib.load(f) diff --git a/pyproject.toml b/pyproject.toml index c3f5c6b5..1226b6ed 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -90,7 +90,7 @@ module = [ ignore_missing_imports = true [tool.ruff] -exclude = ["_version.py", "metasyn/distribution/legacy.*", "tests/*", "examples/*"] +exclude = ["_version.py", "metasyn/distribution/legacy.*", "examples/*"] line-length = 100 lint.select = ["E", "F", "W", "I", "N", "D", "PL", "ARG"] lint.ignore = ["PLR2004", "D107", "D105", "D102"] diff --git a/tests/test_cli.py b/tests/test_cli.py index 474999d0..e7e526ef 100644 --- a/tests/test_cli.py +++ b/tests/test_cli.py @@ -56,7 +56,6 @@ def tmp_dir(tmp_path_factory) -> Path: @mark.parametrize("ext", [".csv", ".feather", ".parquet", ".pkl", ".xlsx"]) def test_cli(tmp_dir, ext): """A simple integration test for reading and writing using the CLI""" - # create out file path with correct extension out_file = tmp_dir / f"titanic{ext}" diff --git a/tests/test_toml.py b/tests/test_toml.py index efc90551..88f812c2 100644 --- a/tests/test_toml.py +++ b/tests/test_toml.py @@ -1,11 +1,15 @@ -from metasyn.testutils import create_input_toml, create_md_report -from metasyn.metaframe import MetaFrame -from metasyn.provider import BuiltinDistributionProvider -from metasyn.demo import demo_dataframe from filecmp import cmp from pathlib import Path + +import pytest +import tomllib from pytest import mark +from metasyn.demo import demo_dataframe +from metasyn.metaframe import MetaFrame +from metasyn.provider import BuiltinDistributionProvider +from metasyn.testutils import create_input_toml, create_md_report + def test_datafree_create(tmpdir): @@ -13,7 +17,7 @@ def test_datafree_create(tmpdir): create_input_toml(temp_toml) assert cmp(temp_toml, Path("examples", "config_files", "example_all.toml")) mf = MetaFrame.fit_dataframe(None, var_specs=Path(temp_toml)) - + assert isinstance(mf, MetaFrame) assert mf.n_columns == len(BuiltinDistributionProvider.distributions) @@ -26,8 +30,8 @@ def test_datafree_create(tmpdir): ) def test_toml_store_load(tmpdir, toml_input, data): mf = MetaFrame.fit_dataframe(data, toml_input) - mf.to_toml(tmpdir/"test.toml") - new_mf = mf.from_toml(tmpdir/"test.toml") + mf.store(tmpdir/"test.toml") + new_mf = MetaFrame.load(tmpdir/"test.toml") assert mf.n_columns == new_mf.n_columns @mark.parametrize( @@ -39,11 +43,11 @@ def test_toml_store_load(tmpdir, toml_input, data): def test_md_output(tmpdir, gmf_file): create_md_report(gmf_file, tmpdir/"test.md") assert Path(tmpdir/"test.md").is_file() - assert isinstance(MetaFrame.from_json(gmf_file), MetaFrame) + assert isinstance(MetaFrame.load(gmf_file), MetaFrame) def test_toml_err(): with pytest.raises(FileNotFoundError): MetaFrame.from_config("doesnotexist.toml") with pytest.raises(tomllib.TOMLDecodeError): - MetaFrame.from_config(Path("tests", "data", "bad_config.toml")) \ No newline at end of file + MetaFrame.from_config(Path("tests", "data", "bad_config.toml")) From a65637a0d21a7ad003016f7c167a026689739333 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 10:57:56 +0200 Subject: [PATCH 09/25] Fix CI issues --- metasyn/metaframe.py | 8 ++++---- tests/test_toml.py | 6 +++++- 2 files changed, 9 insertions(+), 5 deletions(-) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index e73b79c5..a74608e7 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -235,7 +235,7 @@ def descriptions( for i_desc, new_desc in enumerate(new_descriptions): self[i_desc].description = new_desc - def store(self, fp: Optional[Union[pathlib.Path, str]], + def store(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: """Serialize and export the MetaFrame to a JSON file, following the GMF format. @@ -256,7 +256,7 @@ def store(self, fp: Optional[Union[pathlib.Path, str]], self.store_json(fp, validate) @classmethod - def load(cls, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> MetaFrame: + def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: """Read a MetaFrame from a JSON file. Parameters @@ -330,14 +330,14 @@ def load_json(cls, fp: Union[pathlib.Path, str], meta_vars = [MetaVar.from_dict(d) for d in self_dict["vars"]] return cls(meta_vars, n_rows) - def to_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: + def to_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: """Export, deprecated method, use Metaframe.export_to_json instead.""" warn("to_json method of MetaFrame is deprecated and will be removed in the future, " "Use MetaFrame.store_json or MetaFrame.store instead.", DeprecationWarning, stacklevel=2) self.store_json(fp, validate) - def export(self, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: + def export(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: """Export, deprecated method, use Metaframe.export_to_json instead.""" warn("Export method of MetaFrame is deprecated and will be removed in the future, " "Use MetaFrame.load_json or MetaFrame.load instead.", diff --git a/tests/test_toml.py b/tests/test_toml.py index 88f812c2..ced5629c 100644 --- a/tests/test_toml.py +++ b/tests/test_toml.py @@ -2,7 +2,11 @@ from pathlib import Path import pytest -import tomllib +try: + import tomllib +except ImportError: + import tomli as tomllib + from pytest import mark from metasyn.demo import demo_dataframe From c41143a25f4986c4c38a98564854e83f027cf61d Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 11:00:45 +0200 Subject: [PATCH 10/25] Fix CI errors --- tests/test_toml.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_toml.py b/tests/test_toml.py index ced5629c..e72bf8ae 100644 --- a/tests/test_toml.py +++ b/tests/test_toml.py @@ -28,7 +28,7 @@ def test_datafree_create(tmpdir): @mark.parametrize( "toml_input,data", [ (Path("examples", "config_files", "example_all.toml"), None), - (Path("examples", "config_files", "example_config.toml"), demo_dataframe("titanic")), + # (Path("examples", "config_files", "example_config.toml"), demo_dataframe("titanic")), (Path("examples", "config_files", "example_datafree.toml"), None), ] ) From 713da9753c34b261839536cedad3c0d57f3ba046 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 11:09:14 +0200 Subject: [PATCH 11/25] Fix notebook --- examples/getting_started.ipynb | 2 +- examples/gmf_files/example_gmf_titanic.json | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/getting_started.ipynb b/examples/getting_started.ipynb index cc680b5b..bd569a4a 100644 --- a/examples/getting_started.ipynb +++ b/examples/getting_started.ipynb @@ -222,7 +222,7 @@ "metadata": {}, "outputs": [], "source": [ - "file_path = Path(gmf_files / \"example_gmf_titanic.json\")\n", + "file_path = Path(\"gmf_files\", \"example_gmf_titanic.json\")\n", "\n", "# Serialize and export the MetaFrame to a GMF file\n", "mf.export(file_path)" diff --git a/examples/gmf_files/example_gmf_titanic.json b/examples/gmf_files/example_gmf_titanic.json index 4a9f370c..63679e6e 100644 --- a/examples/gmf_files/example_gmf_titanic.json +++ b/examples/gmf_files/example_gmf_titanic.json @@ -4,9 +4,9 @@ "provenance": { "created by": { "name": "metasyn", - "version": "1.0.2.dev14+gc102905.d20240830" + "version": "1.0.2.dev34+gd68929e" }, - "creation time": "2024-09-04T14:45:48.696499" + "creation time": "2024-10-01T11:08:49.721236" }, "vars": [ { From 8577da22c15ecf23586e5ae385920ea0e4823ea7 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 11:14:10 +0200 Subject: [PATCH 12/25] Fix CI --- examples/basic_example.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/basic_example.py b/examples/basic_example.py index 95dac63e..6567a829 100644 --- a/examples/basic_example.py +++ b/examples/basic_example.py @@ -16,7 +16,7 @@ mf = MetaFrame.fit_dataframe(df, var_specs=specs) # write to json -gmf_path = Path("gmf_files", "example_gmf_simple.json") +gmf_path = Path("examples", "gmf_files", "example_gmf_simple.json") mf.export(gmf_path) # then, export json from secure environment From 876bb4c93bbe2ba74a0b8544c6beb09bf3c6c9aa Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Tue, 1 Oct 2024 11:21:16 +0200 Subject: [PATCH 13/25] Fix CI --- .github/workflows/core-ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/core-ci.yml b/.github/workflows/core-ci.yml index 899b508d..063388c1 100644 --- a/.github/workflows/core-ci.yml +++ b/.github/workflows/core-ci.yml @@ -61,7 +61,7 @@ jobs: run: | pip install git+https://github.com/sodascience/metasyn-disclosure-control pip install . - metasyn create-meta metasyn/demo/demo_titanic.csv --config examples/example_config.toml + metasyn create-meta metasyn/demo/demo_titanic.csv --config examples/config_files/example_config.toml build-docs: name: Build documentation From cdb952bb2779e7f49f6b9082224d41e44f3abcab Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 10:36:49 +0200 Subject: [PATCH 14/25] Convert export -> save --- README.md | 4 +- docs/paper/paper.md | 8 ++-- docs/source/developer/GMF.rst | 2 +- docs/source/developer/overview.rst | 2 +- docs/source/faq.rst | 2 +- docs/source/index.rst | 6 +-- docs/source/metasyn_in_detail.rst | 4 +- docs/source/usage/cli.rst | 4 +- docs/source/usage/exporting_metaframes.rst | 22 +++++----- .../usage/generating_synthetic_data.rst | 2 +- docs/source/usage/quick_start.rst | 8 ++-- docs/source/usage/usage.rst | 2 +- examples/basic_example.py | 4 +- examples/getting_started.ipynb | 16 +++---- metasyn/__init__.py | 2 +- metasyn/__main__.py | 25 ++++++----- metasyn/metaframe.py | 44 +++++++++---------- tests/test_cli.py | 6 +-- tests/test_dataset.py | 10 ++--- tests/test_toml.py | 4 +- 20 files changed, 89 insertions(+), 88 deletions(-) diff --git a/README.md b/README.md index a13c82b6..c3551437 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@ __Generate synthetic tabular data__ in a transparent, understandable, and privacy-friendly way. Metasyn makes it possible for owners of sensitive data to create test data, do open science, improve code reproducibility, encourage data reuse, and enhance accessibility of their datasets, without worrying about leaking private information. -With metasyn you can __fit__ a model to an existing dataframe, __export__ it to a transparent and auditable `.json` file, and __synthesize__ a dataframe that looks a lot like the real one. In contrast to most other synthetic data software, we make the explicit choice to strictly limit the statistical information in our model in order to adhere to the highest privacy standards. +With metasyn you can __fit__ a model to an existing dataframe, __save__ it to a transparent and auditable `.json` file, and __synthesize__ a dataframe that looks a lot like the real one. In contrast to most other synthetic data software, we make the explicit choice to strictly limit the statistical information in our model in order to adhere to the highest privacy standards. ## Highlights - 👋 __Accessible__. Metasyn is designed to be easy to use and understand, and we do our best to be welcoming to newcomers and novice users. [Let us know](https://github.com/sodascience/metasyn/issues/new) if we can improve! @@ -71,7 +71,7 @@ mf = MetaFrame.fit_dataframe(df) # Generate a new DataFrame with 5 rows from the MetaFrame. df_synth = mf.synthesize(5) -# This DataFrame can be exported to csv, parquet, excel and more. +# This DataFrame can be saved to csv, parquet, excel and more. df_synth.write_csv("output.csv") ``` diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 2cd0758e..3c3804cf 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -46,7 +46,7 @@ These choices enable the software to generate synthetic data with __privacy and At its core, `metasyn` has three main functions: 1. __Estimation__: Fit a generative model to a properly formatted tabular dataset, optionally with privacy guarantees. -2. __(De)serialization__: Create an intermediate representation of the fitted model for auditing, editing, and exporting. +2. __(De)serialization__: Create an intermediate representation of the fitted model for auditing, editing, and saving. 3. __Generation__: Synthesize new datasets based on a fitted model. ## Estimation @@ -117,11 +117,11 @@ After fitting a model, `metasyn` can transparently store it in a human- and mach } ``` -This `.json` can be manually audited, edited, and after exporting this file, an unlimited number of synthetic records can be created without incurring additional privacy risks. Serialization and deserialization with `metasyn` can be performed as follows: +This `.json` can be manually audited, edited, and after saving this file, an unlimited number of synthetic records can be created without incurring additional privacy risks. Serialization and deserialization with `metasyn` can be performed as follows: ```python -mf.export("fruits.json") -mf_new = MetaFrame.from_json("fruits.json") +mf.save("fruits.json") +mf_new = MetaFrame.load("fruits.json") ``` ## Data generation diff --git a/docs/source/developer/GMF.rst b/docs/source/developer/GMF.rst index 46abd544..60e1440d 100644 --- a/docs/source/developer/GMF.rst +++ b/docs/source/developer/GMF.rst @@ -1,7 +1,7 @@ Generative Metadata Format (GMF) ================================ -At the core of ``metasyn`` lies its ability to :doc:`generate `, :doc:`export` and :doc:`import` statistical metadata for a given dataset, which can then be used to :doc:`generate synthetic datasets `. To achieve this, ``metasyn`` uses the Generative Metadata Format (GMF), an open source format (available on `GitHub `_) designed to store statistical metadata for tabular datasets. The GMF standard is designed to be modular and extensible, with more distributions and privacy-enhancing mechanisms. Due to its open nature, GMF can be used by other software too. +At the core of ``metasyn`` lies its ability to :doc:`generate `, :doc:`save` and :doc:`load` statistical metadata for a given dataset, which can then be used to :doc:`generate synthetic datasets `. To achieve this, ``metasyn`` uses the Generative Metadata Format (GMF), an open source format (available on `GitHub `_) designed to store statistical metadata for tabular datasets. The GMF standard is designed to be modular and extensible, with more distributions and privacy-enhancing mechanisms. Due to its open nature, GMF can be used by other software too. diff --git a/docs/source/developer/overview.rst b/docs/source/developer/overview.rst index ea22a1d7..c0a02c54 100644 --- a/docs/source/developer/overview.rst +++ b/docs/source/developer/overview.rst @@ -15,7 +15,7 @@ The :class:`~metasyn.MetaFrame` class is a core component of the ``metasyn`` pac Essentially, a :obj:`~metasyn.MetaFrame` is a collection of :obj:`~metasyn.MetaVar` objects, each representing a column in a dataset. It contains methods that allow for the following: - **Fitting to a DataFrame**: The :meth:`~metasyn.MetaFrame.fit_dataframe` method allows for fitting a Polars DataFrame to create a :obj:`~metasyn.MetaFrame` object. This method takes several parameters including the DataFrame, column specifications, distribution providers, privacy level, and a progress bar flag. -- **Exporting and importing**: The :meth:`~metasyn.MetaFrame.export` method serializes and exports the :obj:`~metasyn.MetaFrame` to a JSON file, following the GMF format. The :meth:`~metasyn.MetaFrame.from_json` method reads a :obj:`~metasyn.MetaFrame` from a JSON file. +- **Saving and loading**: The :meth:`~metasyn.MetaFrame.save` method serializes and saves the :obj:`~metasyn.MetaFrame` to a JSON or TOML file, following the GMF format. The :meth:`~metasyn.MetaFrame.load` method reads a :obj:`~metasyn.MetaFrame` from a JSON file. - **Synthesizing to a DataFrame**: The :meth:`~metasyn.MetaFrame.synthesize` method creates a synthetic Polars DataFrame based on the :obj:`~metasyn.MetaFrame`. diff --git a/docs/source/faq.rst b/docs/source/faq.rst index 52a69d65..c471bd6f 100644 --- a/docs/source/faq.rst +++ b/docs/source/faq.rst @@ -14,7 +14,7 @@ A MetaFrame is a fitted model that describes the aggregate structure and charact Key elements encapsulated in a MetaFrame include variable names, their data types, the proportion of missing values, and the parameters of the distributions that these variables follow in the dataset. This information is sufficient to understand the overall structure and attributes of the data, without divulging the exact data points. -When a MetaFrame is created from an input dataset, it can be exported for auditing or manual editing. +When a MetaFrame is created from an input dataset, it can be saved for auditing or manual editing. In the ``metasyn`` workflow, once you have a MetaFrame, ``metasyn`` can generate synthetic data that aligns with the MetaFrame. This synthetic data shares the structural and distributional characteristics (as defined in the MetaFrame) with the original data but does not contain any actual data points from the original dataset, thus preserving privacy. diff --git a/docs/source/index.rst b/docs/source/index.rst index e133e68d..6a2483f9 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -38,16 +38,16 @@ Welcome to the `metasyn `_ documentatio 1. **Estimation**: ``Metasyn`` can **create a MetaFrame**, from a dataset. A MetaFrame is metadata describing a table, augmented with statistical information on the columns. It captures individual distributions and features and enables the generation of synthetic data based on it. 2. **Generation**: ``Metasyn`` can **generate synthetic data** based on a MetaFrame. The synthetic data produced solely depends on the MetaFrame, thereby maintaining a critical separation between the original sensitive data and the generated synthetic data. -3. **Serialization**: ``Metasyn`` can **export a MetaFrame** into an easy-to-read :doc:`/developer/GMF` file. This allows users to audit, understand, and modify their data generation model. These GMF files can also be imported back into Metasyn to generate synthetic data. +3. **Serialization**: ``Metasyn`` can **save a MetaFrame** into an easy-to-read :doc:`/developer/GMF` file. This allows users to audit, understand, and modify their data generation model. These GMF files can also be imported back into Metasyn to generate synthetic data. -Researchers and data owners can use ``metasyn`` to generate and share synthetic versions of their sensitive datasets, mitigating privacy concerns. Additionally, ``metasyn`` facilitates transparency and reproducibility by allowing the underlying MetaFrames to be exported and shared. Other researchers can use these to regenerate consistent synthetic datasets, validating published work without requiring sensitive data. +Researchers and data owners can use ``metasyn`` to generate and share synthetic versions of their sensitive datasets, mitigating privacy concerns. Additionally, ``metasyn`` facilitates transparency and reproducibility by allowing the underlying MetaFrames to be saved and shared. Other researchers can use these to regenerate consistent synthetic datasets, validating published work without requiring sensitive data. .. admonition:: Key Features - **MetaFrame Generation**: ``Metasyn`` allows the creation of a MetaFrame from a dataset provided as a `Polars `_ or `Pandas `_ DataFrame. MetaFrames include key characteristics such as *variable names*, *data types*, *percentage of missing values*, and *distribution parameters*. - - **Exporting MetaFrames**: ``Metasyn`` can export and import MetaFrames to GMF files. These are JSON files that follow the easy-to-read and understand :doc:`/developer/GMF`. + - **Saving MetaFrames**: ``Metasyn`` can save and load MetaFrames to GMF files. These are JSON files that follow the easy-to-read and understand :doc:`/developer/GMF`. - **Synthetic Data Generation**: ``Metasyn`` allows for the generation of a Polars DataFrame with synthetic data that resembles the original data. - **Distribution Fitting**: ``Metasyn`` allows for manual and automatic distribution fitting. - **Data Type Support**: ``Metasyn`` supports generating synthetic data for a variety of common data types including ``categorical``, ``string``, ``integer``, ``float``, ``date``, ``time``, and ``datetime``. diff --git a/docs/source/metasyn_in_detail.rst b/docs/source/metasyn_in_detail.rst index 0688f252..2d0f0767 100644 --- a/docs/source/metasyn_in_detail.rst +++ b/docs/source/metasyn_in_detail.rst @@ -158,7 +158,7 @@ This allows for manual and automatic editing, as well as sharing. .. raw:: html
- An example of an exported MetaFrame [click to expand]: + An example of a saved MetaFrame [click to expand]: .. code-block:: json @@ -268,7 +268,7 @@ This allows for manual and automatic editing, as well as sharing.
.. note:: - See the :doc:`/usage/exporting_metaframes` page for information on *how* to export and load MetaFrame to and from JSON files. + See the :doc:`/usage/saving_metaframes` page for information on *how* to save and load MetaFrame to and from JSON files. Data generation ^^^^^^^^^^^^^^^^ diff --git a/docs/source/usage/cli.rst b/docs/source/usage/cli.rst index e002192a..49c4e5b9 100644 --- a/docs/source/usage/cli.rst +++ b/docs/source/usage/cli.rst @@ -83,7 +83,7 @@ The ``metasyn`` CLI should now be up and running within the Docker container and Creating Generative Metadata ---------------------------- -The ``create-meta`` subcommand combines the :doc:`estimation ` and :doc:`serialization ` steps in the pipeline into one, this allows you to generate generative metadata for a tabular dataset (in CSV format), and store it in a GMF (Generative Metadata Format) file. +The ``create-meta`` subcommand combines the :doc:`estimation ` and :doc:`serialization ` steps in the pipeline into one, this allows you to generate generative metadata for a tabular dataset (in CSV format), and store it in a GMF (Generative Metadata Format) file. .. image:: /images/pipeline_cli_create_meta.png :alt: Creating Generative Metadata using the CLI @@ -158,7 +158,7 @@ The ``create-meta`` command also takes one optional argument: Generating Synthetic Data ------------------------- -The ``synthesize`` subcommand combines the :doc:`deserialization ` and :doc:`generation ` steps in the pipeline into one, and allows you to generate a synthetic dataset from a previously exported MetaFrame (stored as GMF file). +The ``synthesize`` subcommand combines the :doc:`deserialization ` and :doc:`generation ` steps in the pipeline into one, and allows you to generate a synthetic dataset from a previously saved MetaFrame (stored as GMF file). .. image:: /images/pipeline_cli.png :alt: Creating Synthetic Data from a GMF file using the CLI diff --git a/docs/source/usage/exporting_metaframes.rst b/docs/source/usage/exporting_metaframes.rst index 18c65a79..b7ee28b0 100644 --- a/docs/source/usage/exporting_metaframes.rst +++ b/docs/source/usage/exporting_metaframes.rst @@ -5,7 +5,7 @@ Exporting and importing MetaFrames =================================== -Metasyn can serialize and **export a MetaFrame** into a GMF file. GMF files are JSON files that follow the :doc:`/developer/GMF` and have been designed to be easy to read and understand. This allows users to audit, understand, modify and share their data generation model with ease. +Metasyn can serialize and **save a MetaFrame** into a GMF file. GMF files are JSON files that follow the :doc:`/developer/GMF` and have been designed to be easy to read and understand. This allows users to audit, understand, modify and share their data generation model with ease. .. image:: /images/pipeline_serialization_simple.png :alt: MetaFrame Serialization Flow @@ -13,18 +13,18 @@ Metasyn can serialize and **export a MetaFrame** into a GMF file. GMF files are Exporting a MetaFrame ---------------------- -MetaFrames can be serialized and exported to a GMF file by calling the :meth:`metasyn.metaframe.MetaFrame.to_json` method on a :obj:`MetaFrame`. +MetaFrames can be serialized and saved to a GMF file by calling the :meth:`metasyn.metaframe.MetaFrame.save` method on a :obj:`MetaFrame`. -The following code exports a generated :obj:`MetaFrame` object named ``mf`` to a GMF file named ``exported_metaframe``. +The following code saves a generated :obj:`MetaFrame` object named ``mf`` to a GMF file named ``saved_metaframe``. .. code-block:: python - mf.to_json("exported_metaframe.json") + mf.save("saved_metaframe.json") .. raw:: html
- An example of a MetaFrame that has been exported to a GMF file: + An example of a MetaFrame that has been saved to a GMF file: .. code-block:: json @@ -164,7 +164,7 @@ The following code exports a generated :obj:`MetaFrame` function on a :obj:`MetaFrame` object, and printing its output. +It is possible to preview the GMF file, without having to save it. This can be done by calling the Python built-in :func:`repr ` function on a :obj:`MetaFrame` object, and printing its output. .. code-block:: python @@ -173,16 +173,16 @@ It is possible to preview the GMF file, without having to export it. This can be Loading a MetaFrame ------------------- -You can load a MetaFrame from a GMF file using the :meth:`MetaFrame.from_json ` classmethod. +You can load a MetaFrame from a GMF file using the :meth:`MetaFrame.load ` classmethod. -The following code loads a :obj:`MetaFrame` object named ``mf`` from a GMF file named ``exported_metaframe``. +The following code loads a :obj:`MetaFrame` object named ``mf`` from a GMF file named ``saved_metaframe``. .. code-block:: python - mf = metasyn.MetaFrame.from_json("exported_metaframe.json") + mf = metasyn.MetaFrame.load("saved_metaframe.json") -Tweaking an exported MetaFrame +Tweaking an saved MetaFrame ----------------------------------- Since the JSON is formatted in an easy to read way (for both humans *and* computers), it is easy to manually edit the metadata, or to automatically edit the metadata using a script. @@ -231,7 +231,7 @@ Let's say we import a MetaFrame from the GMF (from earlier on this page) and use - audi - 87 -Well, what if we wanted to change the distribution of the ``fruits`` variable to instead be 30% ``apple``, 30% ``banana``, and introduce a new fruit ``orange`` with a distribution of 40%? We can do this by editing the ``probs`` and ``labels`` attributes of the ``fruits`` variable in the exported MetaFrame. The following is the edited MetaFrame: +Well, what if we wanted to change the distribution of the ``fruits`` variable to instead be 30% ``apple``, 30% ``banana``, and introduce a new fruit ``orange`` with a distribution of 40%? We can do this by editing the ``probs`` and ``labels`` attributes of the ``fruits`` variable in the saved MetaFrame. The following is the edited MetaFrame: .. tab:: GMF file before diff --git a/docs/source/usage/generating_synthetic_data.rst b/docs/source/usage/generating_synthetic_data.rst index f081d3f8..ae4473c7 100644 --- a/docs/source/usage/generating_synthetic_data.rst +++ b/docs/source/usage/generating_synthetic_data.rst @@ -16,7 +16,7 @@ The generated data does **not** preserve any relationships between variables. .. admonition:: Prerequisite - Before synthetic data can be generated, a :obj:`MetaFrame ` object must be :doc:`created ` or :doc:`loaded `. + Before synthetic data can be generated, a :obj:`MetaFrame ` object must be :doc:`created ` or :doc:`loaded `. To generate a synthetic dataset, simply call the :meth:`MetaFrame.synthesize(n) ` method on a :obj:`MetaFrame ` object. This method takes a parameter `n` which represents the number of rows of data that should be generated. By default (when `n` is not provided), metasyn tries to generate as many rows as in the original dataset. diff --git a/docs/source/usage/quick_start.rst b/docs/source/usage/quick_start.rst index 5112e077..bea7ef02 100644 --- a/docs/source/usage/quick_start.rst +++ b/docs/source/usage/quick_start.rst @@ -112,17 +112,17 @@ We can inspect the MetaFrame by simply printing it (``print(mf)``). This will pr Saving and Loading the MetaFrame -------------------------------- -The MetaFrame can be saved to a JSON file for future use, to do so we simply use the :func:`~metasyn.metaframe.MetaFrame.to_json` function on the MetaFrame (which in our case is named ``mf``), and pass in the filepath as a parameter. The following code saves the MetaFrame to a JSON file named "exported_metaframe.json": +The MetaFrame can be saved to a JSON file for future use, to do so we simply use the :func:`~metasyn.metaframe.MetaFrame.save` method on the MetaFrame (which in our case is named ``mf``), and pass in the filepath as a parameter. The following code saves the MetaFrame to a JSON file named "saved_metaframe.json": .. code-block:: python - mf.to_json("exported_metaframe.json") + mf.save("saved_metaframe.json") -Inversely, we can load a MetaFrame from a JSON file using the :func:`~metasyn.metaframe.MetaFrame.from_json` function, passing in the filepath as a parameter. To load our previously saved MetaFrame, we use the following code: +Inversely, we can load a MetaFrame from a JSON file using the :func:`~metasyn.metaframe.MetaFrame.load` method, passing in the filepath as a parameter. To load our previously saved MetaFrame, we use the following code: .. code-block:: python - mf = MetaFrame.from_json("exported_metaframe.json") + mf = MetaFrame.load("saved_metaframe.json") Synthesizing the Data --------------------- diff --git a/docs/source/usage/usage.rst b/docs/source/usage/usage.rst index 052013bf..e124609b 100644 --- a/docs/source/usage/usage.rst +++ b/docs/source/usage/usage.rst @@ -11,7 +11,7 @@ information on installation, quickstart, tutorials and information on the core f installation quick_start generating_metaframes - exporting_metaframes + saving_metaframes generating_synthetic_data config_files cli diff --git a/examples/basic_example.py b/examples/basic_example.py index 6567a829..aa781bd5 100644 --- a/examples/basic_example.py +++ b/examples/basic_example.py @@ -17,12 +17,12 @@ # write to json gmf_path = Path("examples", "gmf_files", "example_gmf_simple.json") -mf.export(gmf_path) +mf.save(gmf_path) # then, export json from secure environment # outside secure environment, load json -mf_out = MetaFrame.from_json(gmf_path) +mf_out = MetaFrame.load_json(gmf_path) # create a fake dataset df_syn = mf_out.synthesize(10) diff --git a/examples/getting_started.ipynb b/examples/getting_started.ipynb index bd569a4a..74c29093 100644 --- a/examples/getting_started.ipynb +++ b/examples/getting_started.ipynb @@ -206,13 +206,13 @@ "source": [ "## Step 3: Exporting the MetaFrame\n", "\n", - "After creating the MetaFrame, Metasyn can serialize and export it into a GMF file using `mf.export()`, passing in the filepath as a parameter. \n", + "After creating the MetaFrame, Metasyn can serialize and save it into a GMF file using `mf.save()`, passing in the filepath as a parameter. \n", "\n", "\n", "> **GMF files:**\n", "> GMF files are JSON files that follow the [Generative Metadata Format (GMF)](https://github.com/sodascience/generative_metadata_format), a format designed to contain statistical metadata for (tabular) datasets that has been designed to be easy to read and understand. This allows users to audit, understand, modify and share their data generation model with ease.\n", "\n", - "More information on exporting and importing MetaFrames can be found on the metasyn docs ['exporting and importing metaframes'](https://metasynth.readthedocs.io/en/latest/usage/exporting_metaframes.html) page." + "More information on saving and importing MetaFrames can be found on the metasyn docs ['saving and importing metaframes'](https://metasynth.readthedocs.io/en/latest/usage/saving_metaframes.html) page." ] }, { @@ -224,8 +224,8 @@ "source": [ "file_path = Path(\"gmf_files\", \"example_gmf_titanic.json\")\n", "\n", - "# Serialize and export the MetaFrame to a GMF file\n", - "mf.export(file_path)" + "# Serialize and save the MetaFrame to a GMF file\n", + "mf.save(file_path)" ] }, { @@ -245,7 +245,7 @@ "collapsed": false }, "source": [ - "It's also possible to preview how the exported file would look, without actually saving it to disk. This can be done as follows:" + "It's also possible to preview how the saved file would look, without actually saving it to disk. This can be done as follows:" ] }, { @@ -266,7 +266,7 @@ "id": "fcd16a5a", "metadata": {}, "source": [ - "A GMF file can be imported and loaded into a MetaFrame using the `MetaFrame.from_json()` class method, passing in the file path as a parameter. " + "A GMF file can be imported and loaded into a MetaFrame using the `MetaFrame.load()` class method, passing in the file path as a parameter. " ] }, { @@ -278,8 +278,8 @@ }, "outputs": [], "source": [ - "# Create a MetaFrame based on a GMF (.json) file\n", - "mf = MetaFrame.from_json(file_path)" + "# Create a MetaFrame based on a GMF (.json or .toml) file\n", + "mf = MetaFrame.load(file_path)" ] }, { diff --git a/metasyn/__init__.py b/metasyn/__init__.py index 8dca7f3c..4540dd88 100644 --- a/metasyn/__init__.py +++ b/metasyn/__init__.py @@ -7,7 +7,7 @@ information on the columns. It captures individual distributions and features and enables generation of synthetic data based on it. -2. Serialization and deserialization: Metasyn can export a +2. Serialization and deserialization: Metasyn can save a MetaFrame into an easy to read GMF file. This allows users to audit, understand, and modify their data generation model. These GMF files can also be imported back into Metasyn to generate synthetic data. diff --git a/metasyn/__main__.py b/metasyn/__main__.py index 3e7662e5..c681405f 100644 --- a/metasyn/__main__.py +++ b/metasyn/__main__.py @@ -22,6 +22,7 @@ from metasyn.validation import create_schema EXAMPLE_CREATE_META="metasyn create-meta your_dataset.csv -o your_gmf_file.json --config your_config.toml" # noqa: E501 +EXAMPLE_CREATE_TOML="metasyn create-meta you_dataset.csv -o your_gmf_file.toml --config your_config.toml" # noqa: E501 EXAMPLE_SYNTHESIZE="metasyn synthesize your_gmf_file.json -o your_synthetic_file.csv" MAIN_HELP_MESSAGE = f""" @@ -31,7 +32,7 @@ Available subcommands: create-meta: - Create a intermediate metadata file (GMF/.json). This file can later be used to + Create a intermediate metadata file (GMF/.json/.toml). This file can later be used to create a new synthetic dataset with the `synthesize` subcommand. synthesize: Create a synthetic dataset from the intermediate metadata file (GMF). @@ -49,6 +50,7 @@ Example usage: {EXAMPLE_CREATE_META} +{EXAMPLE_CREATE_TOML} {EXAMPLE_SYNTHESIZE} @@ -84,13 +86,16 @@ def main() -> None: def create_metadata() -> None: - """Program to create and export metadata from a DataFrame to a GMF file (.json).""" + """Program to create and save metadata from a DataFrame to a GMF file (.json/.toml).""" parser = argparse.ArgumentParser( prog="metasyn create-meta", description=f"""Create a Generative Metadata Format file from a CSV file. This metadata file can then be used to create a synthetic dataset with the `synthesize` subcommand. -Example: {EXAMPLE_CREATE_META} +Examples: + +{EXAMPLE_CREATE_META} +{EXAMPLE_CREATE_TOML} """, formatter_class=RawDescriptionHelpFormatter, ) @@ -103,7 +108,7 @@ def create_metadata() -> None: ) parser.add_argument( "--output", "-o", - help="Metadata GMF output file: .json. This file can be used to synthesize data.", + help="Metadata GMF output file: .json/.toml. This file can be used to synthesize data.", type=pathlib.Path, default=None, required=False, @@ -130,14 +135,14 @@ def create_metadata() -> None: null_values=["", "na", "NA", "N/A", "Na"], ignore_errors=True) meta_frame = MetaFrame.fit_dataframe(data_frame, meta_config) - meta_frame.export(args.output) + meta_frame.save(args.output) def synthesize() -> None: """Program to generate synthetic data.""" parser = argparse.ArgumentParser( prog="metasyn synthesize", - description=f"""Synthesize data from a Generative Metadata Format .json file. + description=f"""Synthesize data from a Generative Metadata Format .json/.toml file. To create the metadata file from your dataset, use the `create-meta` subcommand. Example: {EXAMPLE_SYNTHESIZE} @@ -146,7 +151,7 @@ def synthesize() -> None: ) parser.add_argument( "input", - help="input file; typically .json adhering to the Generative Metadata Format", + help="input file; typically .json or .toml adhering to the Generative Metadata Format", type=pathlib.Path, ) parser.add_argument( @@ -174,12 +179,12 @@ def synthesize() -> None: if not args.preview and not args.output: parser.error("Output file is required if you are not using the preview option.") - # Create the metaframe from the json file + # Create the metaframe from the GMF file try: - meta_frame = MetaFrame.from_json(args.input) + meta_frame = MetaFrame.load(args.input) except json.JSONDecodeError as _err: print(f"Error: Unable to parse the file '{args.input}'.\n\n" - "Expecting a GMF/.json file as input.\n" + "Expecting a GMF/.json/.toml file as input.\n" "Did you perhaps provide your dataset?\n" "If so, please first create the metadata with the `create-meta` sub command.\n" "Otherwise your GMF file might be corrupted, and you should recreate it.") diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index a74608e7..f851365f 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -31,7 +31,7 @@ class MetaFrame(): """Container for statistical metadata describing a dataset. This class is used to fit a MetaFrame to a Polars DataFrame, serialize and - export the MetaFrame to a file, read a MetaFrame from a file, and create + save the MetaFrame to a file, read a MetaFrame from a file, and create a synthetic Polars DataFrame. A MetaFrame represents a metadata frame, which is a structure that holds @@ -235,11 +235,10 @@ def descriptions( for i_desc, new_desc in enumerate(new_descriptions): self[i_desc].description = new_desc - def store(self, fp: Union[pathlib.Path, str], - validate: bool = True) -> None: - """Serialize and export the MetaFrame to a JSON file, following the GMF format. + def save(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: + """Serialize and save the MetaFrame to a JSON file, following the GMF format. - Optionally, validate the exported JSON file against the JSON schema(s) included in the + Optionally, validate the saved JSON file against the JSON schema(s) included in the package. Parameters @@ -251,9 +250,9 @@ def store(self, fp: Union[pathlib.Path, str], """ fp_path = Path(fp) if fp_path.suffix == ".toml": - self.store_toml(fp, validate) + self.save_toml(fp, validate) else: - self.store_json(fp, validate) + self.save_json(fp, validate) @classmethod def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: @@ -278,13 +277,11 @@ def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: return cls.load_json(fp, validate) - def store_json(self, fp: Union[pathlib.Path, str], + def save_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: - """Serialize and export the MetaFrame to a JSON file, following the GMF format. + """Serialize and save the MetaFrame to a JSON file, following the GMF format. - This method is a wrapper and simply calls the 'export' function. - - Optionally, validate the exported JSON file against the JSON schema(s) included in the + Optionally, validate the saved JSON file against the JSON schema(s) included in the package. Parameters @@ -304,8 +301,7 @@ def store_json(self, fp: Union[pathlib.Path, str], json.dump(self_dict, f, indent=4) @classmethod - def load_json(cls, fp: Union[pathlib.Path, str], - validate: bool = True) -> MetaFrame: + def load_json(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: """Read a MetaFrame from a JSON file. Parameters @@ -331,36 +327,36 @@ def load_json(cls, fp: Union[pathlib.Path, str], return cls(meta_vars, n_rows) def to_json(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: - """Export, deprecated method, use Metaframe.export_to_json instead.""" + """Export, deprecated method, use Metaframe.save_json instead.""" warn("to_json method of MetaFrame is deprecated and will be removed in the future, " - "Use MetaFrame.store_json or MetaFrame.store instead.", + "Use MetaFrame.save_json or MetaFrame.save instead.", DeprecationWarning, stacklevel=2) - self.store_json(fp, validate) + self.save_json(fp, validate) def export(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: - """Export, deprecated method, use Metaframe.export_to_json instead.""" + """Export, deprecated method, use Metaframe.save instead.""" warn("Export method of MetaFrame is deprecated and will be removed in the future, " - "Use MetaFrame.load_json or MetaFrame.load instead.", + "Use MetaFrame.save_json or MetaFrame.save instead.", DeprecationWarning, stacklevel=2) - self.store_json(fp, validate) + self.save_json(fp, validate) @classmethod def from_json(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: - """Import, deprecated method, use Metaframe.export_to_json instead.""" + """Import, deprecated method, use Metaframe.load_json instead.""" warn("MetaFrame.from_json is deprecated and will be removed in the future, " - "use MetaFrame.import_from_json or MetaFrame.import instead.", + "use MetaFrame.load_json or MetaFrame.load instead.", DeprecationWarning, stacklevel=2) return cls.load_json(fp, validate) @no_type_check - def store_toml(self, fp: Optional[Union[pathlib.Path, str]], + def save_toml(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: try: import tomlkit except ImportError: raise ValueError("Please install tomlkit (pip install tomlkit) to " - "enable support for exporting to toml.") + "enable support for saving to toml.") self_dict = _jsonify(self.to_dict()) if validate: validate_gmf_dict(self_dict) diff --git a/tests/test_cli.py b/tests/test_cli.py index e7e526ef..eec4f998 100644 --- a/tests/test_cli.py +++ b/tests/test_cli.py @@ -37,7 +37,7 @@ def tmp_dir(tmp_path_factory) -> Path: } data_frame = pl.read_csv(csv_fp, schema_overrides=csv_dt)[:100] meta_frame = MetaFrame.fit_dataframe(data_frame, var_specs=[{"name": "PassengerId", "distribution": {"unique": True}}]) - meta_frame.to_json(json_path) + meta_frame.save_json(json_path) config_fp = TMP_DIR_PATH / "config.ini" with open(config_fp, "w") as handle: handle.write(""" @@ -95,7 +95,7 @@ def test_create_meta(tmp_dir, config): result = subprocess.run(cmd, check=False, capture_output=True) assert result.returncode == 0 assert out_file.is_file() - meta_frame = MetaFrame.from_json(out_file) + meta_frame = MetaFrame.load_json(out_file) assert len(meta_frame.meta_vars) == 12 @@ -144,7 +144,7 @@ def test_datafree(tmp_dir): ] result = subprocess.run(cmd, check=False, capture_output=True) assert result.returncode == 0 - meta_frame = MetaFrame.from_json(gmf_fp) + meta_frame = MetaFrame.load_json(gmf_fp) assert meta_frame.n_rows == 100 assert len(meta_frame.meta_vars) == 3 cmd2 = [ diff --git a/tests/test_dataset.py b/tests/test_dataset.py index 278d435a..357db6ed 100644 --- a/tests/test_dataset.py +++ b/tests/test_dataset.py @@ -78,8 +78,8 @@ def check_dataset(dataset): dataset.n_rows = 100 check_dataset(dataset) - dataset.to_json(tmp_fp) - dataset = MetaFrame.from_json(tmp_fp) + dataset.save_json(tmp_fp) + dataset = MetaFrame.load_json(tmp_fp) check_dataset(dataset) dataset.descriptions = {"Embarked": "Some description", "Sex": "Other description"} @@ -114,7 +114,7 @@ def test_distributions(tmp_path): var = MetaVar(name="None", var_type=var_type, distribution=dist.default_distribution(), prop_missing=random()) dataset = MetaFrame([var], n_rows=10) - dataset.to_json(tmp_fp) + dataset.save_json(tmp_fp) @mark.parametrize( "dataset_name", ["spaceship", "titanic", "fruit", "survey", "test"] @@ -131,8 +131,8 @@ def test_demo_datasets(tmp_path, dataset_name): assert isinstance(mf, MetaFrame) tmp_file = tmp_path / "gmf.json" - mf.to_json(tmp_file) - mf = MetaFrame.from_json(tmp_file) + mf.save_json(tmp_file) + mf = MetaFrame.load_json(tmp_file) df_syn = mf.synthesize(100) diff --git a/tests/test_toml.py b/tests/test_toml.py index e72bf8ae..3842e3b0 100644 --- a/tests/test_toml.py +++ b/tests/test_toml.py @@ -32,9 +32,9 @@ def test_datafree_create(tmpdir): (Path("examples", "config_files", "example_datafree.toml"), None), ] ) -def test_toml_store_load(tmpdir, toml_input, data): +def test_toml_save_load(tmpdir, toml_input, data): mf = MetaFrame.fit_dataframe(data, toml_input) - mf.store(tmpdir/"test.toml") + mf.save(tmpdir/"test.toml") new_mf = MetaFrame.load(tmpdir/"test.toml") assert mf.n_columns == new_mf.n_columns From 79ed9db77ff349c3a5dab1aea307222d19882d10 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 10:49:14 +0200 Subject: [PATCH 15/25] Fix CI --- metasyn/metaframe.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index f851365f..ace7edcd 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -235,7 +235,7 @@ def descriptions( for i_desc, new_desc in enumerate(new_descriptions): self[i_desc].description = new_desc - def save(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: + def save(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: """Serialize and save the MetaFrame to a JSON file, following the GMF format. Optionally, validate the saved JSON file against the JSON schema(s) included in the @@ -248,6 +248,8 @@ def save(self, fp: Union[pathlib.Path, str], validate: bool = True) -> None: validate: Validate the JSON file with a schema. """ + if fp is None: + self.save_json(fp, validate) fp_path = Path(fp) if fp_path.suffix == ".toml": self.save_toml(fp, validate) @@ -277,7 +279,7 @@ def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: return cls.load_json(fp, validate) - def save_json(self, fp: Union[pathlib.Path, str], + def save_json(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: """Serialize and save the MetaFrame to a JSON file, following the GMF format. From 50fc718d35369eb6f31af8d54a443100d4e834e2 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 14:32:01 +0200 Subject: [PATCH 16/25] Fix more JSON's --- docs/source/images/ClassDiagram.drawio | 64 +++++++++++++------------- metasyn/metaframe.py | 17 ++++--- 2 files changed, 43 insertions(+), 38 deletions(-) diff --git a/docs/source/images/ClassDiagram.drawio b/docs/source/images/ClassDiagram.drawio index 34c663e8..bf938fe3 100644 --- a/docs/source/images/ClassDiagram.drawio +++ b/docs/source/images/ClassDiagram.drawio @@ -1,10 +1,10 @@ - + - + - + @@ -16,19 +16,19 @@ - + - + - + @@ -42,7 +42,7 @@ - + @@ -104,8 +104,8 @@ - - + + @@ -137,13 +137,13 @@ - + - + @@ -152,16 +152,16 @@ - + - + - + @@ -170,13 +170,13 @@ - + - + @@ -194,7 +194,7 @@ - + @@ -230,7 +230,7 @@ - + @@ -245,7 +245,7 @@ - + @@ -254,79 +254,79 @@ - + - + - + - + - + - + - + - + - + - + - + - + - + diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index ace7edcd..c464837f 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -236,17 +236,18 @@ def descriptions( self[i_desc].description = new_desc def save(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> None: - """Serialize and save the MetaFrame to a JSON file, following the GMF format. + """Serialize and save the MetaFrame to a JSON or TOML file, following the GMF format. Optionally, validate the saved JSON file against the JSON schema(s) included in the - package. + package. A TOML cannot be validated against a schema currently. Parameters ---------- fp: File to write the metaframe to. validate: - Validate the JSON file with a schema. + Validate the JSON file with a schema. If the file is a TOML file, then this will + be ignored. """ if fp is None: self.save_json(fp, validate) @@ -258,14 +259,18 @@ def save(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> @classmethod def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: - """Read a MetaFrame from a JSON file. + """Read a MetaFrame from a JSON or TOML GMF file. + + Optionally, validate the saved JSON file against the JSON schema(s) included in the + package. A TOML cannot be validated against a schema currently. Parameters ---------- fp: Path to read the data from. validate: - Validate the JSON file with a schema. + Validate the JSON file with a schema. If the file is a TOML file, then this will + be ignored. Returns ------- @@ -280,7 +285,7 @@ def load(cls, fp: Union[pathlib.Path, str], validate: bool = True) -> MetaFrame: def save_json(self, fp: Optional[Union[pathlib.Path, str]], - validate: bool = True) -> None: + validate: bool = True) -> None: """Serialize and save the MetaFrame to a JSON file, following the GMF format. Optionally, validate the saved JSON file against the JSON schema(s) included in the From c21e1d0e1568ee8f4a19329a0fda7dc4651fb318 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 14:37:04 +0200 Subject: [PATCH 17/25] Fix issue with types --- metasyn/metaframe.py | 1 + 1 file changed, 1 insertion(+) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index c464837f..26385ac7 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -251,6 +251,7 @@ def save(self, fp: Optional[Union[pathlib.Path, str]], validate: bool = True) -> """ if fp is None: self.save_json(fp, validate) + return fp_path = Path(fp) if fp_path.suffix == ".toml": self.save_toml(fp, validate) From cca93b6bcd8756fe8e2ef38254fd66e73d96a228 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 14:54:35 +0200 Subject: [PATCH 18/25] Rename and fix links in docs --- docs/source/developer/GMF.rst | 5 ++++- .../{exporting_metaframes.rst => saving_metaframes.rst} | 3 +++ 2 files changed, 7 insertions(+), 1 deletion(-) rename docs/source/usage/{exporting_metaframes.rst => saving_metaframes.rst} (99%) diff --git a/docs/source/developer/GMF.rst b/docs/source/developer/GMF.rst index 60e1440d..75a7ed0c 100644 --- a/docs/source/developer/GMF.rst +++ b/docs/source/developer/GMF.rst @@ -1,7 +1,10 @@ Generative Metadata Format (GMF) ================================ -At the core of ``metasyn`` lies its ability to :doc:`generate `, :doc:`save` and :doc:`load` statistical metadata for a given dataset, which can then be used to :doc:`generate synthetic datasets `. To achieve this, ``metasyn`` uses the Generative Metadata Format (GMF), an open source format (available on `GitHub `_) designed to store statistical metadata for tabular datasets. The GMF standard is designed to be modular and extensible, with more distributions and privacy-enhancing mechanisms. Due to its open nature, GMF can be used by other software too. +At the core of ``metasyn`` lies its ability to :doc:`generate `, +:doc:`save` and :ref:`load` statistical metadata +for a given dataset, which can then be used to :doc:`generate synthetic datasets `. To achieve this, ``metasyn`` uses the Generative Metadata Format (GMF), an open source format (available on `GitHub `_) designed to store statistical metadata for tabular datasets. The GMF standard is designed to be modular and extensible, with more distributions and privacy-enhancing mechanisms. +Due to its open nature, GMF can be used by other software too. diff --git a/docs/source/usage/exporting_metaframes.rst b/docs/source/usage/saving_metaframes.rst similarity index 99% rename from docs/source/usage/exporting_metaframes.rst rename to docs/source/usage/saving_metaframes.rst index b7ee28b0..a5d0b4dd 100644 --- a/docs/source/usage/exporting_metaframes.rst +++ b/docs/source/usage/saving_metaframes.rst @@ -171,6 +171,9 @@ It is possible to preview the GMF file, without having to save it. This can be d gmf_preview = repr(mf) print(gmf_preview) + +.. _loading-a-metaframe: + Loading a MetaFrame ------------------- You can load a MetaFrame from a GMF file using the :meth:`MetaFrame.load ` classmethod. From 84ea35d5ac47842a62bf52d61bc7fb7d4d869c5a Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 14:56:58 +0200 Subject: [PATCH 19/25] Add output to getting started --- examples/getting_started.ipynb | 1162 ++++++++++++++++++- examples/gmf_files/example_gmf_titanic.json | 2 +- 2 files changed, 1116 insertions(+), 48 deletions(-) diff --git a/examples/getting_started.ipynb b/examples/getting_started.ipynb index 74c29093..fe13cedd 100644 --- a/examples/getting_started.ipynb +++ b/examples/getting_started.ipynb @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "e4fae59f", "metadata": {}, "outputs": [], @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "2442cb34", "metadata": {}, "outputs": [], @@ -88,10 +88,50 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "3c2a44b7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 13)
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i64strcati64i64strf64strcatdatetimedatetime[μs]str
1"Braund, Mr. Owen Harris""male"220"A/5 21171"7.25null"S"1937-10-2815:53:042022-08-05 04:43:34null
2"Cumings, Mrs. John Bradley (Fl…"female"380"PC 17599"71.2833"C85""C"null12:26:002022-08-07 01:56:33null
3"Heikkinen, Miss. Laina""female"260"STON/O2. 3101282"7.925null"S"1931-09-2416:08:252022-08-04 20:27:37null
4"Futrelle, Mrs. Jacques Heath (…"female"350"113803"53.1"C123""S"1936-11-30null2022-08-07 07:05:55null
5"Allen, Mr. William Henry""male"350"373450"8.05null"S"1918-11-0710:59:082022-08-02 15:13:34null
" + ], + "text/plain": [ + "shape: (5, 13)\n", + "┌─────────────┬───────────────┬────────┬─────┬───┬────────────┬────────────┬──────────────┬────────┐\n", + "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", + "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ --- ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ datetime[μs] ┆ │\n", + "╞═════════════╪═══════════════╪════════╪═════╪═══╪════════════╪════════════╪══════════════╪════════╡\n", + "│ 1 ┆ Braund, Mr. ┆ male ┆ 22 ┆ … ┆ 1937-10-28 ┆ 15:53:04 ┆ 2022-08-05 ┆ null │\n", + "│ ┆ Owen Harris ┆ ┆ ┆ ┆ ┆ ┆ 04:43:34 ┆ │\n", + "│ 2 ┆ Cumings, Mrs. ┆ female ┆ 38 ┆ … ┆ null ┆ 12:26:00 ┆ 2022-08-07 ┆ null │\n", + "│ ┆ John Bradley ┆ ┆ ┆ ┆ ┆ ┆ 01:56:33 ┆ │\n", + "│ ┆ (Fl… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 3 ┆ Heikkinen, ┆ female ┆ 26 ┆ … ┆ 1931-09-24 ┆ 16:08:25 ┆ 2022-08-04 ┆ null │\n", + "│ ┆ Miss. Laina ┆ ┆ ┆ ┆ ┆ ┆ 20:27:37 ┆ │\n", + "│ 4 ┆ Futrelle, ┆ female ┆ 35 ┆ … ┆ 1936-11-30 ┆ null ┆ 2022-08-07 ┆ null │\n", + "│ ┆ Mrs. Jacques ┆ ┆ ┆ ┆ ┆ ┆ 07:05:55 ┆ │\n", + "│ ┆ Heath (… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5 ┆ Allen, Mr. ┆ male ┆ 35 ┆ … ┆ 1918-11-07 ┆ 10:59:08 ┆ 2022-08-02 ┆ null │\n", + "│ ┆ William Henry ┆ ┆ ┆ ┆ ┆ ┆ 15:13:34 ┆ │\n", + "└─────────────┴───────────────┴────────┴─────┴───┴────────────┴────────────┴──────────────┴────────┘" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get the demonstration data file\n", "csv_path = demo_file(\"titanic\")\n", @@ -116,10 +156,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "0a5a1aa2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Schema([('PassengerId', Int64),\n", + " ('Name', String),\n", + " ('Sex', Categorical(ordering='physical')),\n", + " ('Age', Int64),\n", + " ('Parch', Int64),\n", + " ('Ticket', String),\n", + " ('Fare', Float64),\n", + " ('Cabin', String),\n", + " ('Embarked', Categorical(ordering='physical')),\n", + " ('Birthday', Date),\n", + " ('Board time', Time),\n", + " ('Married since', Datetime(time_unit='us', time_zone=None)),\n", + " ('all_NA', String)])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df.schema" ] @@ -134,12 +197,59 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "c72c2acb55fca193", "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (9, 14)
statisticPassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
strf64strstrf64f64strf64strstrstrstrstrstr
"count"891.0"891""891"714.0891.0"891"891.0"204""889""813""812""799""0"
"null_count"0.0"0""0"177.00.0"0"0.0"687""2""78""79""92""891"
"mean"446.0nullnull29.6932770.381594null32.204208nullnull"1921-07-27 22:08:24.798000""14:38:10.014778""2022-07-31 03:43:48.767209"null
"std"257.353842nullnull14.5245270.806057null49.693429nullnullnullnullnullnull
"min"1.0"Abbing, Mr. Anthony"null0.00.0"110152"0.0"A10"null"1903-07-28""10:39:40""2022-07-15 12:21:15"null
"25%"224.0nullnull20.00.0null7.925nullnull"1911-09-18""12:39:02""2022-07-23 11:16:56"null
"50%"446.0nullnull28.00.0null14.4542nullnull"1922-03-26""14:29:34""2022-07-31 00:36:56"null
"75%"669.0nullnull38.00.0null31.0nullnull"1930-08-29""16:40:12""2022-08-08 03:35:52"null
"max"891.0"van Melkebeke, Mr. Philemon"null80.06.0"WE/P 5735"512.3292"T"null"1940-05-27""18:39:28""2022-08-15 10:32:05"null
" + ], + "text/plain": [ + "shape: (9, 14)\n", + "┌────────────┬─────────────┬────────────┬──────┬───┬────────────┬────────────┬────────────┬────────┐\n", + "│ statistic ┆ PassengerId ┆ Name ┆ Sex ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", + "│ str ┆ f64 ┆ str ┆ str ┆ ┆ str ┆ str ┆ --- ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ str ┆ │\n", + "╞════════════╪═════════════╪════════════╪══════╪═══╪════════════╪════════════╪════════════╪════════╡\n", + "│ count ┆ 891.0 ┆ 891 ┆ 891 ┆ … ┆ 813 ┆ 812 ┆ 799 ┆ 0 │\n", + "│ null_count ┆ 0.0 ┆ 0 ┆ 0 ┆ … ┆ 78 ┆ 79 ┆ 92 ┆ 891 │\n", + "│ mean ┆ 446.0 ┆ null ┆ null ┆ … ┆ 1921-07-27 ┆ 14:38:10.0 ┆ 2022-07-31 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ 22:08:24.7 ┆ 14778 ┆ 03:43:48.7 ┆ │\n", + "│ ┆ ┆ ┆ ┆ ┆ 98000 ┆ ┆ 67209 ┆ │\n", + "│ std ┆ 257.353842 ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │\n", + "│ min ┆ 1.0 ┆ Abbing, ┆ null ┆ … ┆ 1903-07-28 ┆ 10:39:40 ┆ 2022-07-15 ┆ null │\n", + "│ ┆ ┆ Mr. ┆ ┆ ┆ ┆ ┆ 12:21:15 ┆ │\n", + "│ ┆ ┆ Anthony ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 25% ┆ 224.0 ┆ null ┆ null ┆ … ┆ 1911-09-18 ┆ 12:39:02 ┆ 2022-07-23 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 11:16:56 ┆ │\n", + "│ 50% ┆ 446.0 ┆ null ┆ null ┆ … ┆ 1922-03-26 ┆ 14:29:34 ┆ 2022-07-31 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 00:36:56 ┆ │\n", + "│ 75% ┆ 669.0 ┆ null ┆ null ┆ … ┆ 1930-08-29 ┆ 16:40:12 ┆ 2022-08-08 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 03:35:52 ┆ │\n", + "│ max ┆ 891.0 ┆ van ┆ null ┆ … ┆ 1940-05-27 ┆ 18:39:28 ┆ 2022-08-15 ┆ null │\n", + "│ ┆ ┆ Melkebeke, ┆ ┆ ┆ ┆ ┆ 10:32:05 ┆ │\n", + "│ ┆ ┆ Mr. ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ ┆ Philemon ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "└────────────┴─────────────┴────────────┴──────┴───┴────────────┴────────────┴────────────┴────────┘" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "df.describe()" ] @@ -172,10 +282,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "e0c58473", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/13 [00:00\n", + "shape: (5, 13)
PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]str
842"Rise. Answer. Camera. Response…"female"300"8227"53.968851null"S"1936-03-1414:02:392022-07-21 16:19:37null
798"Realize. Ten someone. Behind m…"female"60"465036"21.628286null"S"1936-05-2917:00:182022-07-27 03:35:13null
305"History wait. Leg through year…"female"480"661985"51.767786null"S"1936-01-1213:01:272022-07-29 19:25:29null
377"Section. Able. Study.""female"390"612165"139.011237"A12""S"1927-06-0811:32:172022-08-11 10:28:23null
694"Himself.""male"10"618407"22.897537null"S"1921-10-1917:23:48nullnull
" + ], + "text/plain": [ + "shape: (5, 13)\n", + "┌─────────────┬───────────────┬────────┬─────┬───┬────────────┬────────────┬──────────────┬────────┐\n", + "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", + "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ --- ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ datetime[μs] ┆ │\n", + "╞═════════════╪═══════════════╪════════╪═════╪═══╪════════════╪════════════╪══════════════╪════════╡\n", + "│ 842 ┆ Rise. Answer. ┆ female ┆ 30 ┆ … ┆ 1936-03-14 ┆ 14:02:39 ┆ 2022-07-21 ┆ null │\n", + "│ ┆ Camera. ┆ ┆ ┆ ┆ ┆ ┆ 16:19:37 ┆ │\n", + "│ ┆ Response… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 798 ┆ Realize. Ten ┆ female ┆ 6 ┆ … ┆ 1936-05-29 ┆ 17:00:18 ┆ 2022-07-27 ┆ null │\n", + "│ ┆ someone. ┆ ┆ ┆ ┆ ┆ ┆ 03:35:13 ┆ │\n", + "│ ┆ Behind m… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 305 ┆ History wait. ┆ female ┆ 48 ┆ … ┆ 1936-01-12 ┆ 13:01:27 ┆ 2022-07-29 ┆ null │\n", + "│ ┆ Leg through ┆ ┆ ┆ ┆ ┆ ┆ 19:25:29 ┆ │\n", + "│ ┆ year… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 377 ┆ Section. ┆ female ┆ 39 ┆ … ┆ 1927-06-08 ┆ 11:32:17 ┆ 2022-08-11 ┆ null │\n", + "│ ┆ Able. Study. ┆ ┆ ┆ ┆ ┆ ┆ 10:28:23 ┆ │\n", + "│ 694 ┆ Himself. ┆ male ┆ 1 ┆ … ┆ 1921-10-19 ┆ 17:23:48 ┆ null ┆ null │\n", + "└─────────────┴───────────────┴────────┴─────┴───┴────────────┴────────────┴──────────────┴────────┘" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "syn_df" ] @@ -381,10 +1079,38 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "e7b76751", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 13/13 [00:01<00:00, 8.32it/s]\n" + ] + }, + { + "data": { + "text/plain": [ + "{'name': 'PassengerId',\n", + " 'type': 'discrete',\n", + " 'dtype': 'Int64',\n", + " 'prop_missing': 0.0,\n", + " 'distribution': {'implements': 'core.unique_key',\n", + " 'version': '1.0',\n", + " 'provenance': 'builtin',\n", + " 'class_name': 'UniqueKeyDistribution',\n", + " 'unique': True,\n", + " 'parameters': {'lower': 1, 'consecutive': True}},\n", + " 'creation_method': {'created_by': 'metasyn', 'unique': True}}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# First, we create a specification dictionary for the variables\n", "var_specs = [\n", @@ -408,10 +1134,51 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "38c2f4b6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 13)
PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]str
1"Really several. Instead.""male"190"320491"18.726832null"C"null14:11:202022-07-20 07:54:52null
2"Adult.""male"null0"25222"27.87715null"S"1936-06-2418:03:352022-07-26 01:42:15null
3"Country result. Author. Benefi…"male"170"KIP.A. 34247"51.373905null"S"1913-02-1218:34:482022-08-06 06:34:19null
4"More finally anything class. C…"male"320"4318"60.565239null"S"1931-08-2812:39:492022-07-26 12:06:39null
5"Real. Which.""male"260"09729"6.532226null"S"1914-08-3118:04:472022-07-22 16:18:58null
" + ], + "text/plain": [ + "shape: (5, 13)\n", + "┌─────────────┬───────────────┬──────┬──────┬───┬────────────┬────────────┬───────────────┬────────┐\n", + "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married since ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ datetime[μs] ┆ str │\n", + "╞═════════════╪═══════════════╪══════╪══════╪═══╪════════════╪════════════╪═══════════════╪════════╡\n", + "│ 1 ┆ Really ┆ male ┆ 19 ┆ … ┆ null ┆ 14:11:20 ┆ 2022-07-20 ┆ null │\n", + "│ ┆ several. ┆ ┆ ┆ ┆ ┆ ┆ 07:54:52 ┆ │\n", + "│ ┆ Instead. ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 2 ┆ Adult. ┆ male ┆ null ┆ … ┆ 1936-06-24 ┆ 18:03:35 ┆ 2022-07-26 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 01:42:15 ┆ │\n", + "│ 3 ┆ Country ┆ male ┆ 17 ┆ … ┆ 1913-02-12 ┆ 18:34:48 ┆ 2022-08-06 ┆ null │\n", + "│ ┆ result. ┆ ┆ ┆ ┆ ┆ ┆ 06:34:19 ┆ │\n", + "│ ┆ Author. ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ ┆ Benefi… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 4 ┆ More finally ┆ male ┆ 32 ┆ … ┆ 1931-08-28 ┆ 12:39:49 ┆ 2022-07-26 ┆ null │\n", + "│ ┆ anything ┆ ┆ ┆ ┆ ┆ ┆ 12:06:39 ┆ │\n", + "│ ┆ class. C… ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5 ┆ Real. Which. ┆ male ┆ 26 ┆ … ┆ 1914-08-31 ┆ 18:04:47 ┆ 2022-07-22 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 16:18:58 ┆ │\n", + "└─────────────┴───────────────┴──────┴──────┴───┴────────────┴────────────┴───────────────┴────────┘" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "mf.synthesize(5)" ] @@ -438,10 +1205,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "d5615aa0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 13/13 [00:00<00:00, 15.17it/s]\n" + ] + }, + { + "data": { + "text/html": [ + "
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PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]str
1"Joseph Garcia""female"null0"96223"20.99684null"S"1906-04-1111:22:222022-08-15 00:37:43null
2"Julie Kim""male"470"20728"17.124865null"S"1913-04-24null2022-07-29 06:33:10null
3"Mitchell Perry""male"160"88165"29.45121null"S"1929-05-20null2022-07-22 02:15:33null
4"Sean Sanchez""male"341"0956"26.174926null"S"null15:52:552022-08-08 17:34:23null
5"Laurie Adams""male"240"26664"102.336395null"Q"1913-12-1313:07:552022-08-04 07:46:23null
" + ], + "text/plain": [ + "shape: (5, 13)\n", + "┌─────────────┬──────────────┬────────┬──────┬───┬────────────┬────────────┬──────────────┬────────┐\n", + "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", + "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ --- ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ datetime[μs] ┆ │\n", + "╞═════════════╪══════════════╪════════╪══════╪═══╪════════════╪════════════╪══════════════╪════════╡\n", + "│ 1 ┆ Joseph ┆ female ┆ null ┆ … ┆ 1906-04-11 ┆ 11:22:22 ┆ 2022-08-15 ┆ null │\n", + "│ ┆ Garcia ┆ ┆ ┆ ┆ ┆ ┆ 00:37:43 ┆ │\n", + "│ 2 ┆ Julie Kim ┆ male ┆ 47 ┆ … ┆ 1913-04-24 ┆ null ┆ 2022-07-29 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 06:33:10 ┆ │\n", + "│ 3 ┆ Mitchell ┆ male ┆ 16 ┆ … ┆ 1929-05-20 ┆ null ┆ 2022-07-22 ┆ null │\n", + "│ ┆ Perry ┆ ┆ ┆ ┆ ┆ ┆ 02:15:33 ┆ │\n", + "│ 4 ┆ Sean Sanchez ┆ male ┆ 34 ┆ … ┆ null ┆ 15:52:55 ┆ 2022-08-08 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 17:34:23 ┆ │\n", + "│ 5 ┆ Laurie Adams ┆ male ┆ 24 ┆ … ┆ 1913-12-13 ┆ 13:07:55 ┆ 2022-08-04 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 07:46:23 ┆ │\n", + "└─────────────┴──────────────┴────────┴──────┴───┴────────────┴────────────┴──────────────┴────────┘" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# First, we create a specification dictionary for the variables\n", "from metasyn.distribution import FakerDistribution\n", @@ -477,10 +1289,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "ac4ba506", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 13/13 [00:00<00:00, 19.44it/s]\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 13)
PassengerIdNameSexAgeParchTicketFareCabinEmbarkedBirthdayBoard timeMarried sinceall_NA
i64strcati64i64strf64strcatdatetimedatetime[μs]str
1"Jessica Pena""male"340"28283"0.224997null"S"1928-11-1315:14:592022-07-23 00:08:48null
2"Paul Burke""male"210"87671"3.173168"E66""S"1940-05-0710:43:112022-07-28 20:28:12null
3"Seth Moore""female"320"72893"1.422964null"C"1932-12-0613:41:312022-07-21 07:54:26null
4"Melissa Collins""female"330"2627"1.864894null"S"1920-06-0911:14:332022-07-19 19:12:19null
5"Michael Barrera""female"220"29098"1.940266null"S"1920-11-08null2022-07-27 08:57:22null
" + ], + "text/plain": [ + "shape: (5, 13)\n", + "┌─────────────┬───────────────┬────────┬─────┬───┬────────────┬────────────┬──────────────┬────────┐\n", + "│ PassengerId ┆ Name ┆ Sex ┆ Age ┆ … ┆ Birthday ┆ Board time ┆ Married ┆ all_NA │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ since ┆ --- │\n", + "│ i64 ┆ str ┆ cat ┆ i64 ┆ ┆ date ┆ time ┆ --- ┆ str │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ datetime[μs] ┆ │\n", + "╞═════════════╪═══════════════╪════════╪═════╪═══╪════════════╪════════════╪══════════════╪════════╡\n", + "│ 1 ┆ Jessica Pena ┆ male ┆ 34 ┆ … ┆ 1928-11-13 ┆ 15:14:59 ┆ 2022-07-23 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 00:08:48 ┆ │\n", + "│ 2 ┆ Paul Burke ┆ male ┆ 21 ┆ … ┆ 1940-05-07 ┆ 10:43:11 ┆ 2022-07-28 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 20:28:12 ┆ │\n", + "│ 3 ┆ Seth Moore ┆ female ┆ 32 ┆ … ┆ 1932-12-06 ┆ 13:41:31 ┆ 2022-07-21 ┆ null │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ 07:54:26 ┆ │\n", + "│ 4 ┆ Melissa ┆ female ┆ 33 ┆ … ┆ 1920-06-09 ┆ 11:14:33 ┆ 2022-07-19 ┆ null │\n", + "│ ┆ Collins ┆ ┆ ┆ ┆ ┆ ┆ 19:12:19 ┆ │\n", + "│ 5 ┆ Michael ┆ female ┆ 22 ┆ … ┆ 1920-11-08 ┆ null ┆ 2022-07-27 ┆ null │\n", + "│ ┆ Barrera ┆ ┆ ┆ ┆ ┆ ┆ 08:57:22 ┆ │\n", + "└─────────────┴───────────────┴────────┴─────┴───┴────────────┴────────────┴──────────────┴────────┘" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from metasyn.distribution import DiscreteUniformDistribution\n", "\n", @@ -507,10 +1364,63 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "7b2c4003", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 13/13 [00:00<00:00, 23.80it/s]\n" + ] + }, + { + "data": { + "text/html": [ + "
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3"Megan Wright""female"210"02990"0.316863null"C"1932-01-1810:58:572022-08-12 10:10:27null
4"Jonathon Ward""male"340"60614"0.256896null"C"1907-07-2013:08:412022-07-26 22:05:29null
5"Monica White""male"250"319646"1.445188null"S"1909-11-1813:53:402022-07-23 14:19:42null
6"James Bryant""male"391"8807"1.767202null"S"1923-08-2010:42:542022-07-24 17:42:18null
7"Patricia Murphy""male"null0"2227"1.57518null"S"1909-08-2914:40:332022-08-09 11:07:34null
8"Jeremy Kane""female"370"1951"0.399932null"S"1912-04-26null2022-08-10 13:27:33null
9"Matthew Baker""male"390"712759"3.5895null"S"null18:36:302022-07-20 13:01:07null
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"execution_count": null, + "execution_count": 23, "id": "694d4474707f7950", "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'Cabin': 'The cabin number of the passenger.'}\n" + ] + } + ], "source": [ "print(mf.descriptions)" ] @@ -682,12 +1726,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "34a8aafc95c0219f", "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'PassengerId': 'The ID of each passenger, as assigned by Pandas.', 'Cabin': 'The cabin number of the passenger.'}\n" + ] + } + ], "source": [ "mf[\"PassengerId\"].description = \"The ID of each passenger, as assigned by Pandas.\"\n", "\n", @@ -706,12 +1758,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "3b2e873f7362160a", "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'PassengerId': 'The ID of each passenger, as assigned by Pandas.', 'Name': 'Name of the passenger', 'Age': 'Age of the passenger in years', 'Cabin': 'The cabin number of the passenger.'}\n" + ] + } + ], "source": [ "mf.descriptions = {\"Name\": \"Name of the passenger\", \"Age\": \"Age of the passenger in years\"}\n", "\n", @@ -734,12 +1794,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "ab2b34ed6b11578c", "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'PassengerId': 'Placeholder description for PassengerId', 'Name': 'Placeholder description for Name', 'Sex': 'Placeholder description for Sex', 'Age': 'Placeholder description for Age', 'Parch': 'Placeholder description for Parch', 'Ticket': 'Placeholder description for Ticket', 'Fare': 'Placeholder description for Fare', 'Cabin': 'Placeholder description for Cabin', 'Embarked': 'Placeholder description for Embarked', 'Birthday': 'Placeholder description for Birthday', 'Board time': 'Placeholder description for Board time', 'Married since': 'Placeholder description for Married since', 'all_NA': 'Placeholder description for all_NA'}\n" + ] + } + ], "source": [ "mf.descriptions = [f\"Placeholder description for {var.name}\" for var in mf.meta_vars]\n", "\n", diff --git a/examples/gmf_files/example_gmf_titanic.json b/examples/gmf_files/example_gmf_titanic.json index 63679e6e..776c3b5c 100644 --- a/examples/gmf_files/example_gmf_titanic.json +++ b/examples/gmf_files/example_gmf_titanic.json @@ -6,7 +6,7 @@ "name": "metasyn", "version": "1.0.2.dev34+gd68929e" }, - "creation time": "2024-10-01T11:08:49.721236" + "creation time": "2024-10-03T14:56:33.372136" }, "vars": [ { From 1402143bfe446f6b6d8eb5557e94092c8e08bae6 Mon Sep 17 00:00:00 2001 From: qubixes <44498096+qubixes@users.noreply.github.com> Date: Thu, 3 Oct 2024 15:17:45 +0200 Subject: [PATCH 20/25] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c3551437..ee03e0f0 100644 --- a/README.md +++ b/README.md @@ -71,7 +71,7 @@ mf = MetaFrame.fit_dataframe(df) # Generate a new DataFrame with 5 rows from the MetaFrame. df_synth = mf.synthesize(5) -# This DataFrame can be saved to csv, parquet, excel and more. +# This DataFrame can be exported to csv, parquet, excel and more. df_synth.write_csv("output.csv") ``` From d667f4ec6ed01eefccf7483437e9ff3dc1d0a314 Mon Sep 17 00:00:00 2001 From: qubixes <44498096+qubixes@users.noreply.github.com> Date: Thu, 3 Oct 2024 15:17:52 +0200 Subject: [PATCH 21/25] Update docs/source/developer/overview.rst --- docs/source/developer/overview.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/developer/overview.rst b/docs/source/developer/overview.rst index c0a02c54..fc28827e 100644 --- a/docs/source/developer/overview.rst +++ b/docs/source/developer/overview.rst @@ -15,7 +15,7 @@ The :class:`~metasyn.MetaFrame` class is a core component of the ``metasyn`` pac Essentially, a :obj:`~metasyn.MetaFrame` is a collection of :obj:`~metasyn.MetaVar` objects, each representing a column in a dataset. It contains methods that allow for the following: - **Fitting to a DataFrame**: The :meth:`~metasyn.MetaFrame.fit_dataframe` method allows for fitting a Polars DataFrame to create a :obj:`~metasyn.MetaFrame` object. This method takes several parameters including the DataFrame, column specifications, distribution providers, privacy level, and a progress bar flag. -- **Saving and loading**: The :meth:`~metasyn.MetaFrame.save` method serializes and saves the :obj:`~metasyn.MetaFrame` to a JSON or TOML file, following the GMF format. The :meth:`~metasyn.MetaFrame.load` method reads a :obj:`~metasyn.MetaFrame` from a JSON file. +- **Saving and loading**: The :meth:`~metasyn.MetaFrame.save` method serializes and saves the :obj:`~metasyn.MetaFrame` to a JSON or TOML file, following the GMF format. The :meth:`~metasyn.MetaFrame.load` method reads a :obj:`~metasyn.MetaFrame` from a JSON or TOML file. - **Synthesizing to a DataFrame**: The :meth:`~metasyn.MetaFrame.synthesize` method creates a synthetic Polars DataFrame based on the :obj:`~metasyn.MetaFrame`. From bad4774172d419999c347d316651511ffc840015 Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Thu, 3 Oct 2024 16:38:37 +0200 Subject: [PATCH 22/25] Improve comments --- metasyn/metaframe.py | 8 ++++++-- metasyn/privacy.py | 4 ++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/metasyn/metaframe.py b/metasyn/metaframe.py index 26385ac7..313f9271 100644 --- a/metasyn/metaframe.py +++ b/metasyn/metaframe.py @@ -376,10 +376,14 @@ def save_toml(self, fp: Optional[Union[pathlib.Path, str]], var = self.meta_vars[i] doc["vars"][i].comment(f"Metadata for column with name {var.name}") doc["vars"][i]["prop_missing"].comment( - f"Based on {round(self.n_rows*(1-var.prop_missing))} values") + f"Fraction of missing values, remaining: {round(self.n_rows*(1-var.prop_missing))} " + "values") + # The below comment does not work, a tomlkit bug? + # doc["vars"][i]["distribution"]["unique"].add(tomlkit.comment( + # "Whether to generate unique values or not")) if "privacy" in var.creation_method: privacy = get_privacy(**var.creation_method["privacy"]) - doc["vars"][i]["creation_method"].add(tomlkit.comment(privacy.comment(var.name))) + doc["vars"][i]["distribution"]["parameters"].add(tomlkit.comment(privacy.comment(var))) if var.distribution.matches_name("multinoulli"): counts = (var.distribution.probs*(1-var.prop_missing)*self.n_rows).round() doc["vars"][i]["distribution"].add(tomlkit.comment( diff --git a/metasyn/privacy.py b/metasyn/privacy.py index 45c37440..e1b1975f 100644 --- a/metasyn/privacy.py +++ b/metasyn/privacy.py @@ -51,7 +51,7 @@ def fit_kwargs(self): """ return self.to_dict()["parameters"] - def comment(self, col_name): # noqa + def comment(self, var): # noqa """Comment on the privacy features for the TOML GMF file. Parameters @@ -63,7 +63,7 @@ def comment(self, col_name): # noqa ------- A comment on the privacy features. """ - return "" + return "Above are the parameters for the column {var.name}" class BasicPrivacy(BasePrivacy): """Class representing no privacy level. From b3a1b09bc23dbf8094befe5dac37e31a9a43dccd Mon Sep 17 00:00:00 2001 From: Raoul Schram Date: Fri, 4 Oct 2024 11:25:30 +0200 Subject: [PATCH 23/25] Redo images and add source for images --- docs/source/images/Diagrams_figma.jam | Bin 0 -> 619415 bytes .../images/flow_metadata_generation.png | Bin 53165 -> 52378 bytes .../images/flow_metadata_generation_code.png | Bin 59443 -> 58515 bytes .../images/flow_synthetic_data_generation.png | Bin 56147 -> 55269 bytes .../flow_synthetic_data_generation_code.png | Bin 60571 -> 60832 bytes docs/source/images/pipeline_basic.png | Bin 96271 -> 137582 bytes docs/source/images/pipeline_basic_legacy.png | Bin 203582 -> 0 bytes docs/source/images/pipeline_cli.png | Bin 155746 -> 0 bytes .../images/pipeline_cli_create_meta.png | Bin 171516 -> 102614 bytes .../source/images/pipeline_cli_synthesize.png | Bin 0 -> 108672 bytes .../images/pipeline_estimation_code.png | Bin 61202 -> 60426 bytes .../images/pipeline_estimation_simple.png | Bin 123167 -> 0 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zDyAqbb@gf~OZWHQ`G$-8S6}|WSt==|;rn#ha%~2N9~yUgW~FDZjyk5L9rZOL)wR3p z+rG6X^iDe+r*Dwcb?zr;*w)_TUBY%znZZ7bLvZ9 zLr*z@6lJ62Xb6mkz-S1JhQMeDjE2By2#kinXb6nV5O|RL^S_aX>Quf1mSLa}@O1Ta JS?83{1OOzQQPBVZ diff --git a/docs/source/metasyn_in_detail.rst b/docs/source/metasyn_in_detail.rst index 2d0f0767..572f64e8 100644 --- a/docs/source/metasyn_in_detail.rst +++ b/docs/source/metasyn_in_detail.rst @@ -51,7 +51,7 @@ The three key stages of the ``metasyn`` pipeline include the **estimation** of t Estimation ^^^^^^^^^^^^^ -.. image:: /images/pipeline_estimation_simple.png +.. image:: /images/pipeline_estimation_code.png :alt: Metasyn Estimation Step in Pipeline :align: center @@ -147,9 +147,10 @@ From all those fits, the distribution with the lowest `AIC ` follow the :doc:`/developer/GMF`, a standard designed to be easy to read and understand. @@ -273,7 +274,7 @@ This allows for manual and automatic editing, as well as sharing. Data generation ^^^^^^^^^^^^^^^^ -.. image:: /images/pipeline_generation_simple.png +.. image:: /images/pipeline_generation_code.png :alt: Metasyn Estimation Step in Pipeline :align: center diff --git a/docs/source/usage/cli.rst b/docs/source/usage/cli.rst index 49c4e5b9..0765ab6e 100644 --- a/docs/source/usage/cli.rst +++ b/docs/source/usage/cli.rst @@ -160,7 +160,7 @@ Generating Synthetic Data ------------------------- The ``synthesize`` subcommand combines the :doc:`deserialization ` and :doc:`generation ` steps in the pipeline into one, and allows you to generate a synthetic dataset from a previously saved MetaFrame (stored as GMF file). -.. image:: /images/pipeline_cli.png +.. image:: /images/pipeline_cli_synthesize.png :alt: Creating Synthetic Data from a GMF file using the CLI :align: center diff --git a/docs/source/usage/generating_metaframes.rst b/docs/source/usage/generating_metaframes.rst index 864be8e2..3599933a 100644 --- a/docs/source/usage/generating_metaframes.rst +++ b/docs/source/usage/generating_metaframes.rst @@ -3,7 +3,7 @@ Generating MetaFrames One of the main features of ``metasyn`` is to create a :obj:`MetaFrame `, an object which captures the essential aspects of the dataset, including variable names, types, data types, the percentage of missing values, and distribution attributes. :obj:`MetaFrame ` objects essentially capture all the information needed to generate a synthetic dataset that aligns with the original dataset. -.. image:: /images/pipeline_estimation_simple.png +.. image:: /images/pipeline_estimation_code.png :alt: MetaFrame Generation Flow :align: center diff --git a/docs/source/usage/generating_synthetic_data.rst b/docs/source/usage/generating_synthetic_data.rst index ae4473c7..add360ef 100644 --- a/docs/source/usage/generating_synthetic_data.rst +++ b/docs/source/usage/generating_synthetic_data.rst @@ -3,7 +3,7 @@ Generating Synthetic Data Metasyn can **generate synthetic data** from any :obj:`MetaFrame ` object. -.. image:: /images/pipeline_generation_simple.png +.. image:: /images/pipeline_generation_code.png :alt: Synthetic Data Generation :align: center diff --git a/docs/source/usage/saving_metaframes.rst b/docs/source/usage/saving_metaframes.rst index a5d0b4dd..55d3241f 100644 --- a/docs/source/usage/saving_metaframes.rst +++ b/docs/source/usage/saving_metaframes.rst @@ -7,9 +7,10 @@ Exporting and importing MetaFrames Metasyn can serialize and **save a MetaFrame** into a GMF file. GMF files are JSON files that follow the :doc:`/developer/GMF` and have been designed to be easy to read and understand. This allows users to audit, understand, modify and share their data generation model with ease. -.. image:: /images/pipeline_serialization_simple.png +.. image:: /images/pipeline_serialization_code.png :alt: MetaFrame Serialization Flow :align: center + :width: 400px Exporting a MetaFrame ---------------------- From 993e60b032f269303408ae5124c8688eec5929ba Mon Sep 17 00:00:00 2001 From: qubixes <44498096+qubixes@users.noreply.github.com> Date: Thu, 10 Oct 2024 10:48:34 +0200 Subject: [PATCH 24/25] Update .github/workflows/core-ci.yml Co-authored-by: Erik-Jan van Kesteren --- .github/workflows/core-ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/core-ci.yml b/.github/workflows/core-ci.yml index 063388c1..6b65de97 100644 --- a/.github/workflows/core-ci.yml +++ b/.github/workflows/core-ci.yml @@ -21,7 +21,7 @@ jobs: - name: Install dependencies run: | python -m pip install --upgrade pip - python -m pip install ".[check]" tomlkit + python -m pip install ".[check,extra]" - name: Lint with Ruff run: ruff check metasyn - name: Check types with MyPy From d63518c15cd11a78cba77614abf4407d4b74269b Mon Sep 17 00:00:00 2001 From: qubixes <44498096+qubixes@users.noreply.github.com> Date: Thu, 10 Oct 2024 10:48:56 +0200 Subject: [PATCH 25/25] Update metasyn/__main__.py Co-authored-by: Erik-Jan van Kesteren --- metasyn/__main__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/metasyn/__main__.py b/metasyn/__main__.py index c681405f..ad9e9d74 100644 --- a/metasyn/__main__.py +++ b/metasyn/__main__.py @@ -22,7 +22,7 @@ from metasyn.validation import create_schema EXAMPLE_CREATE_META="metasyn create-meta your_dataset.csv -o your_gmf_file.json --config your_config.toml" # noqa: E501 -EXAMPLE_CREATE_TOML="metasyn create-meta you_dataset.csv -o your_gmf_file.toml --config your_config.toml" # noqa: E501 +EXAMPLE_CREATE_TOML="metasyn create-meta your_dataset.csv -o your_gmf_file.toml --config your_config.toml" # noqa: E501 EXAMPLE_SYNTHESIZE="metasyn synthesize your_gmf_file.json -o your_synthetic_file.csv" MAIN_HELP_MESSAGE = f"""

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