o +&]i(@sdZddlmZddlZddlmZejr3ddlm Z ddl Z ddl Z ddlZddlmZddlmZGdd d ZGd d d ZeZdS) z Data object interface for Altair datasets. This module provides a `data` object that allows accessing datasets as attributes and calling them with backend options, similar to the vega_datasets interface. ) annotationsN)Loader) LiteralString)_Backend)Datasetc@seZdZdZd+d,d d Zd d d-ddZed.ddZejd/ddZed0ddZ d d d-ddZ d0ddZ e j d1d!d"Ze j d2d%d"Ze j d3d(d"Ze j d d d-d)d"Zd d d-d*d"Zd S)4DatasetAccessora Accessor for individual datasets that can be called with backend options. This object provides access to a specific dataset with support for different backends and autocompletion. Call this object to load the dataset: dataset_accessor(engine="polars", **kwds) Parameters for __call__: engine : {"polars", "pandas", "pandas[pyarrow]", "pyarrow"}, optional The backend to use for loading the dataset. **kwds : Any Additional arguments passed to the loader. Examples -------- >>> from altair.datasets import data >>> >>> # Load with default backend >>> cars_df = data.cars() >>> >>> # Load with specific backend >>> cars_polars = data.cars(engine="polars") >>> cars_pandas = data.cars(engine="pandas") >>> # Note: pandas[pyarrow] backend requires pyarrow package >>> >>> # Get URL >>> url = data.cars.url >>> >>> # Use explicit load method >>> cars_df = data.cars.load(engine="polars") pandasnamerbackendrreturnNonec CsTddl}||_||_|||j|_d|d|d|d|d|d }||_dS)Nrz Load the 'a,' dataset. Parameters ---------- engine : {"polars", "pandas", "pandas[pyarrow]", "pyarrow"}, optional The backend to use for loading the dataset. **kwds : Any Additional arguments passed to the loader. Returns ------- DataFrame or Table The loaded dataset. Examples -------- >>> data.z)() # Load with default backend >>> data.z9(engine="polars") # Load with specific backend >>> data.z!.url # Get dataset URL >>> data.z/.load(engine="polars") # Explicit load method )inspect_name_backend signature _call_impl __signature____doc__)selfr r r docstringrS/var/www/html/IGF-ODF-V3/venv/lib/python3.10/site-packages/altair/datasets/_data.py__init__<s zDatasetAccessor.__init__N)enginer_Backend | Nonekwdst.AnycKs&|rt|n|j}||jfi|SN)r from_backend_loaderr)rrrloadrrrr\szDatasetAccessor._call_implLoader[t.Any, t.Any]cCs$t|dr|jSt|j|_|jS)N _prev_loader)hasattrr"rrrrrrrres zDatasetAccessor._loadervaluecCs ||_dSr)r")rr%rrrrls strcCs|j|jS)aZ Get the URL for this dataset. Returns ------- str The URL of the dataset. Examples -------- >>> from altair.datasets import data >>> cars_url = data.cars.url >>> print(cars_url) https://cdn.jsdelivr.net/npm/vega-datasets@v3.2.1/data/cars.json )rurlrr$rrrr'pszDatasetAccessor.urlcK|jdd|i|S)a Load the dataset with the specified engine. This method provides the same functionality as calling the accessor directly, but with more explicit parameter autocompletion in some IDEs. Parameters ---------- engine : {"polars", "pandas", "pandas[pyarrow]", "pyarrow"}, optional The backend to use for loading the dataset. **kwds : Any Additional arguments passed to the loader. Returns ------- DataFrame or Table The loaded dataset. Examples -------- >>> from altair.datasets import data >>> cars_df = data.cars.load(engine="polars") >>> movies_df = data.movies.load(engine="pandas") rNrrrrrrrrr szDatasetAccessor.loadcCsd|jd|jdS)NzDatasetAccessor('z', default_engine='z'))rrr$rrr__repr__szDatasetAccessor.__repr__t.Literal['polars'] pl.DataFramecKdSrrr*rrr__call__zDatasetAccessor.__call__&t.Literal['pandas', 'pandas[pyarrow]'] pd.DataFramecKr.rrr*rrrr/r0t.Literal['pyarrow']pa.TablecKr.rrr*rrrr/r0cKr.rrr*rrrr/r0cKr()a Load the dataset with the specified engine. Parameters ---------- engine : {{"polars", "pandas", "pandas[pyarrow]", "pyarrow"}}, optional The backend to use for loading the dataset. **kwds Additional arguments passed to the loader. Returns ------- The loaded dataset as a DataFrame/Table from the specified engine. Examples -------- >>> from altair.datasets import data >>> >>> # Load with default engine >>> df = data.cars() >>> >>> # Load with specific engine >>> df = data.cars(engine="polars") rNrr)r*rrrr/sr)r rr rr r )rrrrr r)r r!)r%r!r r r r&)rr,rrr r-)rr1rrr r2)rr3rrr r4)__name__ __module__ __qualname__rrrpropertyrsetterr'r r+toverloadr/rrrrrs0 "#        rcsjeZdZdZddddZd d d Zd!fd d Zd"ddZd#ddZd ddZ d$ddZ d%ddZ Z S)& DataObjectaq Main data object that provides access to all datasets as attributes. This is the primary interface for loading Altair datasets. It provides a simple, intuitive way to access datasets with autocompletion support. Examples -------- >>> from altair.datasets import data >>> >>> # Access datasets as attributes with autocompletion >>> cars_df = data.cars() >>> movies_df = data.movies(engine="pandas") >>> >>> # Get URLs >>> cars_url = data.cars.url >>> movies_url = data.movies.url >>> >>> # Set default engine for all datasets >>> data.set_default_engine("polars") >>> penguins_df = data.penguins() # Uses polars engine >>> >>> # List available datasets >>> available_datasets = data.list_datasets() >>> print(f"Available datasets: {len(available_datasets)}") Available datasets: 72 rr rr r cCs||_i|_d|_dSr)r _accessors_dataset_names)rr rrrrs zDataObject.__init__list[Dataset | LiteralString]cCsX|jdur)zddlm}|}t|j|_W|jSty(g|_Y|jSw|jS)z6Get the list of available dataset names from metadata.Nr)CsvCache)r@altair.datasets._cacherBlistmappingkeys Exception)rrBcacherrr_get_dataset_namess   zDataObject._get_dataset_names list[str]cstt}|}||S)z7Return list of available attributes for autocompletion.)rDsuper__dir__rI)rstandard_attrs dataset_names __class__rrrLszDataObject.__dir__r rrcCsP|}||vr|dd}d|d|}t|t||j|j|<|j|S)N z Dataset 'z!' not found. Available datasets: )rIAttributeErrorrrr?)rr rNavailable_datasets error_msgrrr __getattr__s  zDataObject.__getattr__rcCs||_|jdS)a Set the default engine for all datasets. Parameters ---------- engine : {"polars", "pandas", "pandas[pyarrow]", "pyarrow"} The backend to use as default for all datasets. Examples -------- >>> from altair.datasets import data >>> data.set_default_engine("polars") >>> # Now all datasets will use polars by default >>> cars_df = data.cars() # Uses polars >>> movies_df = data.movies() # Uses polars N)rr?clear)rrrrrset_default_engine#szDataObject.set_default_enginecCs|S)a Get a list of all available dataset names. Returns ------- list[str] List of available dataset names. Examples -------- >>> from altair.datasets import data >>> datasets = data.list_datasets() >>> print(f"Available datasets: {len(datasets)}") Available datasets: 72 >>> print(datasets[:5]) # First 5 datasets ['airports', 'annual_precip', 'anscombe', 'barley', 'birdstrikes'] )rIr$rrr list_datasets8szDataObject.list_datasetscCs|jS)a Get the current default engine. Returns ------- str The current default engine. Examples -------- >>> from altair.datasets import data >>> data.set_default_engine("pandas") >>> print(data.get_default_engine()) pandas >>> data.set_default_engine("polars") >>> print(data.get_default_engine()) polars )rr$rrrget_default_engineLszDataObject.get_default_enginer&cCs t|}d|jd|dS)Nz!AltairDataObject(default_engine='z ', datasets=))lenrIr)r dataset_countrrrr+as zDataObject.__repr__r5)r rr r )r rA)r rJ)r rr r)rrr r )r rr6) r7r8r9rrrIrLrUrWrXrYr+ __classcell__rrrOrr>s     r>)r __future__rtypingr<altair.datasets._loaderr TYPE_CHECKINGtyping_extensionsrrpdpolarsplpyarrowpaaltair.datasets._readerraltair.datasets._typingrrr>datarrrrs      J