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unpack_dtypes)_DELTALAKE_AVAILABLE deltalake) scan_parquet)scan_pyarrow_dataset)Schema)Literal
DeltaTable) DataFrameDataType LazyFrame)CredentialProviderFunctionautoF)versioncolumnsrechunkstorage_optionscredential_providerdelta_table_options use_pyarrowpyarrow_optionsc
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Reads into a DataFrame from a Delta lake table.
Parameters
----------
source
DeltaTable or a Path or URI to the root of the Delta lake table.
Note: For Local filesystem, absolute and relative paths are supported but
for the supported object storages - GCS, Azure and S3 full URI must be provided.
version
Numerical version or timestamp version of the Delta lake table.
Note: If `version` is not provided, the latest version of delta lake
table is read.
columns
Columns to select. Accepts a list of column names.
rechunk
Make sure that all columns are contiguous in memory by
aggregating the chunks into a single array.
storage_options
Extra options for the storage backends supported by `deltalake`.
For cloud storages, this may include configurations for authentication etc.
More info is available `here
`__.
credential_provider
Provide a function that can be called to provide cloud storage
credentials. The function is expected to return a dictionary of
credential keys along with an optional credential expiry time.
.. warning::
This functionality is considered **unstable**. It may be changed
at any point without it being considered a breaking change.
delta_table_options
Additional keyword arguments while reading a Delta lake Table.
use_pyarrow
Flag to enable pyarrow dataset reads.
pyarrow_options
Keyword arguments while converting a Delta lake Table to pyarrow table.
Returns
-------
DataFrame
Examples
--------
Reads a Delta table from local filesystem.
Note: Since version is not provided, the latest version of the delta table is read.
>>> table_path = "/path/to/delta-table/"
>>> pl.read_delta(table_path) # doctest: +SKIP
Reads a specific version of the Delta table from local filesystem.
Note: This will fail if the provided version of the delta table does not exist.
>>> pl.read_delta(table_path, version=1) # doctest: +SKIP
Time travel a delta table from local filesystem using a timestamp version.
>>> pl.read_delta(
... table_path, version=datetime(2020, 1, 1, tzinfo=timezone.utc)
... ) # doctest: +SKIP
Reads a Delta table from AWS S3.
See a list of supported storage options for S3 `here
`__.
>>> table_path = "s3://bucket/path/to/delta-table/"
>>> storage_options = {
... "AWS_ACCESS_KEY_ID": "THE_AWS_ACCESS_KEY_ID",
... "AWS_SECRET_ACCESS_KEY": "THE_AWS_SECRET_ACCESS_KEY",
... }
>>> pl.read_delta(table_path, storage_options=storage_options) # doctest: +SKIP
Reads a Delta table from Google Cloud storage (GCS).
See a list of supported storage options for GCS `here
`__.
>>> table_path = "gs://bucket/path/to/delta-table/"
>>> storage_options = {"SERVICE_ACCOUNT": "SERVICE_ACCOUNT_JSON_ABSOLUTE_PATH"}
>>> pl.read_delta(table_path, storage_options=storage_options) # doctest: +SKIP
Reads a Delta table from Azure.
Following type of table paths are supported,
* az:///
* adl:///
* abfs:///
See a list of supported storage options for Azure `here
`__.
>>> table_path = "az://container/path/to/delta-table/"
>>> storage_options = {
... "AZURE_STORAGE_ACCOUNT_NAME": "AZURE_STORAGE_ACCOUNT_NAME",
... "AZURE_STORAGE_ACCOUNT_KEY": "AZURE_STORAGE_ACCOUNT_KEY",
... }
>>> pl.read_delta(table_path, storage_options=storage_options) # doctest: +SKIP
Reads a Delta table with additional delta specific options. In the below example,
`without_files` option is used which loads the table without file tracking
information.
>>> table_path = "/path/to/delta-table/"
>>> delta_table_options = {"without_files": True}
>>> pl.read_delta(
... table_path, delta_table_options=delta_table_options
... ) # doctest: +SKIP
)sourcer r r r r r! r )
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|j1 j3 }t5 |j7 j0 }|j9 j: } dd} ||| \ }} |j= } |j> jA d r | D cg c] } | jC dd } } tE | |t/ | dkD r| nddt/ | dkD || |xs d S c c} w )aY
Lazily read from a Delta lake table.
Parameters
----------
source
DeltaTable or a Path or URI to the root of the Delta lake table.
Note: For Local filesystem, absolute and relative paths are supported but
for the supported object storages - GCS, Azure and S3 full URI must be provided.
version
Numerical version or timestamp version of the Delta lake table.
Note: If `version` is not provided, the latest version of delta lake
table is read.
storage_options
Extra options for the storage backends supported by `deltalake`.
For cloud storages, this may include configurations for authentication etc.
More info is available `here
`__.
credential_provider
Provide a function that can be called to provide cloud storage
credentials. The function is expected to return a dictionary of
credential keys along with an optional credential expiry time.
.. warning::
This functionality is considered **unstable**. It may be changed
at any point without it being considered a breaking change.
delta_table_options
Additional keyword arguments while reading a Delta lake Table.
use_pyarrow
Flag to enable pyarrow dataset reads.
pyarrow_options
Keyword arguments while converting a Delta lake Table to pyarrow table.
Use this parameter when filtering on partitioned columns or to read
from a 'fsspec' supported filesystem.
rechunk
Make sure that all columns are contiguous in memory by
aggregating the chunks into a single array.
Returns
-------
LazyFrame
Examples
--------
Creates a scan for a Delta table from local filesystem.
Note: Since version is not provided, the latest version of the delta table is read.
>>> table_path = "/path/to/delta-table/"
>>> pl.scan_delta(table_path).collect() # doctest: +SKIP
Creates a scan for a specific version of the Delta table from local filesystem.
Note: This will fail if the provided version of the delta table does not exist.
>>> pl.scan_delta(table_path, version=1).collect() # doctest: +SKIP
Time travel a delta table from local filesystem using a timestamp version.
>>> pl.scan_delta(
... table_path, version=datetime(2020, 1, 1, tzinfo=timezone.utc)
... ).collect() # doctest: +SKIP
Creates a scan for a Delta table from AWS S3.
See a list of supported storage options for S3 `here
`__.
>>> table_path = "s3://bucket/path/to/delta-table/"
>>> storage_options = {
... "AWS_REGION": "eu-central-1",
... "AWS_ACCESS_KEY_ID": "THE_AWS_ACCESS_KEY_ID",
... "AWS_SECRET_ACCESS_KEY": "THE_AWS_SECRET_ACCESS_KEY",
... }
>>> pl.scan_delta(
... table_path, storage_options=storage_options
... ).collect() # doctest: +SKIP
Creates a scan for a Delta table from Google Cloud storage (GCS).
See a list of supported storage options for GCS `here
`__.
>>> table_path = "gs://bucket/path/to/delta-table/"
>>> storage_options = {"SERVICE_ACCOUNT": "SERVICE_ACCOUNT_JSON_ABSOLUTE_PATH"}
>>> pl.scan_delta(
... table_path, storage_options=storage_options
... ).collect() # doctest: +SKIP
Creates a scan for a Delta table from Azure.
Supported options for Azure are available `here
`__.
Following type of table paths are supported,
* az:///
* adl:///
* abfs[s]:///
>>> table_path = "az://container/path/to/delta-table/"
>>> storage_options = {
... "AZURE_STORAGE_ACCOUNT_NAME": "AZURE_STORAGE_ACCOUNT_NAME",
... "AZURE_STORAGE_ACCOUNT_KEY": "AZURE_STORAGE_ACCOUNT_KEY",
... }
>>> pl.scan_delta(
... table_path, storage_options=storage_options
... ).collect() # doctest: +SKIP
Creates a scan for a Delta table with additional delta specific options.
In the below example, `without_files` option is used which loads the table without
file tracking information.
>>> table_path = "/path/to/delta-table/"
>>> delta_table_options = {"without_files": True}
>>> pl.scan_delta(
... table_path, delta_table_options=delta_table_options
... ).collect() # doctest: +SKIP
r r )!_init_credential_provider_builder)+_get_credentials_from_provider_expiry_awarer$ Nr z?cannot use credential_provider when passing a DeltaTable object)
table_pathr r r z7To make use of pyarrow_options, set use_pyarrow to True)DeltaProtocolError) MAX_SUPPORTED_READER_VERSION NOT_SUPPORTED_READER_VERSIONSUPPORTED_READER_FEATURESz&The table's minimum reader version is z5 but polars delta scanner only supports version 1 or z with these reader features: z)The table has set these reader features: z= but these are not yet supported by the polars delta scanner.c t | dk( r
| t g fS g }g }| j D ]0 \ }}||v r|j ||f |j ||f 2 t | t | fS )Nr )lenr itemsappend)schemapartition_columns main_schema hive_schemanamedtypes r(
_split_schemaz!scan_delta.._split_schemay s !Q &6":% % !<<> 2KD%((""D%=1""D%=1 2 k"F;$777r* z lakefs://zs3://insertF)r8 r; missing_columnshive_partitioningr r r )r8 r r9 z list[str]returnztuple[Schema, Schema])#_check_if_delta_availabler r ,polars.io.cloud.credential_provider._builderr, .polars.io.cloud.credential_provider._providersr-
isinstance
ValueErrorbuild_credential_provider_get_delta_lake_tableto_pyarrow_datasetr deltalake.exceptionsr/ deltalake.tabler0 r1 r2 protocolmin_reader_versionreader_features
differencer5 r8 to_arrowr empty_tablemetadatar9 file_uris table_uri
startswithreplacer ) r# r r r r r r! r credential_provider_credsr r, r- credential_provider_buildermsgproviderdl_tblpa_dsr/ r0 r1 r2 table_protocolmissing_features delta_schema
polars_schemar9 r> r: r; rU file_uris r( r$ r$ s @ " $ fj )&G ,'
#
(-@F-JOo &*#"/IIKKK
8 A GR " # *.I.U
E%2 D*C D / F )/R)))N=O PM NC$S) )==?++-L | 7 7 9:AAM );;88+48 8" -]=0.8.0. Read the documentation
`here `_.
NzWhen supplying a DeltaTable directly, `version`, `storage_options`, and `delta_table_options` are ignored.
To silence this warning, don't supply those parameters. )
stacklevel)r r r ) rD rG r r anywarningswarnRuntimeWarningrm rg r load_as_version)r. r r r rl r] s r( rJ rJ s *i 2 23 t# t+#4/
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ModuleNotFoundError)r[ s r( rD rD s O!#&& r* c Z t | }t t h}||z x}rd|}t | y )Nz+dataframe contains unsupported data types: )r r r
TypeError)dtypes
schema_dtypesunsupported_typesoverlapr[ s r( _check_for_unsupported_typesr~ sD !6*M t
"333w3;G;Gn 4r* )r# str | DeltaTabler int | str | datetime | Noner zlist[str] | Noner bool | Noner dict[str, Any] | Noner 3CredentialProviderFunction | Literal['auto'] | Noner r r boolr! r rC r )r# r r r r r r r r r r r r! r r r rC r )rV rg rd r rC rg )NNN)
r. r r r r r r r rC zdeltalake.DeltaTable)rC None)rz zlist[DataType]rC r ))
__future__r rr r pathlibr typingr r urllib.parser polars.convertr polars.datatypesr
r polars.datatypes.convertr polars.dependenciesr
r polars.io.parquetr #polars.io.pyarrow_dataset.functionsr
polars.schemar r r polarsr r r polars.io.cloudr r) r$ rm rJ rD r~ rB r* r( r s " % ! % ' 2 ? * D $55: ,0 $ -1OU15 -1H H )H H
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