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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_uint32.html">pyarrow.types.is_uint32</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_uint64.html">pyarrow.types.is_uint64</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_floating.html">pyarrow.types.is_floating</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_float32.html">pyarrow.types.is_float32</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_date64.html">pyarrow.types.is_date64</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_time32.html">pyarrow.types.is_time32</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_time64.html">pyarrow.types.is_time64</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.TypesEnum.html">pyarrow.types.TypesEnum</a></li> |
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| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/arrays.html">Arrays and Scalars</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.array.html">pyarrow.array</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Int8Array.html">pyarrow.Int8Array</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Int16Array.html">pyarrow.Int16Array</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.DictionaryScalar.html">pyarrow.DictionaryScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ListScalar.html">pyarrow.ListScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.FixedSizeListScalar.html">pyarrow.FixedSizeListScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.LargeListScalar.html">pyarrow.LargeListScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.MapScalar.html">pyarrow.MapScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.StructScalar.html">pyarrow.StructScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.UnionScalar.html">pyarrow.UnionScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ExtensionScalar.html">pyarrow.ExtensionScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.FixedShapeTensorScalar.html">pyarrow.FixedShapeTensorScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.JsonScalar.html">pyarrow.JsonScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.UuidScalar.html">pyarrow.UuidScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Bool8Scalar.html">pyarrow.Bool8Scalar</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/memory.html">Buffers and Memory</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.allocate_buffer.html">pyarrow.allocate_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.py_buffer.html">pyarrow.py_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.foreign_buffer.html">pyarrow.foreign_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Buffer.html">pyarrow.Buffer</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.compress.html">pyarrow.compress</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.decompress.html">pyarrow.decompress</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.MemoryPool.html">pyarrow.MemoryPool</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.default_memory_pool.html">pyarrow.default_memory_pool</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.compute.ascii_rpad.html">pyarrow.compute.ascii_rpad</a></li> |
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| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/acero.html">Acero - Streaming Execution Engine</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| </ul> |
| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/substrait.html">Substrait</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.substrait.deserialize_expressions.html">pyarrow.substrait.deserialize_expressions</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.substrait.serialize_expressions.html">pyarrow.substrait.serialize_expressions</a></li> |
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| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/flight.html">Arrow Flight</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.GcsFileSystem.html">pyarrow.fs.GcsFileSystem</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.FileSystemHandler.html">pyarrow.fs.FileSystemHandler</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.copy_files.html">pyarrow.fs.copy_files</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.initialize_s3.html">pyarrow.fs.initialize_s3</a></li> |
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| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/dataset.html">Dataset</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <section id="pyarrow-parquet-parquetwriter"> |
| <h1>pyarrow.parquet.ParquetWriter<a class="headerlink" href="#pyarrow-parquet-parquetwriter" title="Link to this heading">#</a></h1> |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter"> |
| <em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyarrow.parquet.</span></span><span class="sig-name descname"><span class="pre">ParquetWriter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">where</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filesystem</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flavor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'2.6'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dictionary</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compression</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'snappy'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_statistics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_deprecated_int96_timestamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compression_level</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_byte_stream_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writer_engine_version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_page_version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'1.0'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_compliant_nested_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encryption_properties</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dictionary_pagesize_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store_schema</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_page_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_page_checksum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sorting_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store_decimal_as_integer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">options</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter" title="Link to this definition">#</a></dt> |
| <dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p> |
| <p>Class for incrementally building a Parquet file for Arrow tables.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>where</strong><span class="classifier">path or file-like object</span></dt><dd></dd> |
| <dt><strong>schema</strong><span class="classifier"><a class="reference internal" href="pyarrow.Schema.html#pyarrow.Schema" title="pyarrow.Schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.Schema</span></code></a></span></dt><dd></dd> |
| <dt><strong>version</strong><span class="classifier">{“1.0”, “2.4”, “2.6”}, default “2.6”</span></dt><dd><p>Determine which Parquet logical types are available for use, whether the |
| reduced set from the Parquet 1.x.x format or the expanded logical types |
| added in later format versions. |
| Files written with version=’2.4’ or ‘2.6’ may not be readable in all |
| Parquet implementations, so version=’1.0’ is likely the choice that |
| maximizes file compatibility. |
| UINT32 and some logical types are only available with version ‘2.4’. |
| Nanosecond timestamps are only available with version ‘2.6’. |
| Other features such as compression algorithms or the new serialized |
| data page format must be enabled separately (see ‘compression’ and |
| ‘data_page_version’).</p> |
| </dd> |
| <dt><strong>use_dictionary</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Specify if we should use dictionary encoding in general or only for |
| some columns. |
| When encoding the column, if the dictionary size is too large, the |
| column will fallback to <code class="docutils literal notranslate"><span class="pre">PLAIN</span></code> encoding. Specially, <code class="docutils literal notranslate"><span class="pre">BOOLEAN</span></code> type |
| doesn’t support dictionary encoding.</p> |
| </dd> |
| <dt><strong>compression</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a>, default ‘snappy’</span></dt><dd><p>Specify the compression codec, either on a general basis or per-column. |
| Valid values: {‘NONE’, ‘SNAPPY’, ‘GZIP’, ‘BROTLI’, ‘LZ4’, ‘ZSTD’}.</p> |
| </dd> |
| <dt><strong>write_statistics</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Specify if we should write statistics in general (default is True) or only |
| for some columns.</p> |
| </dd> |
| <dt><strong>use_deprecated_int96_timestamps</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Write timestamps to INT96 Parquet format. Defaults to False unless enabled |
| by flavor argument. This take priority over the coerce_timestamps option.</p> |
| </dd> |
| <dt><strong>coerce_timestamps</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Cast timestamps to a particular resolution. If omitted, defaults are chosen |
| depending on <cite>version</cite>. For <code class="docutils literal notranslate"><span class="pre">version='1.0'</span></code> and <code class="docutils literal notranslate"><span class="pre">version='2.4'</span></code>, |
| nanoseconds are cast to microseconds (‘us’), while for |
| <code class="docutils literal notranslate"><span class="pre">version='2.6'</span></code> (the default), they are written natively without loss |
| of resolution. Seconds are always cast to milliseconds (‘ms’) by default, |
| as Parquet does not have any temporal type with seconds resolution. |
| If the casting results in loss of data, it will raise an exception |
| unless <code class="docutils literal notranslate"><span class="pre">allow_truncated_timestamps=True</span></code> is given. |
| Valid values: {None, ‘ms’, ‘us’}</p> |
| </dd> |
| <dt><strong>allow_truncated_timestamps</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Allow loss of data when coercing timestamps to a particular |
| resolution. E.g. if microsecond or nanosecond data is lost when coercing to |
| ‘ms’, do not raise an exception. Passing <code class="docutils literal notranslate"><span class="pre">allow_truncated_timestamp=True</span></code> |
| will NOT result in the truncation exception being ignored unless |
| <code class="docutils literal notranslate"><span class="pre">coerce_timestamps</span></code> is not None.</p> |
| </dd> |
| <dt><strong>data_page_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Set a target threshold for the approximate encoded size of data |
| pages within a column chunk (in bytes). If None, use the default data page |
| size of 1MByte.</p> |
| </dd> |
| <dt><strong>flavor</strong><span class="classifier">{‘spark’}, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Sanitize schema or set other compatibility options to work with |
| various target systems.</p> |
| </dd> |
| <dt><strong>filesystem</strong><span class="classifier"><a class="reference internal" href="pyarrow.fs.FileSystem.html#pyarrow.fs.FileSystem" title="pyarrow.fs.FileSystem"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileSystem</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>If nothing passed, will be inferred from <cite>where</cite> if path-like, else |
| <cite>where</cite> is already a file-like object so no filesystem is needed.</p> |
| </dd> |
| <dt><strong>compression_level</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Specify the compression level for a codec, either on a general basis or |
| per-column. If None is passed, arrow selects the compression level for |
| the compression codec in use. The compression level has a different |
| meaning for each codec, so you have to read the documentation of the |
| codec you are using. |
| An exception is thrown if the compression codec does not allow specifying |
| a compression level.</p> |
| </dd> |
| <dt><strong>use_byte_stream_split</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Specify if the byte_stream_split encoding should be used in general or |
| only for some columns. If both dictionary and byte_stream_stream are |
| enabled, then dictionary is preferred. |
| The byte_stream_split encoding is valid for integer, floating-point |
| and fixed-size binary data types (including decimals); it should be |
| combined with a compression codec so as to achieve size reduction.</p> |
| </dd> |
| <dt><strong>column_encoding</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Specify the encoding scheme on a per column basis. |
| Can only be used when <code class="docutils literal notranslate"><span class="pre">use_dictionary</span></code> is set to False, and |
| cannot be used in combination with <code class="docutils literal notranslate"><span class="pre">use_byte_stream_split</span></code>. |
| Currently supported values: {‘PLAIN’, ‘BYTE_STREAM_SPLIT’, |
| ‘DELTA_BINARY_PACKED’, ‘DELTA_LENGTH_BYTE_ARRAY’, ‘DELTA_BYTE_ARRAY’}. |
| Certain encodings are only compatible with certain data types. |
| Please refer to the encodings section of <a class="reference external" href="https://arrow.apache.org/docs/cpp/parquet.html#encodings">Reading and writing Parquet |
| files</a>.</p> |
| </dd> |
| <dt><strong>data_page_version</strong><span class="classifier">{“1.0”, “2.0”}, default “1.0”</span></dt><dd><p>The serialized Parquet data page format version to write, defaults to |
| 1.0. This does not impact the file schema logical types and Arrow to |
| Parquet type casting behavior; for that use the “version” option.</p> |
| </dd> |
| <dt><strong>use_compliant_nested_type</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Whether to write compliant Parquet nested type (lists) as defined |
| <a class="reference external" href="https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#nested-types">here</a>, defaults to <code class="docutils literal notranslate"><span class="pre">True</span></code>. |
| For <code class="docutils literal notranslate"><span class="pre">use_compliant_nested_type=True</span></code>, this will write into a list |
| with 3-level structure where the middle level, named <code class="docutils literal notranslate"><span class="pre">list</span></code>, |
| is a repeated group with a single field named <code class="docutils literal notranslate"><span class="pre">element</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o"><</span><span class="nb">list</span><span class="o">-</span><span class="n">repetition</span><span class="o">></span> <span class="n">group</span> <span class="o"><</span><span class="n">name</span><span class="o">></span> <span class="p">(</span><span class="n">LIST</span><span class="p">)</span> <span class="p">{</span> |
| <span class="n">repeated</span> <span class="n">group</span> <span class="nb">list</span> <span class="p">{</span> |
| <span class="o"><</span><span class="n">element</span><span class="o">-</span><span class="n">repetition</span><span class="o">></span> <span class="o"><</span><span class="n">element</span><span class="o">-</span><span class="nb">type</span><span class="o">></span> <span class="n">element</span><span class="p">;</span> |
| <span class="p">}</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>For <code class="docutils literal notranslate"><span class="pre">use_compliant_nested_type=False</span></code>, this will also write into a list |
| with 3-level structure, where the name of the single field of the middle |
| level <code class="docutils literal notranslate"><span class="pre">list</span></code> is taken from the element name for nested columns in Arrow, |
| which defaults to <code class="docutils literal notranslate"><span class="pre">item</span></code>:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o"><</span><span class="nb">list</span><span class="o">-</span><span class="n">repetition</span><span class="o">></span> <span class="n">group</span> <span class="o"><</span><span class="n">name</span><span class="o">></span> <span class="p">(</span><span class="n">LIST</span><span class="p">)</span> <span class="p">{</span> |
| <span class="n">repeated</span> <span class="n">group</span> <span class="nb">list</span> <span class="p">{</span> |
| <span class="o"><</span><span class="n">element</span><span class="o">-</span><span class="n">repetition</span><span class="o">></span> <span class="o"><</span><span class="n">element</span><span class="o">-</span><span class="nb">type</span><span class="o">></span> <span class="n">item</span><span class="p">;</span> |
| <span class="p">}</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| </dd> |
| <dt><strong>encryption_properties</strong><span class="classifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileEncryptionProperties</span></code>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>File encryption properties for Parquet Modular Encryption. |
| If None, no encryption will be done. |
| The encryption properties can be created using: |
| <code class="docutils literal notranslate"><span class="pre">CryptoFactory.file_encryption_properties()</span></code>.</p> |
| </dd> |
| <dt><strong>write_batch_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Number of values to write to a page at a time. If None, use the default of |
| 1024. <code class="docutils literal notranslate"><span class="pre">write_batch_size</span></code> is complementary to <code class="docutils literal notranslate"><span class="pre">data_page_size</span></code>. If pages |
| are exceeding the <code class="docutils literal notranslate"><span class="pre">data_page_size</span></code> due to large column values, lowering |
| the batch size can help keep page sizes closer to the intended size.</p> |
| </dd> |
| <dt><strong>dictionary_pagesize_limit</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Specify the dictionary page size limit per row group. If None, use the |
| default 1MB.</p> |
| </dd> |
| <dt><strong>store_schema</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>By default, the Arrow schema is serialized and stored in the Parquet |
| file metadata (in the “ARROW:schema” key). When reading the file, |
| if this key is available, it will be used to more faithfully recreate |
| the original Arrow data. For example, for tz-aware timestamp columns |
| it will restore the timezone (Parquet only stores the UTC values without |
| timezone), or columns with duration type will be restored from the int64 |
| Parquet column.</p> |
| </dd> |
| <dt><strong>write_page_index</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Whether to write a page index in general for all columns. |
| Writing statistics to the page index disables the old method of writing |
| statistics to each data page header. The page index makes statistics-based |
| filtering more efficient than the page header, as it gathers all the |
| statistics for a Parquet file in a single place, avoiding scattered I/O. |
| Note that the page index is not yet used on the read size by PyArrow.</p> |
| </dd> |
| <dt><strong>write_page_checksum</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Whether to write page checksums in general for all columns. |
| Page checksums enable detection of data corruption, which might occur during |
| transmission or in the storage.</p> |
| </dd> |
| <dt><strong>sorting_columns</strong><span class="classifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Sequence</span></code> of <a class="reference internal" href="pyarrow.parquet.SortingColumn.html#pyarrow.parquet.SortingColumn" title="pyarrow.parquet.SortingColumn"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SortingColumn</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Specify the sort order of the data being written. The writer does not sort |
| the data nor does it verify that the data is sorted. The sort order is |
| written to the row group metadata, which can then be used by readers.</p> |
| </dd> |
| <dt><strong>store_decimal_as_integer</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Allow decimals with 1 <= precision <= 18 to be stored as integers. |
| In Parquet, DECIMAL can be stored in any of the following physical types: |
| - int32: for 1 <= precision <= 9. |
| - int64: for 10 <= precision <= 18. |
| - fixed_len_byte_array: precision is limited by the array size.</p> |
| <blockquote> |
| <div><p>Length n can store <= floor(log_10(2^(8*n - 1) - 1)) base-10 digits.</p> |
| </div></blockquote> |
| <ul class="simple"> |
| <li><p>binary: precision is unlimited. The minimum number of bytes to store the |
| unscaled value is used.</p></li> |
| </ul> |
| <p>By default, this is DISABLED and all decimal types annotate fixed_len_byte_array. |
| When enabled, the writer will use the following physical types to store decimals: |
| - int32: for 1 <= precision <= 9. |
| - int64: for 10 <= precision <= 18. |
| - fixed_len_byte_array: for precision > 18.</p> |
| <p>As a consequence, decimal columns stored in integer types are more compact.</p> |
| </dd> |
| <dt><strong>use_content_defined_chunking</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Optimize parquet files for content addressable storage (CAS) systems by writing |
| data pages according to content-defined chunk boundaries. This allows for more |
| efficient deduplication of data across files, hence more efficient network |
| transfers and storage. The chunking is based on a rolling hash algorithm that |
| identifies chunk boundaries based on the actual content of the data.</p> |
| <p>Note that it is an experimental feature and the API may change in the future.</p> |
| <p>If set to <code class="docutils literal notranslate"><span class="pre">True</span></code>, a default configuration is used with <cite>min_chunk_size=256 KiB</cite> |
| and <cite>max_chunk_size=1024 KiB</cite>. The chunk size distribution approximates a normal |
| distribution between <cite>min_chunk_size</cite> and <cite>max_chunk_size</cite> (sizes are accounted |
| before any Parquet encodings).</p> |
| <p>A <cite>dict</cite> can be passed to adjust the chunker parameters with the following keys: |
| - <cite>min_chunk_size</cite>: minimum chunk size in bytes, default 256 KiB</p> |
| <blockquote> |
| <div><p>The rolling hash will not be updated until this size is reached for each chunk. |
| Note that all data sent through the hash function is counted towards the chunk |
| size, including definition and repetition levels if present.</p> |
| </div></blockquote> |
| <ul class="simple"> |
| <li><p><cite>max_chunk_size</cite>: maximum chunk size in bytes, default is 1024 KiB |
| The chunker will create a new chunk whenever the chunk size exceeds this value. |
| Note that the parquet writer has a related <cite>data_pagesize</cite> property that controls |
| the maximum size of a parquet data page after encoding. While setting |
| <cite>data_page_size</cite> to a smaller value than <cite>max_chunk_size</cite> doesn’t affect the |
| chunking effectiveness, it results in more small parquet data pages.</p></li> |
| <li><p><cite>norm_level</cite>: normalization level to center the chunk size around the average |
| size more aggressively, default 0 |
| Increasing the normalization level increases the probability of finding a chunk, |
| improving the deduplication ratio, but also increasing the number of small chunks |
| resulting in many small parquet data pages. The default value provides a good |
| balance between deduplication ratio and fragmentation. Use norm_level=1 or |
| norm_level=2 to reach a higher deduplication ratio at the expense of |
| fragmentation.</p></li> |
| </ul> |
| </dd> |
| <dt><strong>writer_engine_version</strong><span class="classifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">unused</span></code></span></dt><dd></dd> |
| <dt><strong>**options</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a></span></dt><dd><p>If options contains a key <cite>metadata_collector</cite> then the |
| corresponding value is assumed to be a list (or any object with |
| <cite>.append</cite> method) that will be filled with the file metadata instance |
| of the written file.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <p>Generate an example PyArrow Table and RecordBatch:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">pyarrow</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pa</span> |
| <span class="gp">>>> </span><span class="n">table</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">table</span><span class="p">({</span><span class="s1">'n_legs'</span><span class="p">:</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">100</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="s1">'animal'</span><span class="p">:</span> <span class="p">[</span><span class="s2">"Flamingo"</span><span class="p">,</span> <span class="s2">"Parrot"</span><span class="p">,</span> <span class="s2">"Dog"</span><span class="p">,</span> <span class="s2">"Horse"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s2">"Brittle stars"</span><span class="p">,</span> <span class="s2">"Centipede"</span><span class="p">]})</span> |
| <span class="gp">>>> </span><span class="n">batch</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">record_batch</span><span class="p">([[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">100</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="p">[</span><span class="s2">"Flamingo"</span><span class="p">,</span> <span class="s2">"Parrot"</span><span class="p">,</span> <span class="s2">"Dog"</span><span class="p">,</span> <span class="s2">"Horse"</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="s2">"Brittle stars"</span><span class="p">,</span> <span class="s2">"Centipede"</span><span class="p">]],</span> |
| <span class="gp">... </span> <span class="n">names</span><span class="o">=</span><span class="p">[</span><span class="s1">'n_legs'</span><span class="p">,</span> <span class="s1">'animal'</span><span class="p">])</span> |
| </pre></div> |
| </div> |
| <p>create a ParquetWriter object:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">pyarrow.parquet</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">writer</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetWriter</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">,</span> <span class="n">table</span><span class="o">.</span><span class="n">schema</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>and write the Table into the Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">writer</span><span class="o">.</span><span class="n">write_table</span><span class="p">(</span><span class="n">table</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">writer</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">pq</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">)</span><span class="o">.</span><span class="n">to_pandas</span><span class="p">()</span> |
| <span class="go"> n_legs animal</span> |
| <span class="go">0 2 Flamingo</span> |
| <span class="go">1 2 Parrot</span> |
| <span class="go">2 4 Dog</span> |
| <span class="go">3 4 Horse</span> |
| <span class="go">4 5 Brittle stars</span> |
| <span class="go">5 100 Centipede</span> |
| </pre></div> |
| </div> |
| <p>create a ParquetWriter object for the RecordBatch:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">writer2</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetWriter</span><span class="p">(</span><span class="s1">'example2.parquet'</span><span class="p">,</span> <span class="n">batch</span><span class="o">.</span><span class="n">schema</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>and write the RecordBatch into the Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">writer2</span><span class="o">.</span><span class="n">write_batch</span><span class="p">(</span><span class="n">batch</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">writer2</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">pq</span><span class="o">.</span><span class="n">read_table</span><span class="p">(</span><span class="s1">'example2.parquet'</span><span class="p">)</span><span class="o">.</span><span class="n">to_pandas</span><span class="p">()</span> |
| <span class="go"> n_legs animal</span> |
| <span class="go">0 2 Flamingo</span> |
| <span class="go">1 2 Parrot</span> |
| <span class="go">2 4 Dog</span> |
| <span class="go">3 4 Horse</span> |
| <span class="go">4 5 Brittle stars</span> |
| <span class="go">5 100 Centipede</span> |
| </pre></div> |
| </div> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.__init__"> |
| <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">where</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filesystem</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">flavor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'2.6'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_dictionary</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compression</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'snappy'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_statistics</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_deprecated_int96_timestamps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compression_level</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_byte_stream_split</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">column_encoding</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">writer_engine_version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_page_version</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'1.0'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_compliant_nested_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">encryption_properties</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dictionary_pagesize_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store_schema</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_page_index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">write_page_checksum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sorting_columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store_decimal_as_integer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">options</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.__init__"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.__init__" title="Link to this definition">#</a></dt> |
| <dd></dd></dl> |
| |
| <p class="rubric">Methods</p> |
| <div class="pst-scrollable-table-container"><table class="autosummary longtable table"> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.__init__" title="pyarrow.parquet.ParquetWriter.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(where, schema[, filesystem, ...])</p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.add_key_value_metadata" title="pyarrow.parquet.ParquetWriter.add_key_value_metadata"><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_key_value_metadata</span></code></a>(key_value_metadata)</p></td> |
| <td><p>Add key-value metadata to the file.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.close" title="pyarrow.parquet.ParquetWriter.close"><code class="xref py py-obj docutils literal notranslate"><span class="pre">close</span></code></a>()</p></td> |
| <td><p>Close the connection to the Parquet file.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.write" title="pyarrow.parquet.ParquetWriter.write"><code class="xref py py-obj docutils literal notranslate"><span class="pre">write</span></code></a>(table_or_batch[, row_group_size])</p></td> |
| <td><p>Write RecordBatch or Table to the Parquet file.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.write_batch" title="pyarrow.parquet.ParquetWriter.write_batch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">write_batch</span></code></a>(batch[, row_group_size])</p></td> |
| <td><p>Write RecordBatch to the Parquet file.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetWriter.write_table" title="pyarrow.parquet.ParquetWriter.write_table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">write_table</span></code></a>(table[, row_group_size])</p></td> |
| <td><p>Write Table to the Parquet file.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.add_key_value_metadata"> |
| <span class="sig-name descname"><span class="pre">add_key_value_metadata</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key_value_metadata</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.add_key_value_metadata"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.add_key_value_metadata" title="Link to this definition">#</a></dt> |
| <dd><p>Add key-value metadata to the file. |
| This will overwrite any existing metadata with the same key.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>key_value_metadata</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">dict</span></code></a></span></dt><dd><p>Keys and values must be string-like / coercible to bytes.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.close"> |
| <span class="sig-name descname"><span class="pre">close</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.close"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.close" title="Link to this definition">#</a></dt> |
| <dd><p>Close the connection to the Parquet file.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.write"> |
| <span class="sig-name descname"><span class="pre">write</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">table_or_batch</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">row_group_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.write"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.write" title="Link to this definition">#</a></dt> |
| <dd><p>Write RecordBatch or Table to the Parquet file.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>table_or_batch</strong><span class="classifier">{<a class="reference internal" href="pyarrow.RecordBatch.html#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordBatch</span></code></a>, <a class="reference internal" href="pyarrow.Table.html#pyarrow.Table" title="pyarrow.Table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Table</span></code></a>}</span></dt><dd></dd> |
| <dt><strong>row_group_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Maximum number of rows in each written row group. If None, the row |
| group size will be the minimum of the number of rows in the |
| Table/RecordBatch and 1024 * 1024.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.write_batch"> |
| <span class="sig-name descname"><span class="pre">write_batch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">row_group_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.write_batch"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.write_batch" title="Link to this definition">#</a></dt> |
| <dd><p>Write RecordBatch to the Parquet file.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>batch</strong><span class="classifier"><a class="reference internal" href="pyarrow.RecordBatch.html#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordBatch</span></code></a></span></dt><dd></dd> |
| <dt><strong>row_group_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Maximum number of rows in written row group. If None, the |
| row group size will be the minimum of the RecordBatch |
| size (in rows) and 1024 * 1024. If set larger than 64 * 1024 * 1024 |
| then 64 * 1024 * 1024 will be used instead.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetWriter.write_table"> |
| <span class="sig-name descname"><span class="pre">write_table</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">table</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">row_group_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetWriter.write_table"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetWriter.write_table" title="Link to this definition">#</a></dt> |
| <dd><p>Write Table to the Parquet file.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>table</strong><span class="classifier"><a class="reference internal" href="pyarrow.Table.html#pyarrow.Table" title="pyarrow.Table"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Table</span></code></a></span></dt><dd></dd> |
| <dt><strong>row_group_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Maximum number of rows in each written row group. If None, |
| the row group size will be the minimum of the Table size (in rows) |
| and 1024 * 1024. If set larger than 64 * 1024 * 1024 then |
| 64 * 1024 * 1024 will be used instead.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| </dd></dl> |
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| </dd></dl> |
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