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| <div class="section" id="pyarrow-parquet-parquetfile"> |
| <h1>pyarrow.parquet.ParquetFile<a class="headerlink" href="#pyarrow-parquet-parquetfile" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyarrow.parquet.ParquetFile"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyarrow.parquet.</code><code class="sig-name descname">ParquetFile</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">source</span></em>, <em class="sig-param"><span class="n">metadata</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">common_metadata</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">read_dictionary</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">memory_map</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">buffer_size</span><span class="o">=</span><span class="default_value">0</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p> |
| <p>Reader interface for a single Parquet file.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>source</strong> (<em>str</em><em>, </em><em>pathlib.Path</em><em>, </em><a class="reference internal" href="pyarrow.NativeFile.html#pyarrow.NativeFile" title="pyarrow.NativeFile"><em>pyarrow.NativeFile</em></a><em>, or </em><em>file-like object</em>) – Readable source. For passing bytes or buffer-like file containing a |
| Parquet file, use pyarrow.BufferReader.</p></li> |
| <li><p><strong>metadata</strong> (<em>FileMetaData</em><em>, </em><em>default None</em>) – Use existing metadata object, rather than reading from file.</p></li> |
| <li><p><strong>common_metadata</strong> (<em>FileMetaData</em><em>, </em><em>default None</em>) – Will be used in reads for pandas schema metadata if not found in the |
| main file’s metadata, no other uses at the moment.</p></li> |
| <li><p><strong>memory_map</strong> (<em>bool</em><em>, </em><em>default False</em>) – If the source is a file path, use a memory map to read file, which can |
| improve performance in some environments.</p></li> |
| <li><p><strong>buffer_size</strong> (<em>int</em><em>, </em><em>default 0</em>) – If positive, perform read buffering when deserializing individual |
| column chunks. Otherwise IO calls are unbuffered.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.__init__"> |
| <code class="sig-name descname">__init__</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">source</span></em>, <em class="sig-param"><span class="n">metadata</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">common_metadata</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">read_dictionary</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">memory_map</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">buffer_size</span><span class="o">=</span><span class="default_value">0</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile.__init__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.__init__" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Initialize self. See help(type(self)) for accurate signature.</p> |
| </dd></dl> |
| |
| <p class="rubric">Methods</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.__init__" title="pyarrow.parquet.ParquetFile.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(source[, metadata, …])</p></td> |
| <td><p>Initialize self.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.read" title="pyarrow.parquet.ParquetFile.read"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read</span></code></a>([columns, use_threads, use_pandas_metadata])</p></td> |
| <td><p>Read a Table from Parquet format,</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.read_row_group" title="pyarrow.parquet.ParquetFile.read_row_group"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_row_group</span></code></a>(i[, columns, use_threads, …])</p></td> |
| <td><p>Read a single row group from a Parquet file.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.read_row_groups" title="pyarrow.parquet.ParquetFile.read_row_groups"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_row_groups</span></code></a>(row_groups[, columns, …])</p></td> |
| <td><p>Read a multiple row groups from a Parquet file.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.scan_contents" title="pyarrow.parquet.ParquetFile.scan_contents"><code class="xref py py-obj docutils literal notranslate"><span class="pre">scan_contents</span></code></a>([columns, batch_size])</p></td> |
| <td><p>Read contents of file for the given columns and batch size.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Attributes</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.metadata" title="pyarrow.parquet.ParquetFile.metadata"><code class="xref py py-obj docutils literal notranslate"><span class="pre">metadata</span></code></a></p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.num_row_groups" title="pyarrow.parquet.ParquetFile.num_row_groups"><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_row_groups</span></code></a></p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.schema" title="pyarrow.parquet.ParquetFile.schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">schema</span></code></a></p></td> |
| <td><p>Return the Parquet schema, unconverted to Arrow types</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.schema_arrow" title="pyarrow.parquet.ParquetFile.schema_arrow"><code class="xref py py-obj docutils literal notranslate"><span class="pre">schema_arrow</span></code></a></p></td> |
| <td><p>Return the inferred Arrow schema, converted from the whole Parquet file’s schema</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.metadata"> |
| <em class="property">property </em><code class="sig-name descname">metadata</code><a class="headerlink" href="#pyarrow.parquet.ParquetFile.metadata" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.num_row_groups"> |
| <em class="property">property </em><code class="sig-name descname">num_row_groups</code><a class="headerlink" href="#pyarrow.parquet.ParquetFile.num_row_groups" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.read"> |
| <code class="sig-name descname">read</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">columns</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">use_threads</span><span class="o">=</span><span class="default_value">True</span></em>, <em class="sig-param"><span class="n">use_pandas_metadata</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile.read"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.read" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read a Table from Parquet format,</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>columns</strong> (<em>list</em>) – If not None, only these columns will be read from the file. A |
| column name may be a prefix of a nested field, e.g. ‘a’ will select |
| ‘a.b’, ‘a.c’, and ‘a.d.e’.</p></li> |
| <li><p><strong>use_threads</strong> (<em>bool</em><em>, </em><em>default True</em>) – Perform multi-threaded column reads.</p></li> |
| <li><p><strong>use_pandas_metadata</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.table.Table</em> – Content of the file as a table (of columns).</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.read_row_group"> |
| <code class="sig-name descname">read_row_group</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">i</span></em>, <em class="sig-param"><span class="n">columns</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">use_threads</span><span class="o">=</span><span class="default_value">True</span></em>, <em class="sig-param"><span class="n">use_pandas_metadata</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile.read_row_group"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.read_row_group" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read a single row group from a Parquet file.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>columns</strong> (<em>list</em>) – If not None, only these columns will be read from the row group. A |
| column name may be a prefix of a nested field, e.g. ‘a’ will select |
| ‘a.b’, ‘a.c’, and ‘a.d.e’.</p></li> |
| <li><p><strong>use_threads</strong> (<em>bool</em><em>, </em><em>default True</em>) – Perform multi-threaded column reads.</p></li> |
| <li><p><strong>use_pandas_metadata</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.table.Table</em> – Content of the row group as a table (of columns)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.read_row_groups"> |
| <code class="sig-name descname">read_row_groups</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">row_groups</span></em>, <em class="sig-param"><span class="n">columns</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">use_threads</span><span class="o">=</span><span class="default_value">True</span></em>, <em class="sig-param"><span class="n">use_pandas_metadata</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile.read_row_groups"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.read_row_groups" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read a multiple row groups from a Parquet file.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>row_groups</strong> (<em>list</em>) – Only these row groups will be read from the file.</p></li> |
| <li><p><strong>columns</strong> (<em>list</em>) – If not None, only these columns will be read from the row group. A |
| column name may be a prefix of a nested field, e.g. ‘a’ will select |
| ‘a.b’, ‘a.c’, and ‘a.d.e’.</p></li> |
| <li><p><strong>use_threads</strong> (<em>bool</em><em>, </em><em>default True</em>) – Perform multi-threaded column reads.</p></li> |
| <li><p><strong>use_pandas_metadata</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.table.Table</em> – Content of the row groups as a table (of columns).</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.scan_contents"> |
| <code class="sig-name descname">scan_contents</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">columns</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">batch_size</span><span class="o">=</span><span class="default_value">65536</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet.html#ParquetFile.scan_contents"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.scan_contents" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Read contents of file for the given columns and batch size.</p> |
| <p class="rubric">Notes</p> |
| <p>This function’s primary purpose is benchmarking. |
| The scan is executed on a single thread.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>columns</strong> (<em>list of integers</em><em>, </em><em>default None</em>) – Select columns to read, if None scan all columns.</p></li> |
| <li><p><strong>batch_size</strong> (<em>int</em><em>, </em><em>default 64K</em>) – Number of rows to read at a time internally.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>num_rows</strong> (<em>number of rows in file</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.schema"> |
| <em class="property">property </em><code class="sig-name descname">schema</code><a class="headerlink" href="#pyarrow.parquet.ParquetFile.schema" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the Parquet schema, unconverted to Arrow types</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.parquet.ParquetFile.schema_arrow"> |
| <em class="property">property </em><code class="sig-name descname">schema_arrow</code><a class="headerlink" href="#pyarrow.parquet.ParquetFile.schema_arrow" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return the inferred Arrow schema, converted from the whole Parquet |
| file’s schema</p> |
| </dd></dl> |
| |
| </dd></dl> |
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