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| <section id="pyarrow-parquet-parquetfile"> |
| <h1>pyarrow.parquet.ParquetFile<a class="headerlink" href="#pyarrow-parquet-parquetfile" title="Permalink to this heading">#</a></h1> |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile"> |
| <em class="property"><span class="pre">class</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">ParquetFile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">source</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</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">common_metadata</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">read_dictionary</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">memory_map</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">buffer_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_buffer</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">coerce_int96_timestamp_unit</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">decryption_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">thrift_string_size_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">thrift_container_size_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">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">page_checksum_verification</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile" title="Permalink 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 v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p> |
| <p>Reader interface for a single Parquet file.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>source</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path" title="(in Python v3.12)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pathlib.Path</span></code></a>, <a class="reference internal" href="pyarrow.NativeFile.html#pyarrow.NativeFile" title="pyarrow.NativeFile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.NativeFile</span></code></a>, or file-like object</span></dt><dd><p>Readable source. For passing bytes or buffer-like file containing a |
| Parquet file, use pyarrow.BufferReader.</p> |
| </dd> |
| <dt><strong>metadata</strong><span class="classifier"><a class="reference internal" href="pyarrow.parquet.FileMetaData.html#pyarrow.parquet.FileMetaData" title="pyarrow.parquet.FileMetaData"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileMetaData</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Use existing metadata object, rather than reading from file.</p> |
| </dd> |
| <dt><strong>common_metadata</strong><span class="classifier"><a class="reference internal" href="pyarrow.parquet.FileMetaData.html#pyarrow.parquet.FileMetaData" title="pyarrow.parquet.FileMetaData"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileMetaData</span></code></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>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> |
| </dd> |
| <dt><strong>read_dictionary</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>List of column names to read directly as DictionaryArray.</p> |
| </dd> |
| <dt><strong>memory_map</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If the source is a file path, use a memory map to read file, which can |
| improve performance in some environments.</p> |
| </dd> |
| <dt><strong>buffer_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 0</span></dt><dd><p>If positive, perform read buffering when deserializing individual |
| column chunks. Otherwise IO calls are unbuffered.</p> |
| </dd> |
| <dt><strong>pre_buffer</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Coalesce and issue file reads in parallel to improve performance on |
| high-latency filesystems (e.g. S3). If True, Arrow will use a |
| background I/O thread pool.</p> |
| </dd> |
| <dt><strong>coerce_int96_timestamp_unit</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Cast timestamps that are stored in INT96 format to a particular |
| resolution (e.g. ‘ms’). Setting to None is equivalent to ‘ns’ |
| and therefore INT96 timestamps will be inferred as timestamps |
| in nanoseconds.</p> |
| </dd> |
| <dt><strong>decryption_properties</strong><span class="classifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileDecryptionProperties</span></code>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>File decryption properties for Parquet Modular Encryption.</p> |
| </dd> |
| <dt><strong>thrift_string_size_limit</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>If not None, override the maximum total string size allocated |
| when decoding Thrift structures. The default limit should be |
| sufficient for most Parquet files.</p> |
| </dd> |
| <dt><strong>thrift_container_size_limit</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>If not None, override the maximum total size of containers allocated |
| when decoding Thrift structures. The default limit should be |
| sufficient for most Parquet files.</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 v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>If nothing passed, will be inferred based on path. |
| Path will try to be found in the local on-disk filesystem otherwise |
| it will be parsed as an URI to determine the filesystem.</p> |
| </dd> |
| <dt><strong>page_checksum_verification</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If True, verify the checksum for each page read from the file.</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <p>Generate an example PyArrow Table and write it to Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Create a <code class="docutils literal notranslate"><span class="pre">ParquetFile</span></code> object from the Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Read the data:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">parquet_file</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[2,2,4,4,5,100]]</span> |
| <span class="go">animal: [["Flamingo","Parrot","Dog","Horse","Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| <p>Create a ParquetFile object with “animal” column as DictionaryArray:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">,</span> |
| <span class="gp">... </span> <span class="n">read_dictionary</span><span class="o">=</span><span class="p">[</span><span class="s2">"animal"</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: dictionary<values=string, indices=int32, ordered=0></span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[2,2,4,4,5,100]]</span> |
| <span class="go">animal: [ -- dictionary:</span> |
| <span class="go">["Flamingo","Parrot",...,"Brittle stars","Centipede"] -- indices:</span> |
| <span class="go">[0,1,2,3,4,5]]</span> |
| </pre></div> |
| </div> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.__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">source</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</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">common_metadata</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">read_dictionary</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">memory_map</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">buffer_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_buffer</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">coerce_int96_timestamp_unit</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">decryption_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">thrift_string_size_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">thrift_container_size_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">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">page_checksum_verification</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.__init__"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.__init__" title="Permalink to this definition">#</a></dt> |
| <dd></dd></dl> |
| |
| <p class="rubric">Methods</p> |
| <table class="autosummary longtable table autosummary"> |
| <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></p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.close" title="pyarrow.parquet.ParquetFile.close"><code class="xref py py-obj docutils literal notranslate"><span class="pre">close</span></code></a>([force])</p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.iter_batches" title="pyarrow.parquet.ParquetFile.iter_batches"><code class="xref py py-obj docutils literal notranslate"><span class="pre">iter_batches</span></code></a>([batch_size, row_groups, ...])</p></td> |
| <td><p>Read streaming batches from a Parquet file.</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="autosummary longtable table autosummary"> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.parquet.ParquetFile.closed" title="pyarrow.parquet.ParquetFile.closed"><code class="xref py py-obj docutils literal notranslate"><span class="pre">closed</span></code></a></p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-even"><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>Return the Parquet metadata.</p></td> |
| </tr> |
| <tr class="row-odd"><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>Return the number of row groups of the Parquet file.</p></td> |
| </tr> |
| <tr class="row-even"><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-odd"><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 class="sig sig-object py" id="pyarrow.parquet.ParquetFile.close"> |
| <span class="sig-name descname"><span class="pre">close</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.close"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.close" title="Permalink to this definition">#</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.closed"> |
| <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">closed</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyarrow.parquet.ParquetFile.closed" title="Permalink to this definition">#</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.iter_batches"> |
| <span class="sig-name descname"><span class="pre">iter_batches</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">65536</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">row_groups</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">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">use_threads</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_pandas_metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.iter_batches"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.parquet.ParquetFile.iter_batches" title="Permalink to this definition">#</a></dt> |
| <dd><p>Read streaming batches from a 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_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 64K</span></dt><dd><p>Maximum number of records to yield per batch. Batches may be |
| smaller if there aren’t enough rows in the file.</p> |
| </dd> |
| <dt><strong>row_groups</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>Only these row groups will be read from the file.</p> |
| </dd> |
| <dt><strong>columns</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>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> |
| </dd> |
| <dt><strong>use_threads</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Perform multi-threaded column reads.</p> |
| </dd> |
| <dt><strong>use_pandas_metadata</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Yields<span class="colon">:</span></dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt><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">pyarrow.RecordBatch</span></code></a></dt><dd><p>Contents of each batch as a record batch</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <p>Generate an example Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">parquet_file</span><span class="o">.</span><span class="n">iter_batches</span><span class="p">():</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="s2">"RecordBatch"</span><span class="p">)</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">to_pandas</span><span class="p">())</span> |
| <span class="gp">...</span> |
| <span class="go">RecordBatch</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> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.metadata"> |
| <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">metadata</span></span><a class="headerlink" href="#pyarrow.parquet.ParquetFile.metadata" title="Permalink to this definition">#</a></dt> |
| <dd><p>Return the Parquet metadata.</p> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.num_row_groups"> |
| <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">num_row_groups</span></span><a class="headerlink" href="#pyarrow.parquet.ParquetFile.num_row_groups" title="Permalink to this definition">#</a></dt> |
| <dd><p>Return the number of row groups of the Parquet file.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</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">parquet_file</span><span class="o">.</span><span class="n">num_row_groups</span> |
| <span class="go">1</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.read"> |
| <span class="sig-name descname"><span class="pre">read</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">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">use_threads</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_pandas_metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.read"><span class="viewcode-link"><span class="pre">[source]</span></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"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>columns</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>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> |
| </dd> |
| <dt><strong>use_threads</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Perform multi-threaded column reads.</p> |
| </dd> |
| <dt><strong>use_pandas_metadata</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.table.Table</span></code></dt><dd><p>Content of the file as a table (of columns).</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <p>Generate an example Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Read a Table:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">parquet_file</span><span class="o">.</span><span class="n">read</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"animal"</span><span class="p">])</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">animal: [["Flamingo","Parrot",...,"Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.read_row_group"> |
| <span class="sig-name descname"><span class="pre">read_row_group</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">i</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">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">use_threads</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_pandas_metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.read_row_group"><span class="viewcode-link"><span class="pre">[source]</span></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"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>i</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a></span></dt><dd><p>Index of the individual row group that we want to read.</p> |
| </dd> |
| <dt><strong>columns</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>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> |
| </dd> |
| <dt><strong>use_threads</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Perform multi-threaded column reads.</p> |
| </dd> |
| <dt><strong>use_pandas_metadata</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.table.Table</span></code></dt><dd><p>Content of the row group as a table (of columns)</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</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">parquet_file</span><span class="o">.</span><span class="n">read_row_group</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[2,2,4,4,5,100]]</span> |
| <span class="go">animal: [["Flamingo","Parrot",...,"Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.read_row_groups"> |
| <span class="sig-name descname"><span class="pre">read_row_groups</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">row_groups</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">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">use_threads</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_pandas_metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.read_row_groups"><span class="viewcode-link"><span class="pre">[source]</span></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"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>row_groups</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>Only these row groups will be read from the file.</p> |
| </dd> |
| <dt><strong>columns</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a></span></dt><dd><p>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> |
| </dd> |
| <dt><strong>use_threads</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Perform multi-threaded column reads.</p> |
| </dd> |
| <dt><strong>use_pandas_metadata</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.12)"><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 v3.12)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>If True and file has custom pandas schema metadata, ensure that |
| index columns are also loaded.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.table.Table</span></code></dt><dd><p>Content of the row groups as a table (of columns).</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</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">parquet_file</span><span class="o">.</span><span class="n">read_row_groups</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">])</span> |
| <span class="go">pyarrow.Table</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| <span class="go">----</span> |
| <span class="go">n_legs: [[2,2,4,4,5,...,2,4,4,5,100]]</span> |
| <span class="go">animal: [["Flamingo","Parrot","Dog",...,"Brittle stars","Centipede"]]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.scan_contents"> |
| <span class="sig-name descname"><span class="pre">scan_contents</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">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">batch_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">65536</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/parquet/core.html#ParquetFile.scan_contents"><span class="viewcode-link"><span class="pre">[source]</span></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> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>columns</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of <code class="xref py py-obj docutils literal notranslate"><span class="pre">integers</span></code>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Select columns to read, if None scan all columns.</p> |
| </dd> |
| <dt><strong>batch_size</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 64K</span></dt><dd><p>Number of rows to read at a time internally.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><dl> |
| <dt><strong>num_rows</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a></span></dt><dd><p>Number of rows in file</p> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Notes</p> |
| <p>This function’s primary purpose is benchmarking. |
| The scan is executed on a single thread.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</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">parquet_file</span><span class="o">.</span><span class="n">scan_contents</span><span class="p">()</span> |
| <span class="go">6</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
| <dl class="py property"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.schema"> |
| <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">schema</span></span><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 property"> |
| <dt class="sig sig-object py" id="pyarrow.parquet.ParquetFile.schema_arrow"> |
| <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">schema_arrow</span></span><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> |
| <p class="rubric">Examples</p> |
| <p>Generate an example Parquet file:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</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="kn">import</span> <span class="nn">pyarrow.parquet</span> <span class="k">as</span> <span class="nn">pq</span> |
| <span class="gp">>>> </span><span class="n">pq</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="s1">'example.parquet'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">parquet_file</span> <span class="o">=</span> <span class="n">pq</span><span class="o">.</span><span class="n">ParquetFile</span><span class="p">(</span><span class="s1">'example.parquet'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Read the Arrow schema:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">parquet_file</span><span class="o">.</span><span class="n">schema_arrow</span> |
| <span class="go">n_legs: int64</span> |
| <span class="go">animal: string</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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