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| <article class="bd-article"> |
| |
| <section id="module-datafusion.io"> |
| <span id="datafusion-io"></span><h1>datafusion.io<a class="headerlink" href="#module-datafusion.io" title="Link to this heading">#</a></h1> |
| <p>IO read functions using global context.</p> |
| <section id="functions"> |
| <h2>Functions<a class="headerlink" href="#functions" title="Link to this heading">#</a></h2> |
| <div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary"> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#datafusion.io.read_avro" title="datafusion.io.read_avro"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_avro</span></code></a>(→ datafusion.dataframe.DataFrame)</p></td> |
| <td><p>Create a <code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code> for reading Avro data source.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#datafusion.io.read_csv" title="datafusion.io.read_csv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_csv</span></code></a>(→ datafusion.dataframe.DataFrame)</p></td> |
| <td><p>Read a CSV data source.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#datafusion.io.read_json" title="datafusion.io.read_json"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_json</span></code></a>(→ datafusion.dataframe.DataFrame)</p></td> |
| <td><p>Read a line-delimited JSON data source.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#datafusion.io.read_parquet" title="datafusion.io.read_parquet"><code class="xref py py-obj docutils literal notranslate"><span class="pre">read_parquet</span></code></a>(→ datafusion.dataframe.DataFrame)</p></td> |
| <td><p>Read a Parquet source into a <code class="xref py py-class docutils literal notranslate"><span class="pre">Dataframe</span></code>.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| </section> |
| <section id="module-contents"> |
| <h2>Module Contents<a class="headerlink" href="#module-contents" title="Link to this heading">#</a></h2> |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="datafusion.io.read_avro"> |
| <span class="sig-prename descclassname"><span class="pre">datafusion.io.</span></span><span class="sig-name descname"><span class="pre">read_avro</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pathlib.Path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pyarrow.Schema</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_partition_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pyarrow.DataType</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_extension</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'.avro'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="../dataframe/index.html#datafusion.dataframe.DataFrame" title="datafusion.dataframe.DataFrame"><span class="pre">datafusion.dataframe.DataFrame</span></a></span></span><a class="headerlink" href="#datafusion.io.read_avro" title="Link to this definition">#</a></dt> |
| <dd><p>Create a <code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code> for reading Avro data source.</p> |
| <p>This function will use the global context. Any functions or tables registered |
| with another context may not be accessible when used with a DataFrame created |
| using this function.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>path</strong> – Path to the Avro file.</p></li> |
| <li><p><strong>schema</strong> – The data source schema.</p></li> |
| <li><p><strong>file_partition_cols</strong> – Partition columns.</p></li> |
| <li><p><strong>file_extension</strong> – File extension to select.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><p>DataFrame representation of the read Avro file</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="datafusion.io.read_csv"> |
| <span class="sig-prename descclassname"><span class="pre">datafusion.io.</span></span><span class="sig-name descname"><span class="pre">read_csv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pathlib.Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">pathlib.Path</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pyarrow.Schema</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">has_header</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">delimiter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">','</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema_infer_max_records</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_extension</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'.csv'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">table_partition_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pyarrow.DataType</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_compression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">options</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../options/index.html#datafusion.options.CsvReadOptions" title="datafusion.options.CsvReadOptions"><span class="pre">datafusion.options.CsvReadOptions</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="../dataframe/index.html#datafusion.dataframe.DataFrame" title="datafusion.dataframe.DataFrame"><span class="pre">datafusion.dataframe.DataFrame</span></a></span></span><a class="headerlink" href="#datafusion.io.read_csv" title="Link to this definition">#</a></dt> |
| <dd><p>Read a CSV data source.</p> |
| <p>This function will use the global context. Any functions or tables registered |
| with another context may not be accessible when used with a DataFrame created |
| using this function.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>path</strong> – Path to the CSV file</p></li> |
| <li><p><strong>schema</strong> – An optional schema representing the CSV files. If None, the |
| CSV reader will try to infer it based on data in file.</p></li> |
| <li><p><strong>has_header</strong> – Whether the CSV file have a header. If schema inference |
| is run on a file with no headers, default column names are |
| created.</p></li> |
| <li><p><strong>delimiter</strong> – An optional column delimiter.</p></li> |
| <li><p><strong>schema_infer_max_records</strong> – Maximum number of rows to read from CSV |
| files for schema inference if needed.</p></li> |
| <li><p><strong>file_extension</strong> – File extension; only files with this extension are |
| selected for data input.</p></li> |
| <li><p><strong>table_partition_cols</strong> – Partition columns.</p></li> |
| <li><p><strong>file_compression_type</strong> – File compression type.</p></li> |
| <li><p><strong>options</strong> – Set advanced options for CSV reading. This cannot be |
| combined with any of the other options in this method.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><p>DataFrame representation of the read CSV files</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="datafusion.io.read_json"> |
| <span class="sig-prename descclassname"><span class="pre">datafusion.io.</span></span><span class="sig-name descname"><span class="pre">read_json</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pathlib.Path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pyarrow.Schema</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema_infer_max_records</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_extension</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'.json'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">table_partition_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pyarrow.DataType</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_compression_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="../dataframe/index.html#datafusion.dataframe.DataFrame" title="datafusion.dataframe.DataFrame"><span class="pre">datafusion.dataframe.DataFrame</span></a></span></span><a class="headerlink" href="#datafusion.io.read_json" title="Link to this definition">#</a></dt> |
| <dd><p>Read a line-delimited JSON data source.</p> |
| <p>This function will use the global context. Any functions or tables registered |
| with another context may not be accessible when used with a DataFrame created |
| using this function.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>path</strong> – Path to the JSON file.</p></li> |
| <li><p><strong>schema</strong> – The data source schema.</p></li> |
| <li><p><strong>schema_infer_max_records</strong> – Maximum number of rows to read from JSON |
| files for schema inference if needed.</p></li> |
| <li><p><strong>file_extension</strong> – File extension; only files with this extension are |
| selected for data input.</p></li> |
| <li><p><strong>table_partition_cols</strong> – Partition columns.</p></li> |
| <li><p><strong>file_compression_type</strong> – File compression type.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><p>DataFrame representation of the read JSON files.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="datafusion.io.read_parquet"> |
| <span class="sig-prename descclassname"><span class="pre">datafusion.io.</span></span><span class="sig-name descname"><span class="pre">read_parquet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pathlib.Path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">table_partition_cols</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">pyarrow.DataType</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parquet_pruning</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_extension</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'.parquet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">skip_metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pyarrow.Schema</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_sort_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="../expr/index.html#datafusion.expr.Expr" title="datafusion.expr.Expr"><span class="pre">datafusion.expr.Expr</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="../dataframe/index.html#datafusion.dataframe.DataFrame" title="datafusion.dataframe.DataFrame"><span class="pre">datafusion.dataframe.DataFrame</span></a></span></span><a class="headerlink" href="#datafusion.io.read_parquet" title="Link to this definition">#</a></dt> |
| <dd><p>Read a Parquet source into a <code class="xref py py-class docutils literal notranslate"><span class="pre">Dataframe</span></code>.</p> |
| <p>This function will use the global context. Any functions or tables registered |
| with another context may not be accessible when used with a DataFrame created |
| using this function.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>path</strong> – Path to the Parquet file.</p></li> |
| <li><p><strong>table_partition_cols</strong> – Partition columns.</p></li> |
| <li><p><strong>parquet_pruning</strong> – Whether the parquet reader should use the predicate |
| to prune row groups.</p></li> |
| <li><p><strong>file_extension</strong> – File extension; only files with this extension are |
| selected for data input.</p></li> |
| <li><p><strong>skip_metadata</strong> – Whether the parquet reader should skip any metadata |
| that may be in the file schema. This can help avoid schema |
| conflicts due to metadata.</p></li> |
| <li><p><strong>schema</strong> – An optional schema representing the parquet files. If None, |
| the parquet reader will try to infer it based on data in the |
| file.</p></li> |
| <li><p><strong>file_sort_order</strong> – Sort order for the file.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns<span class="colon">:</span></dt> |
| <dd class="field-even"><p>DataFrame representation of the read Parquet files</p> |
| </dd> |
| </dl> |
| </dd></dl> |
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