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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_uint32.html">pyarrow.types.is_uint32</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_uint64.html">pyarrow.types.is_uint64</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_floating.html">pyarrow.types.is_floating</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_float32.html">pyarrow.types.is_float32</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_date64.html">pyarrow.types.is_date64</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_time32.html">pyarrow.types.is_time32</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.is_time64.html">pyarrow.types.is_time64</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.types.TypesEnum.html">pyarrow.types.TypesEnum</a></li> |
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| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/arrays.html">Arrays and Scalars</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.array.html">pyarrow.array</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Int8Array.html">pyarrow.Int8Array</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Int16Array.html">pyarrow.Int16Array</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.DictionaryScalar.html">pyarrow.DictionaryScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ListScalar.html">pyarrow.ListScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.FixedSizeListScalar.html">pyarrow.FixedSizeListScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.LargeListScalar.html">pyarrow.LargeListScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.MapScalar.html">pyarrow.MapScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.StructScalar.html">pyarrow.StructScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.UnionScalar.html">pyarrow.UnionScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ExtensionScalar.html">pyarrow.ExtensionScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.FixedShapeTensorScalar.html">pyarrow.FixedShapeTensorScalar</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.JsonScalar.html">pyarrow.JsonScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.UuidScalar.html">pyarrow.UuidScalar</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Bool8Scalar.html">pyarrow.Bool8Scalar</a></li> |
| </ul> |
| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/memory.html">Buffers and Memory</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.allocate_buffer.html">pyarrow.allocate_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.py_buffer.html">pyarrow.py_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.foreign_buffer.html">pyarrow.foreign_buffer</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.Buffer.html">pyarrow.Buffer</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.compress.html">pyarrow.compress</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.decompress.html">pyarrow.decompress</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.MemoryPool.html">pyarrow.MemoryPool</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.default_memory_pool.html">pyarrow.default_memory_pool</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.compute.ascii_rpad.html">pyarrow.compute.ascii_rpad</a></li> |
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| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/acero.html">Acero - Streaming Execution Engine</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| </ul> |
| </details></li> |
| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/substrait.html">Substrait</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.substrait.deserialize_expressions.html">pyarrow.substrait.deserialize_expressions</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.substrait.serialize_expressions.html">pyarrow.substrait.serialize_expressions</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ipc.new_stream.html">pyarrow.ipc.new_stream</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ipc.open_stream.html">pyarrow.ipc.open_stream</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.ipc.read_tensor.html">pyarrow.ipc.read_tensor</a></li> |
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| <li class="toctree-l3 has-children"><a class="reference internal" href="../api/flight.html">Arrow Flight</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.GcsFileSystem.html">pyarrow.fs.GcsFileSystem</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.AzureFileSystem.html">pyarrow.fs.AzureFileSystem</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.PyFileSystem.html">pyarrow.fs.PyFileSystem</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.copy_files.html">pyarrow.fs.copy_files</a></li> |
| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.initialize_s3.html">pyarrow.fs.initialize_s3</a></li> |
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| <li class="toctree-l4"><a class="reference internal" href="pyarrow.fs.S3LogLevel.html">pyarrow.fs.S3LogLevel</a></li> |
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| <li class="toctree-l3 current active has-children"><a class="reference internal" href="../api/dataset.html">Dataset</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul class="current"> |
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| <section id="pyarrow-dataset-write-dataset"> |
| <h1>pyarrow.dataset.write_dataset<a class="headerlink" href="#pyarrow-dataset-write-dataset" title="Link to this heading">#</a></h1> |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="pyarrow.dataset.write_dataset"> |
| <span class="sig-prename descclassname"><span class="pre">pyarrow.dataset.</span></span><span class="sig-name descname"><span class="pre">write_dataset</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">base_dir</span></span></em>, <em class="sig-param"><span class="keyword-only-separator o"><abbr title="Keyword-only parameters separator (PEP 3102)"><span class="pre">*</span></abbr></span></em>, <em class="sig-param"><span class="n"><span class="pre">basename_template</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">format</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">partitioning</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">partitioning_flavor</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schema</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">file_options</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">preserve_order</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">max_partitions</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">max_open_files</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">max_rows_per_file</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">min_rows_per_group</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">max_rows_per_group</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">file_visitor</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">existing_data_behavior</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'error'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">create_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/pyarrow/dataset.html#write_dataset"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyarrow.dataset.write_dataset" title="Link to this definition">#</a></dt> |
| <dd><p>Write a dataset to a given format and partitioning.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>data</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.Dataset.html#pyarrow.dataset.Dataset" title="pyarrow.dataset.Dataset"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Dataset</span></code></a>, Table/RecordBatch, RecordBatchReader, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a> of Table/RecordBatch, or <a class="reference external" href="https://docs.python.org/3/glossary.html#term-iterable" title="(in Python v3.13)"><span>iterable</span></a> of <a class="reference internal" href="pyarrow.RecordBatch.html#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RecordBatch</span></code></a></span></dt><dd><p>The data to write. This can be a Dataset instance or |
| in-memory Arrow data. If an iterable is given, the schema must |
| also be given.</p> |
| </dd> |
| <dt><strong>base_dir</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a></span></dt><dd><p>The root directory where to write the dataset.</p> |
| </dd> |
| <dt><strong>basename_template</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, optional</span></dt><dd><p>A template string used to generate basenames of written data files. |
| The token ‘{i}’ will be replaced with an automatically incremented |
| integer. If not specified, it defaults to |
| “part-{i}.” + format.default_extname</p> |
| </dd> |
| <dt><strong>format</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.FileFormat.html#pyarrow.dataset.FileFormat" title="pyarrow.dataset.FileFormat"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FileFormat</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a></span></dt><dd><p>The format in which to write the dataset. Currently supported: |
| “parquet”, “ipc”/”arrow”/”feather”, and “csv”. If a FileSystemDataset |
| is being written and <cite>format</cite> is not specified, it defaults to the |
| same format as the specified FileSystemDataset. When writing a |
| Table or RecordBatch, this keyword is required.</p> |
| </dd> |
| <dt><strong>partitioning</strong><span class="classifier"><a class="reference internal" href="pyarrow.dataset.Partitioning.html#pyarrow.dataset.Partitioning" title="pyarrow.dataset.Partitioning"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Partitioning</span></code></a> or <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">list</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>], optional</span></dt><dd><p>The partitioning scheme specified with the <code class="docutils literal notranslate"><span class="pre">partitioning()</span></code> |
| function or a list of field names. When providing a list of |
| field names, you can use <code class="docutils literal notranslate"><span class="pre">partitioning_flavor</span></code> to drive which |
| partitioning type should be used.</p> |
| </dd> |
| <dt><strong>partitioning_flavor</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">str</span></code></a>, optional</span></dt><dd><p>One of the partitioning flavors supported by |
| <code class="docutils literal notranslate"><span class="pre">pyarrow.dataset.partitioning</span></code>. If omitted will use the |
| default of <code class="docutils literal notranslate"><span class="pre">partitioning()</span></code> which is directory partitioning.</p> |
| </dd> |
| <dt><strong>schema</strong><span class="classifier"><a class="reference internal" href="pyarrow.Schema.html#pyarrow.Schema" title="pyarrow.Schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Schema</span></code></a>, optional</span></dt><dd></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>, optional</span></dt><dd></dd> |
| <dt><strong>file_options</strong><span class="classifier"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.dataset.FileWriteOptions</span></code>, optional</span></dt><dd><p>FileFormat specific write options, created using the |
| <code class="docutils literal notranslate"><span class="pre">FileFormat.make_write_options()</span></code> function.</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 v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Write files in parallel. If enabled, then maximum parallelism will be |
| used determined by the number of available CPU cores. Using multiple |
| threads may change the order of rows in the written dataset if |
| preserve_order is set to False.</p> |
| </dd> |
| <dt><strong>preserve_order</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#False" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">False</span></code></a></span></dt><dd><p>Preserve the order of rows. If enabled, order of rows in the dataset are |
| guaranteed to be preserved even if use_threads is set to True. This may |
| cause notable performance degradation.</p> |
| </dd> |
| <dt><strong>max_partitions</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 1024</span></dt><dd><p>Maximum number of partitions any batch may be written into.</p> |
| </dd> |
| <dt><strong>max_open_files</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 1024</span></dt><dd><p>If greater than 0 then this will limit the maximum number of |
| files that can be left open. If an attempt is made to open |
| too many files then the least recently used file will be closed. |
| If this setting is set too low you may end up fragmenting your |
| data into many small files.</p> |
| </dd> |
| <dt><strong>max_rows_per_file</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 0</span></dt><dd><p>Maximum number of rows per file. If greater than 0 then this will |
| limit how many rows are placed in any single file. Otherwise there |
| will be no limit and one file will be created in each output |
| directory unless files need to be closed to respect max_open_files</p> |
| </dd> |
| <dt><strong>min_rows_per_group</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 0</span></dt><dd><p>Minimum number of rows per group. When the value is greater than 0, |
| the dataset writer will batch incoming data and only write the row |
| groups to the disk when sufficient rows have accumulated.</p> |
| </dd> |
| <dt><strong>max_rows_per_group</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, default 1024 * 1024</span></dt><dd><p>Maximum number of rows per group. If the value is greater than 0, |
| then the dataset writer may split up large incoming batches into |
| multiple row groups. If this value is set, then min_rows_per_group |
| should also be set. Otherwise it could end up with very small row |
| groups.</p> |
| </dd> |
| <dt><strong>file_visitor</strong><span class="classifier">function</span></dt><dd><p>If set, this function will be called with a WrittenFile instance |
| for each file created during the call. This object will have both |
| a path attribute and a metadata attribute.</p> |
| <p>The path attribute will be a string containing the path to |
| the created file.</p> |
| <p>The metadata attribute will be the parquet metadata of the file. |
| This metadata will have the file path attribute set and can be used |
| to build a _metadata file. The metadata attribute will be None if |
| the format is not parquet.</p> |
| <p>Example visitor which simple collects the filenames created:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">visited_paths</span> <span class="o">=</span> <span class="p">[]</span> |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">file_visitor</span><span class="p">(</span><span class="n">written_file</span><span class="p">):</span> |
| <span class="n">visited_paths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">written_file</span><span class="o">.</span><span class="n">path</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </dd> |
| <dt><strong>existing_data_behavior</strong><span class="classifier">‘error’ | ‘overwrite_or_ignore’ | ‘delete_matching’</span></dt><dd><p>Controls how the dataset will handle data that already exists in |
| the destination. The default behavior (‘error’) is to raise an error |
| if any data exists in the destination.</p> |
| <p>‘overwrite_or_ignore’ will ignore any existing data and will |
| overwrite files with the same name as an output file. Other |
| existing files will be ignored. This behavior, in combination |
| with a unique basename_template for each write, will allow for |
| an append workflow.</p> |
| <p>‘delete_matching’ is useful when you are writing a partitioned |
| dataset. The first time each partition directory is encountered |
| the entire directory will be deleted. This allows you to overwrite |
| old partitions completely.</p> |
| </dd> |
| <dt><strong>create_dir</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.13)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>If False, directories will not be created. This can be useful for |
| filesystems that do not require directories.</p> |
| </dd> |
| </dl> |
| </dd> |
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