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From w...@apache.org
Subject [19/30] arrow-site git commit: Update Python and GLib API docs for 0.6.0
Date Wed, 16 Aug 2017 21:33:13 GMT
http://git-wip-us.apache.org/repos/asf/arrow-site/blob/4d4a3202/docs/python/api.html
----------------------------------------------------------------------
diff --git a/docs/python/api.html b/docs/python/api.html
index a35a846..35d537e 100644
--- a/docs/python/api.html
+++ b/docs/python/api.html
@@ -73,7 +73,8 @@
 <li class="toctree-l1"><a class="reference internal" href="memory.html">Memory
and IO Interfaces</a></li>
 <li class="toctree-l1"><a class="reference internal" href="data.html">In-Memory
Data Model</a></li>
 <li class="toctree-l1"><a class="reference internal" href="ipc.html">IPC: Fast
Streaming and Serialization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="filesystems.html">Filesystem
Interfaces</a></li>
+<li class="toctree-l1"><a class="reference internal" href="filesystems.html">File
System Interfaces</a></li>
+<li class="toctree-l1"><a class="reference internal" href="plasma.html">The Plasma
In-Memory Object Store</a></li>
 <li class="toctree-l1"><a class="reference internal" href="pandas.html">Using
PyArrow with pandas</a></li>
 <li class="toctree-l1"><a class="reference internal" href="parquet.html">Reading
and Writing the Apache Parquet Format</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">API
Reference</a></li>
@@ -94,13 +95,15 @@
 <li><a class="reference internal" href="#">API Reference</a><ul>
 <li><a class="reference internal" href="#type-and-schema-factory-functions">Type
and Schema Factory Functions</a></li>
 <li><a class="reference internal" href="#scalar-value-types">Scalar Value Types</a></li>
-<li><a class="reference internal" href="#array-types-and-constructors">Array
Types and Constructors</a></li>
+<li><a class="reference internal" href="#array-types">Array Types</a></li>
 <li><a class="reference internal" href="#tables-and-record-batches">Tables and
Record Batches</a></li>
 <li><a class="reference internal" href="#tensor-type-and-functions">Tensor type
and Functions</a></li>
 <li><a class="reference internal" href="#input-output-and-shared-memory">Input
/ Output and Shared Memory</a></li>
+<li><a class="reference internal" href="#file-systems">File Systems</a></li>
 <li><a class="reference internal" href="#interprocess-communication-and-messaging">Interprocess
Communication and Messaging</a></li>
 <li><a class="reference internal" href="#memory-pools">Memory Pools</a></li>
 <li><a class="reference internal" href="#type-classes">Type Classes</a></li>
+<li><a class="reference internal" href="#in-memory-object-store">In-Memory Object
Store</a></li>
 <li><a class="reference internal" href="#apache-parquet">Apache Parquet</a></li>
 </ul>
 </li>
@@ -322,90 +325,87 @@
 </tbody>
 </table>
 </div>
-<div class="section" id="array-types-and-constructors">
-<span id="api-array"></span><h2>Array Types and Constructors<a class="headerlink"
href="#array-types-and-constructors" title="Permalink to this headline">¶</a></h2>
+<div class="section" id="array-types">
+<span id="api-array"></span><h2>Array Types<a class="headerlink" href="#array-types"
title="Permalink to this headline">¶</a></h2>
 <table border="1" class="longtable docutils">
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title="pyarrow.Array"><code class="xref py py-obj docutils literal"><span class="pre">Array</span></code></a></td>
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title="pyarrow.BooleanArray"><code class="xref py py-obj docutils literal"><span
class="pre">BooleanArray</span></code></a></td>
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title="pyarrow.TimestampArray"><code class="xref py py-obj docutils literal"><span
class="pre">TimestampArray</span></code></a></td>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.lib.TimestampArray.html#pyarrow.lib.TimestampArray"
title="pyarrow.lib.TimestampArray"><code class="xref py py-obj docutils literal"><span
class="pre">TimestampArray</span></code></a></td>
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-<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.DecimalArray.html#pyarrow.DecimalArray"
title="pyarrow.DecimalArray"><code class="xref py py-obj docutils literal"><span
class="pre">DecimalArray</span></code></a></td>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.lib.DecimalArray.html#pyarrow.lib.DecimalArray"
title="pyarrow.lib.DecimalArray"><code class="xref py py-obj docutils literal"><span
class="pre">DecimalArray</span></code></a></td>
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-<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.ListArray.html#pyarrow.ListArray"
title="pyarrow.ListArray"><code class="xref py py-obj docutils literal"><span
class="pre">ListArray</span></code></a></td>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.lib.ListArray.html#pyarrow.lib.ListArray"
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 <td></td>
 </tr>
 </tbody>
@@ -483,6 +483,28 @@
 </tbody>
 </table>
 </div>
+<div class="section" id="file-systems">
+<h2>File Systems<a class="headerlink" href="#file-systems" title="Permalink to this
headline">¶</a></h2>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.hdfs.connect.html#pyarrow.hdfs.connect"
title="pyarrow.hdfs.connect"><code class="xref py py-obj docutils literal"><span
class="pre">hdfs.connect</span></code></a>([host,&nbsp;port,&nbsp;user,&nbsp;...])</td>
+<td>Connect to an HDFS cluster.</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.LocalFileSystem.html#pyarrow.LocalFileSystem"
title="pyarrow.LocalFileSystem"><code class="xref py py-obj docutils literal"><span
class="pre">LocalFileSystem</span></code></a></td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<dl class="class">
+<dt>
+<em class="property">class </em><code class="descclassname">pyarrow.</code><code
class="descname">HadoopFileSystem</code><a class="reference internal" href="_modules/pyarrow/hdfs.html#HadoopFileSystem"><span
class="viewcode-link">[source]</span></a></dt>
+<dd></dd></dl>
+
+</div>
 <div class="section" id="interprocess-communication-and-messaging">
 <span id="api-ipc"></span><h2>Interprocess Communication and Messaging<a
class="headerlink" href="#interprocess-communication-and-messaging" title="Permalink to this
headline">¶</a></h2>
 <table border="1" class="longtable docutils">
@@ -567,18 +589,38 @@
 <col width="90%" />
 </colgroup>
 <tbody valign="top">
-<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.DataType.html#pyarrow.DataType"
title="pyarrow.DataType"><code class="xref py py-obj docutils literal"><span class="pre">DataType</span></code></a></td>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.lib.DataType.html#pyarrow.lib.DataType"
title="pyarrow.lib.DataType"><code class="xref py py-obj docutils literal"><span
class="pre">DataType</span></code></a></td>
 <td>Base type for Apache Arrow data type instances.</td>
 </tr>
-<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.Field.html#pyarrow.Field"
title="pyarrow.Field"><code class="xref py py-obj docutils literal"><span class="pre">Field</span></code></a></td>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.lib.Field.html#pyarrow.lib.Field"
title="pyarrow.lib.Field"><code class="xref py py-obj docutils literal"><span
class="pre">Field</span></code></a></td>
 <td>Represents a named field, with a data type, nullability, and optional</td>
 </tr>
-<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.Schema.html#pyarrow.Schema"
title="pyarrow.Schema"><code class="xref py py-obj docutils literal"><span class="pre">Schema</span></code></a></td>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.lib.Schema.html#pyarrow.lib.Schema"
title="pyarrow.lib.Schema"><code class="xref py py-obj docutils literal"><span
class="pre">Schema</span></code></a></td>
 <td></td>
 </tr>
 </tbody>
 </table>
 </div>
+<div class="section" id="in-memory-object-store">
+<span id="api-plasma"></span><h2>In-Memory Object Store<a class="headerlink"
href="#in-memory-object-store" title="Permalink to this headline">¶</a></h2>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.plasma.ObjectID.html#pyarrow.plasma.ObjectID"
title="pyarrow.plasma.ObjectID"><code class="xref py py-obj docutils literal"><span
class="pre">ObjectID</span></code></a></td>
+<td>An ObjectID represents a string of bytes used to identify Plasma objects.</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.plasma.PlasmaClient.html#pyarrow.plasma.PlasmaClient"
title="pyarrow.plasma.PlasmaClient"><code class="xref py py-obj docutils literal"><span
class="pre">PlasmaClient</span></code></a></td>
+<td>The PlasmaClient is used to interface with a plasma store and manager.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.plasma.PlasmaBuffer.html#pyarrow.plasma.PlasmaBuffer"
title="pyarrow.plasma.PlasmaBuffer"><code class="xref py py-obj docutils literal"><span
class="pre">PlasmaBuffer</span></code></a></td>
+<td>This is the type returned by calls to get with a PlasmaClient.</td>
+</tr>
+</tbody>
+</table>
+</div>
 <div class="section" id="apache-parquet">
 <span id="api-parquet"></span><h2>Apache Parquet<a class="headerlink"
href="#apache-parquet" title="Permalink to this headline">¶</a></h2>
 <table border="1" class="longtable docutils">
@@ -590,16 +632,25 @@
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title="pyarrow.parquet.ParquetDataset"><code class="xref py py-obj docutils literal"><span
class="pre">ParquetDataset</span></code></a>(path_or_paths[,&nbsp;filesystem,&nbsp;...])</td>
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 </tr>
-<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.ParquetFile.html#pyarrow.parquet.ParquetFile"
title="pyarrow.parquet.ParquetFile"><code class="xref py py-obj docutils literal"><span
class="pre">ParquetFile</span></code></a>(source[,&nbsp;metadata])</td>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.ParquetFile.html#pyarrow.parquet.ParquetFile"
title="pyarrow.parquet.ParquetFile"><code class="xref py py-obj docutils literal"><span
class="pre">ParquetFile</span></code></a>(source[,&nbsp;metadata,&nbsp;common_metadata])</td>
 <td>Reader interface for a single Parquet file</td>
 </tr>
-<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.parquet.read_table.html#pyarrow.parquet.read_table"
title="pyarrow.parquet.read_table"><code class="xref py py-obj docutils literal"><span
class="pre">read_table</span></code></a>(source[,&nbsp;columns,&nbsp;nthreads,&nbsp;metadata])</td>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.parquet.read_table.html#pyarrow.parquet.read_table"
title="pyarrow.parquet.read_table"><code class="xref py py-obj docutils literal"><span
class="pre">read_table</span></code></a>(source[,&nbsp;columns,&nbsp;nthreads,&nbsp;...])</td>
 <td>Read a Table from Parquet format</td>
 </tr>
-<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.write_metadata.html#pyarrow.parquet.write_metadata"
title="pyarrow.parquet.write_metadata"><code class="xref py py-obj docutils literal"><span
class="pre">write_metadata</span></code></a>(schema,&nbsp;where[,&nbsp;version])</td>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.read_metadata.html#pyarrow.parquet.read_metadata"
title="pyarrow.parquet.read_metadata"><code class="xref py py-obj docutils literal"><span
class="pre">read_metadata</span></code></a>(where)</td>
+<td>Read FileMetadata from footer of a single Parquet file</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.parquet.read_pandas.html#pyarrow.parquet.read_pandas"
title="pyarrow.parquet.read_pandas"><code class="xref py py-obj docutils literal"><span
class="pre">read_pandas</span></code></a>(source[,&nbsp;columns,&nbsp;nthreads,&nbsp;...])</td>
+<td>Read a Table from Parquet format, also reading DataFrame index values if</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.read_schema.html#pyarrow.parquet.read_schema"
title="pyarrow.parquet.read_schema"><code class="xref py py-obj docutils literal"><span
class="pre">read_schema</span></code></a>(where)</td>
+<td>Read effective Arrow schema from Parquet file metadata</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.parquet.write_metadata.html#pyarrow.parquet.write_metadata"
title="pyarrow.parquet.write_metadata"><code class="xref py py-obj docutils literal"><span
class="pre">write_metadata</span></code></a>(schema,&nbsp;where[,&nbsp;version,&nbsp;...])</td>
 <td>Write metadata-only Parquet file from schema</td>
 </tr>
-<tr class="row-odd"><td><a class="reference internal" href="generated/pyarrow.parquet.write_table.html#pyarrow.parquet.write_table"
title="pyarrow.parquet.write_table"><code class="xref py py-obj docutils literal"><span
class="pre">write_table</span></code></a>(table,&nbsp;where[,&nbsp;row_group_size,&nbsp;...])</td>
+<tr class="row-even"><td><a class="reference internal" href="generated/pyarrow.parquet.write_table.html#pyarrow.parquet.write_table"
title="pyarrow.parquet.write_table"><code class="xref py py-obj docutils literal"><span
class="pre">write_table</span></code></a>(table,&nbsp;where[,&nbsp;row_group_size,&nbsp;...])</td>
 <td>Write a Table to Parquet format</td>
 </tr>
 </tbody>

http://git-wip-us.apache.org/repos/asf/arrow-site/blob/4d4a3202/docs/python/data.html
----------------------------------------------------------------------
diff --git a/docs/python/data.html b/docs/python/data.html
index fe35ea3..f60fe3c 100644
--- a/docs/python/data.html
+++ b/docs/python/data.html
@@ -73,7 +73,8 @@
 <li class="toctree-l1"><a class="reference internal" href="memory.html">Memory
and IO Interfaces</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">In-Memory
Data Model</a></li>
 <li class="toctree-l1"><a class="reference internal" href="ipc.html">IPC: Fast
Streaming and Serialization</a></li>
-<li class="toctree-l1"><a class="reference internal" href="filesystems.html">Filesystem
Interfaces</a></li>
+<li class="toctree-l1"><a class="reference internal" href="filesystems.html">File
System Interfaces</a></li>
+<li class="toctree-l1"><a class="reference internal" href="plasma.html">The Plasma
In-Memory Object Store</a></li>
 <li class="toctree-l1"><a class="reference internal" href="pandas.html">Using
PyArrow with pandas</a></li>
 <li class="toctree-l1"><a class="reference internal" href="parquet.html">Reading
and Writing the Apache Parquet Format</a></li>
 <li class="toctree-l1"><a class="reference internal" href="api.html">API Reference</a></li>
@@ -215,7 +216,7 @@ same for one or more types. For example, <code class="docutils literal"><span
cl
 <p>These objects are <cite>metadata</cite>; they are used for describing
the data in arrays,
 schemas, and record batches. In Python, they can be used in functions where the
 input data (e.g. Python objects) may be coerced to more than one Arrow type.</p>
-<p>The <a class="reference internal" href="generated/pyarrow.Field.html#pyarrow.Field"
title="pyarrow.Field"><code class="xref py py-class docutils literal"><span class="pre">Field</span></code></a>
type is a type plus a name and optional
+<p>The <code class="xref py py-class docutils literal"><span class="pre">Field</span></code>
type is a type plus a name and optional
 user-defined metadata:</p>
 <div class="highlight-ipython"><div class="highlight"><pre><span></span><span
class="gp">In [11]: </span><span class="n">f0</span> <span class="o">=</span>
<span class="n">pa</span><span class="o">.</span><span class="n">field</span><span
class="p">(</span><span class="s1">&#39;int32_field&#39;</span><span
class="p">,</span> <span class="n">t1</span><span class="p">)</span>
 
@@ -258,7 +259,7 @@ functions.</p>
 </div>
 <div class="section" id="schemas">
 <span id="data-schema"></span><h2>Schemas<a class="headerlink" href="#schemas"
title="Permalink to this headline">¶</a></h2>
-<p>The <a class="reference internal" href="generated/pyarrow.Schema.html#pyarrow.Schema"
title="pyarrow.Schema"><code class="xref py py-class docutils literal"><span class="pre">Schema</span></code></a>
type is similar to the <code class="docutils literal"><span class="pre">struct</span></code>
array type; it
+<p>The <code class="xref py py-class docutils literal"><span class="pre">Schema</span></code>
type is similar to the <code class="docutils literal"><span class="pre">struct</span></code>
array type; it
 defines the column names and types in a record batch or table data
 structure. The <code class="docutils literal"><span class="pre">pyarrow.schema</span></code>
factory function makes new Schema objects in
 Python:</p>
@@ -296,7 +297,7 @@ the <code class="docutils literal"><span class="pre">numpy.array</span></code>
f
 
 <span class="gp">In [24]: </span><span class="n">arr</span>
 <span class="gh">Out[24]: </span><span class="go"></span>
-<span class="go">&lt;pyarrow.lib.Int64Array object at 0x2b964178bb88&gt;</span>
+<span class="go">&lt;pyarrow.lib.Int64Array object at 0x7fdbf15f60e8&gt;</span>
 <span class="go">[</span>
 <span class="go">  1,</span>
 <span class="go">  2,</span>
@@ -351,7 +352,7 @@ in a file or stream to transmit integer <em>indices</em> referencing
a shared
 particularly often used with strings to save memory and improve performance.</p>
 <p>The way that dictionaries are handled in the Apache Arrow format and the way
 they appear in C++ and Python is slightly different. We define a special
-<a class="reference internal" href="generated/pyarrow.DictionaryArray.html#pyarrow.DictionaryArray"
title="pyarrow.DictionaryArray"><code class="xref py py-class docutils literal"><span
class="pre">DictionaryArray</span></code></a> type with a corresponding
dictionary type. Let&#8217;s
+<a class="reference internal" href="generated/pyarrow.lib.DictionaryArray.html#pyarrow.lib.DictionaryArray"
title="pyarrow.lib.DictionaryArray"><code class="xref py py-class docutils literal"><span
class="pre">DictionaryArray</span></code></a> type with a corresponding
dictionary type. Let&#8217;s
 consider an example:</p>
 <div class="highlight-ipython"><div class="highlight"><pre><span></span><span
class="gp">In [33]: </span><span class="n">indices</span> <span class="o">=</span>
<span class="n">pa</span><span class="o">.</span><span class="n">array</span><span
class="p">([</span><span class="mi">0</span><span class="p">,</span>
<span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span
class="p">,</span> <span class="mi">1</span><span class="p">,</span>
<span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span
class="p">,</span> <span class="bp">None</span><span class="p">,</span>
<span class="mi">2</span><span class="p">])</span>
 
@@ -361,7 +362,7 @@ consider an example:</p>
 
 <span class="gp">In [36]: </span><span class="n">dict_array</span>
 <span class="gh">Out[36]: </span><span class="go"></span>
-<span class="go">&lt;pyarrow.lib.DictionaryArray object at 0x2b96417ab6a8&gt;</span>
+<span class="go">&lt;pyarrow.lib.DictionaryArray object at 0x7fdbf1601588&gt;</span>
 <span class="go">[</span>
 <span class="go">  &#39;foo&#39;,</span>
 <span class="go">  &#39;bar&#39;,</span>
@@ -376,11 +377,11 @@ consider an example:</p>
 </div>
 <p>Here we have:</p>
 <div class="highlight-ipython"><div class="highlight"><pre><span></span><span
class="gp">In [37]: </span><span class="k">print</span><span class="p">(</span><span
class="n">dict_array</span><span class="o">.</span><span class="n">type</span><span
class="p">)</span>
-<span class="go">dictionary&lt;values=string, indices=int64&gt;</span>
+<span class="go">dictionary&lt;values=string, indices=int64, ordered=0&gt;</span>
 
 <span class="gp">In [38]: </span><span class="n">dict_array</span><span
class="o">.</span><span class="n">indices</span>
-<span class="go">
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