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updated built documentation
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Deep Ganguli committed Mar 5, 2014
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19 changes: 18 additions & 1 deletion docs/build/html/genindex.html
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Expand Up @@ -49,12 +49,29 @@ <h3>Navigation</h3>
<h1 id="index">Index</h1>

<div class="genindex-jumpbox">
<a href="#G"><strong>G</strong></a>
<a href="#E"><strong>E</strong></a>
| <a href="#G"><strong>G</strong></a>
| <a href="#P"><strong>P</strong></a>
| <a href="#S"><strong>S</strong></a>
| <a href="#T"><strong>T</strong></a>

</div>
<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%" valign="top"><dl>

<dt><a href="index.html#client.PyDruid.export_pandas">export_pandas() (client.PyDruid method)</a>
</dt>

</dl></td>
<td style="width: 33%" valign="top"><dl>

<dt><a href="index.html#client.PyDruid.export_tsv">export_tsv() (client.PyDruid method)</a>
</dt>

</dl></td>
</tr></table>

<h2 id="G">G</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
<td style="width: 33%" valign="top"><dl>
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230 changes: 227 additions & 3 deletions docs/build/html/index.html
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Expand Up @@ -54,7 +54,231 @@ <h1>Welcome to PyDruid&#8217;s documentation!<a class="headerlink" href="#welcom
<span class="target" id="module-pydruid"></span><dl class="class">
<dt id="client.PyDruid">
<em class="property">class </em><tt class="descclassname">client.</tt><tt class="descname">PyDruid</tt><big>(</big><em>url</em>, <em>endpoint</em><big>)</big><a class="headerlink" href="#client.PyDruid" title="Permalink to this definition"></a></dt>
<dd><dl class="method">
<dd><p>PyDruid exposes a simple API for creating and executing Druid queries. PyDruid also exposes
a method for exporting query results into pandas.DataFrame objects for subsequent analysis
with the python scientific computing stack, or simply exporting query results to a TSV file
for analysis with your favorite tool, e.g., R, Julia, Matlab, Excel.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>url</strong> (<em>str</em>) &#8211; URL of Bard node in the Druid cluster</li>
<li><strong>endpoint</strong> (<em>str</em>) &#8211; Endpoint that Bard listens for queries on</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Variables:</th><td class="field-body"><ul class="first last simple">
<li><strong>result_json</strong> (<em>str</em>) &#8211; JSON object representing a query result. Initial value: None</li>
<li><strong>result</strong> (<em>list</em>) &#8211; Query result parsed into a list of dicts. Initial value: None</li>
<li><strong>query_type</strong> (<em>str</em>) &#8211; Name of most recently run query, e.g., topN. Initial value: None</li>
<li><strong>query_dict</strong> (<em>dict</em>) &#8211; JSON object representing the query. Initial value: None</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>Example</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
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47</pre></div></td><td class="code"><div class="highlight"><pre> <span class="o">&gt;&gt;&gt;</span> <span class="kn">from</span> <span class="nn">pydruid.client</span> <span class="kn">import</span> <span class="o">*</span>

<span class="o">&gt;&gt;&gt;</span> <span class="n">query</span> <span class="o">=</span> <span class="n">PyDruid</span><span class="p">(</span><span class="s">&#39;http://localhost:8083&#39;</span><span class="p">,</span> <span class="s">&#39;druid/v2/&#39;</span><span class="p">)</span>

<span class="o">&gt;&gt;&gt;</span> <span class="n">top</span> <span class="o">=</span> <span class="n">query</span><span class="o">.</span><span class="n">topn</span><span class="p">(</span>
<span class="n">datasource</span><span class="o">=</span><span class="s">&#39;twitterstream&#39;</span><span class="p">,</span>
<span class="n">granularity</span><span class="o">=</span><span class="s">&#39;all&#39;</span><span class="p">,</span>
<span class="n">intervals</span><span class="o">=</span><span class="s">&#39;2013-10-04/pt1h&#39;</span><span class="p">,</span>
<span class="n">aggregations</span><span class="o">=</span><span class="p">{</span><span class="s">&quot;count&quot;</span><span class="p">:</span> <span class="n">doublesum</span><span class="p">(</span><span class="s">&quot;count&quot;</span><span class="p">)},</span>
<span class="n">dimension</span><span class="o">=</span><span class="s">&#39;user_name&#39;</span><span class="p">,</span>
<span class="nb">filter</span> <span class="o">=</span> <span class="n">Dimension</span><span class="p">(</span><span class="s">&#39;user_lang&#39;</span><span class="p">)</span> <span class="o">==</span> <span class="s">&#39;en&#39;</span><span class="p">,</span>
<span class="n">metric</span><span class="o">=</span><span class="s">&#39;count&#39;</span><span class="p">,</span>
<span class="n">threshold</span><span class="o">=</span><span class="mi">2</span>
<span class="p">)</span>

<span class="o">&gt;&gt;&gt;</span> <span class="k">print</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">query</span><span class="o">.</span><span class="n">query_dict</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="o">&gt;&gt;&gt;</span> <span class="p">{</span>
<span class="s">&quot;metric&quot;</span><span class="p">:</span> <span class="s">&quot;count&quot;</span><span class="p">,</span>
<span class="s">&quot;aggregations&quot;</span><span class="p">:</span> <span class="p">[</span>
<span class="p">{</span>
<span class="s">&quot;type&quot;</span><span class="p">:</span> <span class="s">&quot;doubleSum&quot;</span><span class="p">,</span>
<span class="s">&quot;fieldName&quot;</span><span class="p">:</span> <span class="s">&quot;count&quot;</span><span class="p">,</span>
<span class="s">&quot;name&quot;</span><span class="p">:</span> <span class="s">&quot;count&quot;</span>
<span class="p">}</span>
<span class="p">],</span>
<span class="s">&quot;dimension&quot;</span><span class="p">:</span> <span class="s">&quot;user_name&quot;</span><span class="p">,</span>
<span class="s">&quot;filter&quot;</span><span class="p">:</span> <span class="p">{</span>
<span class="s">&quot;type&quot;</span><span class="p">:</span> <span class="s">&quot;selector&quot;</span><span class="p">,</span>
<span class="s">&quot;dimension&quot;</span><span class="p">:</span> <span class="s">&quot;user_lang&quot;</span><span class="p">,</span>
<span class="s">&quot;value&quot;</span><span class="p">:</span> <span class="s">&quot;en&quot;</span>
<span class="p">},</span>
<span class="s">&quot;intervals&quot;</span><span class="p">:</span> <span class="s">&quot;2013-10-04/pt1h&quot;</span><span class="p">,</span>
<span class="s">&quot;dataSource&quot;</span><span class="p">:</span> <span class="s">&quot;twitterstream&quot;</span><span class="p">,</span>
<span class="s">&quot;granularity&quot;</span><span class="p">:</span> <span class="s">&quot;all&quot;</span><span class="p">,</span>
<span class="s">&quot;threshold&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span>
<span class="s">&quot;queryType&quot;</span><span class="p">:</span> <span class="s">&quot;topN&quot;</span>
<span class="p">}</span>

<span class="o">&gt;&gt;&gt;</span> <span class="k">print</span> <span class="n">query</span><span class="o">.</span><span class="n">result</span>
<span class="o">&gt;&gt;&gt;</span> <span class="p">[{</span><span class="s">&#39;timestamp&#39;</span><span class="p">:</span> <span class="s">&#39;2013-10-04T00:00:00.000Z&#39;</span><span class="p">,</span>
<span class="s">&#39;result&#39;</span><span class="p">:</span> <span class="p">[{</span><span class="s">&#39;count&#39;</span><span class="p">:</span> <span class="mf">7.0</span><span class="p">,</span> <span class="s">&#39;user_name&#39;</span><span class="p">:</span> <span class="s">&#39;user_1&#39;</span><span class="p">},</span> <span class="p">{</span><span class="s">&#39;count&#39;</span><span class="p">:</span> <span class="mf">6.0</span><span class="p">,</span> <span class="s">&#39;user_name&#39;</span><span class="p">:</span> <span class="s">&#39;user_2&#39;</span><span class="p">}]}]</span>

<span class="o">&gt;&gt;&gt;</span> <span class="n">df</span> <span class="o">=</span> <span class="n">query</span><span class="o">.</span><span class="n">export_pandas</span><span class="p">()</span>
<span class="o">&gt;&gt;&gt;</span> <span class="k">print</span> <span class="n">df</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">count</span> <span class="n">timestamp</span> <span class="n">user_name</span>
<span class="mi">0</span> <span class="mi">7</span> <span class="mi">2013</span><span class="o">-</span><span class="mi">10</span><span class="o">-</span><span class="mo">04</span><span class="n">T00</span><span class="p">:</span><span class="mo">00</span><span class="p">:</span><span class="mf">00.000</span><span class="n">Z</span> <span class="n">user_1</span>
<span class="mi">1</span> <span class="mi">6</span> <span class="mi">2013</span><span class="o">-</span><span class="mi">10</span><span class="o">-</span><span class="mo">04</span><span class="n">T00</span><span class="p">:</span><span class="mo">00</span><span class="p">:</span><span class="mf">00.000</span><span class="n">Z</span> <span class="n">user_2</span>
</pre></div>
</td></tr></table></div>
<dl class="method">
<dt id="client.PyDruid.export_pandas">
<tt class="descname">export_pandas</tt><big>(</big><big>)</big><a class="headerlink" href="#client.PyDruid.export_pandas" title="Permalink to this definition"></a></dt>
<dd><p>Export the current query result to a Pandas DataFrame object.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The DataFrame representing the query result</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">DataFrame</td>
</tr>
<tr class="field-odd field"><th class="field-name" colspan="2">Raises NotImplementedError:</th></tr>
<tr class="field-odd field"><td>&nbsp;</td><td class="field-body"></td>
</tr>
</tbody>
</table>
<p>Example</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
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16</pre></div></td><td class="code"><div class="highlight"><pre> <span class="o">&gt;&gt;&gt;</span> <span class="n">top</span> <span class="o">=</span> <span class="n">query</span><span class="o">.</span><span class="n">topn</span><span class="p">(</span>
<span class="n">datasource</span><span class="o">=</span><span class="s">&#39;twitterstream&#39;</span><span class="p">,</span>
<span class="n">granularity</span><span class="o">=</span><span class="s">&#39;all&#39;</span><span class="p">,</span>
<span class="n">intervals</span><span class="o">=</span><span class="s">&#39;2013-10-04/pt1h&#39;</span><span class="p">,</span>
<span class="n">aggregations</span><span class="o">=</span><span class="p">{</span><span class="s">&quot;count&quot;</span><span class="p">:</span> <span class="n">doublesum</span><span class="p">(</span><span class="s">&quot;count&quot;</span><span class="p">)},</span>
<span class="n">dimension</span><span class="o">=</span><span class="s">&#39;user_name&#39;</span><span class="p">,</span>
<span class="nb">filter</span> <span class="o">=</span> <span class="n">Dimension</span><span class="p">(</span><span class="s">&#39;user_lang&#39;</span><span class="p">)</span> <span class="o">==</span> <span class="s">&#39;en&#39;</span><span class="p">,</span>
<span class="n">metric</span><span class="o">=</span><span class="s">&#39;count&#39;</span><span class="p">,</span>
<span class="n">threshold</span><span class="o">=</span><span class="mi">2</span>
<span class="p">)</span>

<span class="o">&gt;&gt;&gt;</span> <span class="n">df</span> <span class="o">=</span> <span class="n">query</span><span class="o">.</span><span class="n">export_pandas</span><span class="p">()</span>
<span class="o">&gt;&gt;&gt;</span> <span class="k">print</span> <span class="n">df</span>
<span class="o">&gt;&gt;&gt;</span> <span class="n">count</span> <span class="n">timestamp</span> <span class="n">user_name</span>
<span class="mi">0</span> <span class="mi">7</span> <span class="mi">2013</span><span class="o">-</span><span class="mi">10</span><span class="o">-</span><span class="mo">04</span><span class="n">T00</span><span class="p">:</span><span class="mo">00</span><span class="p">:</span><span class="mf">00.000</span><span class="n">Z</span> <span class="n">user_1</span>
<span class="mi">1</span> <span class="mi">6</span> <span class="mi">2013</span><span class="o">-</span><span class="mi">10</span><span class="o">-</span><span class="mo">04</span><span class="n">T00</span><span class="p">:</span><span class="mo">00</span><span class="p">:</span><span class="mf">00.000</span><span class="n">Z</span> <span class="n">user_2</span>
</pre></div>
</td></tr></table></div>
</dd></dl>

<dl class="method">
<dt id="client.PyDruid.export_tsv">
<tt class="descname">export_tsv</tt><big>(</big><em>dest_path</em><big>)</big><a class="headerlink" href="#client.PyDruid.export_tsv" title="Permalink to this definition"></a></dt>
<dd><p>Export the current query result to a tsv file.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>dest_path</strong> (<em>str</em>) &#8211; file to write query results to</td>
</tr>
<tr class="field-even field"><th class="field-name" colspan="2">Raises NotImplementedError:</th></tr>
<tr class="field-even field"><td>&nbsp;</td><td class="field-body"></td>
</tr>
</tbody>
</table>
<p>Example</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
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16</pre></div></td><td class="code"><div class="highlight"><pre> &gt;&gt;&gt; top = query.topn(
datasource=&#39;twitterstream&#39;,
granularity=&#39;all&#39;,
intervals=&#39;2013-10-04/pt1h&#39;,
aggregations={&quot;count&quot;: doublesum(&quot;count&quot;)},
dimension=&#39;user_name&#39;,
filter = Dimension(&#39;user_lang&#39;) == &#39;en&#39;,
metric=&#39;count&#39;,
threshold=2
)

&gt;&gt;&gt; query.export_tsv(&#39;top.tsv&#39;)
&gt;&gt;&gt; !cat top.tsv
&gt;&gt;&gt; count user_name timestamp
7.0 user_1 2013-10-04T00:00:00.000Z
6.0 user_2 2013-10-04T00:00:00.000Z
</pre></div>
</td></tr></table></div>
</dd></dl>

<dl class="method">
<dt id="client.PyDruid.groupby">
<tt class="descname">groupby</tt><big>(</big><em>**kwargs</em><big>)</big><a class="headerlink" href="#client.PyDruid.groupby" title="Permalink to this definition"></a></dt>
<dd><p>A group-by query groups a results set (the requested aggregate metrics) by the specified dimension(s).</p>
Expand Down Expand Up @@ -313,9 +537,9 @@ <h1>Welcome to PyDruid&#8217;s documentation!<a class="headerlink" href="#welcom
<span class="n">granularity</span><span class="o">=</span><span class="s">&#39;all&#39;</span><span class="p">,</span>
<span class="n">intervals</span><span class="o">=</span><span class="s">&#39;2013-06-14/pt1h&#39;</span><span class="p">,</span>
<span class="n">aggregations</span><span class="o">=</span><span class="p">{</span><span class="s">&quot;count&quot;</span><span class="p">:</span> <span class="n">doublesum</span><span class="p">(</span><span class="s">&quot;count&quot;</span><span class="p">)},</span>
<span class="n">dimension</span><span class="o">=</span><span class="s">&#39;user&#39;</span><span class="p">,</span>
<span class="n">dimension</span><span class="o">=</span><span class="s">&#39;user_name&#39;</span><span class="p">,</span>
<span class="n">metric</span><span class="o">=</span><span class="s">&#39;count&#39;</span><span class="p">,</span>
<span class="nb">filter</span><span class="o">=</span><span class="n">Dimension</span><span class="p">(</span><span class="s">&#39;language&#39;</span><span class="p">)</span> <span class="o">==</span> <span class="s">&#39;en&#39;</span><span class="p">,</span>
<span class="nb">filter</span><span class="o">=</span><span class="n">Dimension</span><span class="p">(</span><span class="s">&#39;user_lang&#39;</span><span class="p">)</span> <span class="o">==</span> <span class="s">&#39;en&#39;</span><span class="p">,</span>
<span class="n">threshold</span><span class="o">=</span><span class="mi">1</span>
<span class="p">)</span>
<span class="o">&gt;&gt;&gt;</span> <span class="k">print</span> <span class="n">top</span>
Expand Down
9 changes: 4 additions & 5 deletions docs/build/html/objects.inv
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# Project: PyDruid
# Version: 0.2.0
# The remainder of this file is compressed using zlib.
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