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<div class="highlight"><pre><span></span><code><span class="c1"># download presidio</span>
<span class="err">!</span><span class="n">pip</span> <span class="n">install</span> <span class="n">presidio_analyzer</span> <span class="n">presidio_anonymizer</span>
<span class="err">!</span><span class="n">python</span> <span class="o">-</span><span class="n">m</span> <span class="n">spacy</span> <span class="n">download</span> <span class="n">en_core_web_lg</span>
</code></pre></div>
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<p>Path to notebook: <a href="https://www.github.com/microsoft/presidio/blob/main/docs/samples/python/batch_processing.ipynb">https://www.github.com/microsoft/presidio/blob/main/docs/samples/python/batch_processing.ipynb</a></p>
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<h1 id="run-presidio-on-structured-semi-structured-data">Run Presidio on structured / semi-structured data</h1>
<p>This sample shows how Presidio could be potentially extended to handle the anonymization of a table or data frame.
It introduces methods for the analysis and anonymization of both lists and dicts. </p>
<p>Note: this sample input here is a Pandas DataFrame and a JSON file, but it can be used in other scenarios such as querying SQL data or using Spark DataFrames.</p>
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<h3 id="set-up-imports">Set up imports</h3>
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<div class="highlight"><pre><span></span><code><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">Iterator</span><span class="p">,</span> <span class="n">Iterable</span>
<span class="kn">import</span> <span class="nn">collections</span>
<span class="kn">from</span> <span class="nn">dataclasses</span> <span class="kn">import</span> <span class="n">dataclass</span>
<span class="kn">import</span> <span class="nn">pprint</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">presidio_analyzer</span> <span class="kn">import</span> <span class="n">AnalyzerEngine</span><span class="p">,</span> <span class="n">BatchAnalyzerEngine</span><span class="p">,</span> <span class="n">RecognizerResult</span><span class="p">,</span> <span class="n">DictAnalyzerResult</span>
<span class="kn">from</span> <span class="nn">presidio_anonymizer</span> <span class="kn">import</span> <span class="n">AnonymizerEngine</span><span class="p">,</span> <span class="n">BatchAnonymizerEngine</span>
<span class="kn">from</span> <span class="nn">presidio_anonymizer.entities</span> <span class="kn">import</span> <span class="n">EngineResult</span>
</code></pre></div>
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<h2 id="example-using-sample-tabular-data">Example using sample tabular data</h2>
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<div class="highlight"><pre><span></span><code><span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;name phrase&quot;</span><span class="p">,</span> <span class="s2">&quot;phone number phrase&quot;</span><span class="p">,</span> <span class="s2">&quot;integer&quot;</span><span class="p">,</span> <span class="s2">&quot;boolean&quot;</span> <span class="p">]</span>
<span class="n">sample_data</span> <span class="o">=</span> <span class="p">[</span>
<span class="p">(</span><span class="s1">&#39;Charlie likes this&#39;</span><span class="p">,</span> <span class="s1">&#39;Please call 212-555-1234 after 2pm&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">True</span><span class="p">),</span>
<span class="p">(</span><span class="s1">&#39;You should talk to Mike&#39;</span><span class="p">,</span> <span class="s1">&#39;his number is 978-428-7111&#39;</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="kc">False</span><span class="p">),</span>
<span class="p">(</span><span class="s1">&#39;Mary had a little startup&#39;</span><span class="p">,</span> <span class="s1">&#39;Phone number: 202-342-1234&#39;</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
<span class="p">]</span>
</code></pre></div>
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<div class="highlight"><pre><span></span><code><span class="c1"># Create Pandas DataFrame</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">sample_data</span><span class="p">,</span><span class="n">columns</span><span class="o">=</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df</span>
</code></pre></div>
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<th>name phrase</th>
<th>phone number phrase</th>
<th>integer</th>
<th>boolean</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>Charlie likes this</td>
<td>Please call 212-555-1234 after 2pm</td>
<td>1</td>
<td>True</td>
</tr>
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<th>1</th>
<td>You should talk to Mike</td>
<td>his number is 978-428-7111</td>
<td>2</td>
<td>False</td>
</tr>
<tr>
<th>2</th>
<td>Mary had a little startup</td>
<td>Phone number: 202-342-1234</td>
<td>3</td>
<td>False</td>
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<div class="highlight"><pre><span></span><code><span class="c1"># DataFrame to dict</span>
<span class="n">df_dict</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">to_dict</span><span class="p">(</span><span class="n">orient</span><span class="o">=</span><span class="s2">&quot;list&quot;</span><span class="p">)</span>
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<div class="highlight"><pre><span></span><code><span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">df_dict</span><span class="p">)</span>
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<code>{'boolean': [True, False, False],
'integer': [1, 2, 3],
'name phrase': ['Charlie likes this',
'You should talk to Mike',
'Mary had a little startup'],
'phone number phrase': ['Please call 212-555-1234 after 2pm',
'his number is 978-428-7111',
'Phone number: 202-342-1234']}
</code>
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<div class="highlight"><pre><span></span><code><span class="n">analyzer</span> <span class="o">=</span> <span class="n">AnalyzerEngine</span><span class="p">()</span>
<span class="n">batch_analyzer</span> <span class="o">=</span> <span class="n">BatchAnalyzerEngine</span><span class="p">(</span><span class="n">analyzer_engine</span><span class="o">=</span><span class="n">analyzer</span><span class="p">)</span>
<span class="n">batch_anonymizer</span> <span class="o">=</span> <span class="n">BatchAnonymizerEngine</span><span class="p">()</span>
</code></pre></div>
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<div class="highlight"><pre><span></span><code><span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">batch_analyzer</span><span class="o">.</span><span class="n">analyze_dict</span><span class="p">(</span><span class="n">df_dict</span><span class="p">,</span> <span class="n">language</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">)</span>
<span class="n">analyzer_results</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">analyzer_results</span><span class="p">)</span>
<span class="n">analyzer_results</span>
</code></pre></div>
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<code>[DictAnalyzerResult(key='name phrase', value=['Charlie likes this', 'You should talk to Mike', 'Mary had a little startup'], recognizer_results=[[type: PERSON, start: 0, end: 7, score: 0.85], [type: PERSON, start: 19, end: 23, score: 0.85], [type: PERSON, start: 0, end: 4, score: 0.85]]),
DictAnalyzerResult(key='phone number phrase', value=['Please call 212-555-1234 after 2pm', 'his number is 978-428-7111', 'Phone number: 202-342-1234'], recognizer_results=[[type: DATE_TIME, start: 31, end: 34, score: 0.85, type: PHONE_NUMBER, start: 12, end: 24, score: 0.75], [type: PHONE_NUMBER, start: 14, end: 26, score: 0.75], [type: PHONE_NUMBER, start: 14, end: 26, score: 0.75]]),
DictAnalyzerResult(key='integer', value=[1, 2, 3], recognizer_results=[[], [], []]),
DictAnalyzerResult(key='boolean', value=[True, False, False], recognizer_results=[[], [], []])]</code>
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<div class="highlight"><pre><span></span><code><span class="n">anonymizer_results</span> <span class="o">=</span> <span class="n">batch_anonymizer</span><span class="o">.</span><span class="n">anonymize_dict</span><span class="p">(</span><span class="n">analyzer_results</span><span class="p">)</span>
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<div class="highlight"><pre><span></span><code><span class="n">scrubbed_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">anonymizer_results</span><span class="p">)</span>
</code></pre></div>
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<div class="highlight"><pre><span></span><code><span class="n">scrubbed_df</span>
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}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name phrase</th>
<th>phone number phrase</th>
<th>integer</th>
<th>boolean</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>&lt;PERSON&gt; likes this</td>
<td>Please call &lt;PHONE_NUMBER&gt; after &lt;DATE_TIME&gt;</td>
<td>1</td>
<td>True</td>
</tr>
<tr>
<th>1</th>
<td>You should talk to &lt;PERSON&gt;</td>
<td>his number is &lt;PHONE_NUMBER&gt;</td>
<td>2</td>
<td>False</td>
</tr>
<tr>
<th>2</th>
<td>&lt;PERSON&gt; had a little startup</td>
<td>Phone number: &lt;PHONE_NUMBER&gt;</td>
<td>3</td>
<td>False</td>
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<h2 id="example-using-json">Example using JSON</h2>
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<div class="highlight"><pre><span></span><code><span class="n">nested_dict</span> <span class="o">=</span> <span class="p">{</span>
<span class="s2">&quot;key_a&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;key_a1&quot;</span><span class="p">:</span> <span class="s2">&quot;My phone number is 212-121-1424&quot;</span><span class="p">},</span>
<span class="s2">&quot;key_b&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;www.abc.com&quot;</span><span class="p">},</span>
<span class="s2">&quot;key_c&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span>
<span class="s2">&quot;names&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;James Bond&quot;</span><span class="p">,</span> <span class="s2">&quot;Clark Kent&quot;</span><span class="p">,</span> <span class="s2">&quot;Hakeem Olajuwon&quot;</span><span class="p">,</span> <span class="s2">&quot;No name here!&quot;</span><span class="p">]</span>
<span class="p">}</span>
<span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">nested_dict</span><span class="p">)</span>
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<code>{'key_a': {'key_a1': 'My phone number is 212-121-1424'},
'key_b': {'www.abc.com'},
'key_c': 3,
'names': ['James Bond', 'Clark Kent', 'Hakeem Olajuwon', 'No name here!']}
</code>
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<div class="highlight"><pre><span></span><code><span class="c1"># Analyze dict</span>
<span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">batch_analyzer</span><span class="o">.</span><span class="n">analyze_dict</span><span class="p">(</span><span class="n">input_dict</span> <span class="o">=</span> <span class="n">nested_dict</span><span class="p">,</span> <span class="n">language</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">)</span>
<span class="c1"># Anonymize dict</span>
<span class="n">anonymizer_results</span> <span class="o">=</span> <span class="n">batch_anonymizer</span><span class="o">.</span><span class="n">anonymize_dict</span><span class="p">(</span><span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">analyzer_results</span><span class="p">)</span>
<span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">anonymizer_results</span><span class="p">)</span>
</code></pre></div>
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<code>{'key_a': {'key_a1': 'My phone number is &lt;PHONE_NUMBER&gt;'},
'key_b': ['&lt;URL&gt;'],
'key_c': 3,
'names': ['&lt;PERSON&gt;', '&lt;PERSON&gt;', '&lt;PERSON&gt;', 'No name here!']}
</code>
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<h3 id="ignoring-specific-keys">Ignoring specific keys</h3>
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<div class="highlight"><pre><span></span><code><span class="n">keys_to_skip</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;key_a1&quot;</span><span class="p">,</span> <span class="s2">&quot;names&quot;</span><span class="p">]</span>
<span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">batch_analyzer</span><span class="o">.</span><span class="n">analyze_dict</span><span class="p">(</span><span class="n">input_dict</span> <span class="o">=</span> <span class="n">nested_dict</span><span class="p">,</span> <span class="n">language</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">keys_to_skip</span><span class="o">=</span><span class="n">keys_to_skip</span><span class="p">)</span>
<span class="c1"># Anonymize dict</span>
<span class="n">anonymizer_results</span> <span class="o">=</span> <span class="n">batch_anonymizer</span><span class="o">.</span><span class="n">anonymize_dict</span><span class="p">(</span><span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">analyzer_results</span><span class="p">)</span>
<span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">anonymizer_results</span><span class="p">)</span>
</code></pre></div>
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<pre>
<code>{'key_a': {'key_a1': 'My phone number is 212-121-1424'},
'key_b': ['&lt;URL&gt;'],
'key_c': 3,
'names': ['James Bond', 'Clark Kent', 'Hakeem Olajuwon', 'No name here!']}
</code>
</pre>
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<h3 id="ignoring-nested-keys">Ignoring nested keys</h3>
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<div class="highlight"><pre><span></span><code><span class="n">keys_to_skip</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;key_a.key_a1&quot;</span><span class="p">]</span>
<span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">batch_analyzer</span><span class="o">.</span><span class="n">analyze_dict</span><span class="p">(</span><span class="n">input_dict</span> <span class="o">=</span> <span class="n">nested_dict</span><span class="p">,</span> <span class="n">language</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">keys_to_skip</span><span class="o">=</span><span class="n">keys_to_skip</span><span class="p">)</span>
<span class="c1"># Anonymize dict</span>
<span class="n">anonymizer_results</span> <span class="o">=</span> <span class="n">batch_anonymizer</span><span class="o">.</span><span class="n">anonymize_dict</span><span class="p">(</span><span class="n">analyzer_results</span> <span class="o">=</span> <span class="n">analyzer_results</span><span class="p">)</span>
<span class="n">pprint</span><span class="o">.</span><span class="n">pprint</span><span class="p">(</span><span class="n">anonymizer_results</span><span class="p">)</span>
</code></pre></div>
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<code>{'key_a': {'key_a1': 'My phone number is 212-121-1424'},
'key_b': ['&lt;URL&gt;'],
'key_c': 3,
'names': ['&lt;PERSON&gt;', '&lt;PERSON&gt;', '&lt;PERSON&gt;', 'No name here!']}
</code>
</pre>
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<h4 id="note"><strong>Note!</strong></h4>
<p>JSON files with objects within lists, e.g.:
<div class="highlight"><pre><span></span><code>{
&quot;key&quot;: [
{
&quot;key2&quot;: &quot;Peter Parker&quot;
},
{
&quot;key3&quot;: &quot;555-1234&quot;
}
]
}
</code></pre></div></p>
<p>Are not yet supported. Consider breaking the JSON to parts if needed.</p>
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