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Sid Mohan
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Sid Mohan
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v2.3.0 ready
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‎CHANGELOG.MD

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# ChangeLog
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## [2024-03-25]
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### `datafog-python` [2.3.2]
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- Added datafog-python/examples/uploading-file-types.ipynb to show JSON uploading example (#16)
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- Added datafog-python/tests/regex_issue.py to show issue with regex recognizer creation
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- Moved versioning to separate invocable function in setup.py

‎examples/getting-started.ipynb

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"# Print the DataFrame\n",
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"print(df)\n",
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"\n",
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"\n",
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"def scan_text(text):\n",
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" return presidio.scan(text)\n",
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"\n",
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"df['scan_results'] = df['text'].apply(scan_text)\n"
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"\n",
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"df[\"scan_results\"] = df[\"text\"].apply(scan_text)"
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]
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},
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{
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"scan_results1 = presidio.scan(ceo_email_chunk)\n",
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"print(\"PII Detected - base case:\", scan_results1)\n",
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"\n",
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"scan_results2 = presidio.scan(ceo_email_chunk, deny_list=['CTO'])\n",
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"scan_results2 = presidio.scan(ceo_email_chunk, deny_list=[\"CTO\"])\n",
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"print(\"PII Detected with deny list:\", scan_results2)"
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]
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}

‎examples/uploading-file-types.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<img src=\"../public/colorlogo.png\" width=\"50%\"/>\n",
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"\n",
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"\n",
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"[Homepage](https://www.datafog.ai) | \n",
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"[Discord](https://discord.gg/bzDth394R4) | \n",
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"[Github](https://github.com/datafog/datafog-python) | \n",
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"[Contact](mailto:[email protected])\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## What we're covering\n",
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"\n",
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"In this notebook, we're covering how to use DataFog with different file types.\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting datafog==2.3.2b10\n",
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" Downloading datafog-2.3.2b10.tar.gz (13 kB)\n",
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" Installing build dependencies ... \u001b[?25ldone\n",
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"\u001b[?25h Getting requirements to build wheel ... \u001b[?25ldone\n",
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"\u001b[?25h Installing backend dependencies ... \u001b[?25ldone\n",
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"\u001b[?25h Preparing metadata (pyproject.toml) ... \u001b[?25ldone\n",
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"\u001b[?25hRequirement already satisfied: pandas==2.2.1 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from datafog==2.3.2b10) (2.2.1)\n",
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"Requirement already satisfied: presidio-analyzer==2.2.353 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from datafog==2.3.2b10) (2.2.353)\n",
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"Requirement already satisfied: pytest==8.0.2 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from datafog==2.3.2b10) (8.0.2)\n",
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"Requirement already satisfied: Requests==2.31.0 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from datafog==2.3.2b10) (2.31.0)\n",
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"Requirement already satisfied: requests-file>=1.4 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from tldextract->presidio-analyzer==2.2.353->datafog==2.3.2b10) (2.0.0)\n",
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"Requirement already satisfied: filelock>=3.0.8 in /Users/sidmohan/Desktop/datafog-pypi-v2.3.2/.venv/lib/python3.11/site-packages (from tldextract->presidio-analyzer==2.2.353->datafog==2.3.2b10) (3.13.1)\n",
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"Building wheels for collected packages: datafog\n",
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" Building wheel for datafog (pyproject.toml) ... \u001b[?25ldone\n",
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"\u001b[?25h Created wheel for datafog: filename=datafog-2.3.2b10-py3-none-any.whl size=10839 sha256=98c6651a54b1e3b5d878d59fa534c7c8c22e1e6d4a49f04b43d4e447b9bd7e90\n",
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" Stored in directory: /Users/sidmohan/Library/Caches/pip/wheels/a2/87/a5/513ca3a2ad3d826f945f1277a85346ae1bfd4d6261bb202b2d\n",
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"Successfully built datafog\n",
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"Installing collected packages: datafog\n",
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" Attempting uninstall: datafog\n",
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" Found existing installation: datafog 2.3.2b9\n",
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" Uninstalling datafog-2.3.2b9:\n",
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" Successfully uninstalled datafog-2.3.2b9\n",
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"Successfully installed datafog-2.3.2b10\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"# Initialize\n",
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"%pip install datafog==2.3.2b10\n",
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"import json\n",
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"\n",
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"import requests\n",
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"from datafog import PresidioEngine as presidio\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### JSON"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" uuid \\\n",
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"0 a1b2c3d4-e5f6-7g8h-9i0j-k1l2m3n4o5p6 \n",
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"1 q9w8e7r6-t5y4-u3i2-o1p0-a9s8d7f6g5h4 \n",
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"2 z1x2c3v4-b5n6-m7q8-w9e0-r1t2y3u4i5o6 \n",
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"3 p1o2i3u4-y5t6-r7e8-w9q0-a1s2d3f4g5h6 \n",
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"4 l1k2j3h4-g5f6-d7s8-a9q0-w1e2r3t4y5u6 \n",
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"\n",
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" text_chunk \\\n",
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"0 Cisco to Acquire Splunk, to Help Make Organiza... \n",
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"1 Cisco intends to acquire Splunk for $157 per s... \n",
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"2 Our combined capabilities will drive the next ... \n",
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"3 Tidal Partners LLC is acting as financial advi... \n",
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"4 Cisco will host a conference call for Thursday... \n",
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"\n",
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" doc_source \n",
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"0 CEO_Google_Drive_Press_Release_Draft.docx \n",
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"1 CEO_Google_Drive_Press_Release_Draft.docx \n",
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"2 CEO_Google_Drive_Press_Release_Draft.docx \n",
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"3 CEO_Google_Drive_Press_Release_Draft.docx \n",
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"4 CEO_Google_Drive_Press_Release_Draft.docx \n"
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]
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}
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],
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"source": [
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"# Load the JSON data from the URL\n",
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"url = \"https://gist.githubusercontent.com/sidmohan0/757185e0b9ff63fe00096baa0ce3fa45/raw/cb30da88e985d171bef281c927434cac52c239ea/sample.json\"\n",
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"data = requests.get(url).text\n",
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"# Parse the JSON data\n",
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"data = json.loads(data)\n",
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"# print(data)\n",
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"# Create a DataFrame from the JSON data\n",
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"df = pd.DataFrame(data)\n",
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"# print(df.shape)\n",
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"print(df.head(10))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"ban_list = [\n",
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" \"Cisco\",\n",
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" \"Splunk\",\n",
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" \"Tidal Partners LLC\",\n",
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" \"$157 per share\",\n",
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" \"$28 billion\",\n",
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" \"equity value\",\n",
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" \"Chuck Robbins\",\n",
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" \"acquire\",\n",
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" \"acquisition\",\n",
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" \"September 21, 2023\",\n",
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" \"5:15 am (PT)\",\n",
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" \"8:15 am (ET)\",\n",
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" \"conference call\",\n",
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" \"AI-enabled security\",\n",
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" \"observability\",\n",
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" \"next generation\",\n",
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" \"financial advisor\",\n",
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" \"CEO_Google_Drive_Press_Release_Draft.docx\",\n",
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"]\n",
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"\n",
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"\n",
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"def scan_text(text):\n",
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" return presidio.scan(text, deny_list=ban_list)\n",
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"\n",
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"\n",
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"df[\"scan_results\"] = df[\"text_chunk\"].apply(scan_text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0 [type: CUSTOM_PII, start: 0, end: 5, score: 1....\n",
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"1 [type: CUSTOM_PII, start: 0, end: 5, score: 1....\n",
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"2 [type: CUSTOM_PII, start: 41, end: 56, score: ...\n",
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"3 [type: CUSTOM_PII, start: 0, end: 18, score: 1...\n",
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"4 [type: CUSTOM_PII, start: 0, end: 5, score: 1....\n",
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"Name: scan_results, dtype: object\n"
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]
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}
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],
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"source": [
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"print(df[\"scan_results\"])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎setup.py

+5-1
Original file line numberDiff line numberDiff line change
@@ -5,6 +5,10 @@
55
long_description = f.read()
66

77

8+
def __version__():
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return "2.3.2"
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project_urls = {
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"Homepage": "https://datafog.ai",
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"Documentation": "https://docs.datafog.ai",
@@ -16,7 +20,7 @@
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setup(
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name="datafog",
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version="2.3.2b1",
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version=__version__(),
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author="DataFog",
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author_email="[email protected]",
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description="Scan, redact, and manage PII in your documents before they get uploaded to a Retrieval Augmented Generation (RAG) system.",

‎src/datafog/__about__.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -1,2 +1,2 @@
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# SSOT for the package version
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__version__ = "2.3.2b1"
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__version__ = "2.3.2"

‎tests/regex_issue.py

+28
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,28 @@
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import pandas as pd
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import requests
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from datafog import PresidioEngine as presidio
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url = "https://gist.githubusercontent.com/sidmohan0/757185e0b9ff63fe00096baa0ce3fa45/raw/0bef1789c1167acd286902f3466e54e151feaab3/sample.json"
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response = requests.get(url)
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data = response.json()
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df = pd.DataFrame(data)
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print(df.head())
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# create a dataframe with some text data
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def datafog_scanner(text):
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# create regex recognizer to scan for deal numbers
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regex_pattern = r"\$\S+"
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deal_regex = presidio.create_ad_hoc_regex_recognizer(
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regex_pattern=regex_pattern, entity_type="deal_values", score=0.4
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)
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return presidio.scan(
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text,
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deny_list=["Cisco", "Splunk", "CSCO", "SPLK"],
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ad_hoc_recognizers=[deal_regex],
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)
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df["scan_results"] = df["text"].apply(datafog_scanner)

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