{
    "info": {
        "author": "Harshit Sanghvi",
        "author_email": "hello@sanghviharshit.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: End Users/Desktop",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Auto Pocket Tagger\n\nUse Google cloud's Natural Language Processing API to automatically analyze the webpage from articles saved in your Pocket list, derive tags/keywords based on the content of the page, and add tags to the articles in Pocket list for free.\n\n> Pocket has suggested tags service for their paid premium plans. You can find more about it [here](https://help.getpocket.com/article/906-pocket-premium-suggested-tags). This still requires manual work of adding the tags to each article one-by-one. This package automates all of it for free.\n\n## Features\n- Uses [Python wrapper](https://github.com/tapanpandita/pocket) for [Pocket API](http://getpocket.com/api/docs) to retrieve articles in the `My List`\n- Uses [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/) to scrape webpages\n- Uses Google Cloud's [Natural Language Processing API](https://cloud.google.com/natural-language/) to generate list of categories and entities from the content of the webpage\n- Uses Pocket API to add tags to articles in your `My List`\n\n\n## Usage\n\n### Installation\n\n#### Install published version from pypi\n```shell\n$ pip install pocket-tagger\n```\n\n#### Install latest version from git\n```shell\n$ pip install git+https://github.com/sanghviharshit/pocket-tagger\n```\n\n\n### Prerequisites\n#### [Google Cloud](https://cloud.google.com/natural-language/docs/quickstart)\n\nThis package relies on Google cloud natural language processing API, which requires billing enabled on your project.\nYou can find the quickstart instructions [here](https://cloud.google.com/natural-language/docs/quickstart)\n**Options:**\n1. Create a service account and download the credentials file - https://cloud.google.com/video-intelligence/docs/common/auth\n```python\ntagger = PocketTagger(gcloud_credentials_file=\"gcloud_credentials_file.json\")\n```\n2. or Configure gloud locally - https://cloud.google.com/sdk/gcloud/reference/init\n```python\ntagger = PocketTagger()\n```\n\n#### [Pocket API](https://getpocket.com/developer/)\n\nTo fetch the articles list and add tags, you need a developer key from [here](https://getpocket.com/developer/)\nCreate a new Application with `modify` and `retrieve` permissions. Save the Consumer Key and Access Token.\n```python\ntagger = PocketTagger(consumer_key='your-consumer-key',\n                access_token='your-access-token')\n```\n\n### [Examples](./examples)\n\n```python\n# Initialize PocketTagger with GCloud and Pocket API Credentials\ntagger = PocketTagger(gcloud_credentials_file=\"gcloud_credentials_file.json\",\n                consumer_key='pocket-consumer-key',\n                access_token='pocket-access-token')\n\n# Check https://getpocket.com/developer/docs/v3/retrieve for additional list of options you can pass for retrieving pocket list\narticles = tagger.get_articles_from_api(count=10, offset=10, detailType='complete')\n\n# Alternatively you can load the articles from file if you saved them previously using save_articles_to_file\n# articles = tagger.get_articles_from_file(\"20190621.json\")\n# Generate tags for each article\narticles_with_tags = tagger.get_tags_for_articles(articles)\n\n# Save the articles with tags to file. You can use this file to verify it looks good before running the final step to tag the articles.\ntagger.save_articles_to_file(today.strftime('%Y%m%d-with-tags.json'), articles_with_tags)\n\n# You can skip this step if you want to do a dry run. Verify the tags in the file we generated in the previous step.\ntagger.add_tags_to_articles(articles_with_tags)\n```\n\n### Optional overrides\nYou can override the default thresholds for [entity](https://cloud.google.com/natural-language/docs/reference/rest/v1/Entity\n) salience and [category](https://cloud.google.com/natural-language/docs/reference/rest/v1/ClassificationCategory) confidence\n\n```python\nthresholds = {\n  'entity_salience_threshold': 0.7\n  'category_confidence_threshold': 0.3\n}\narticles_with_tags = tagger.get_tags_for_articles(articles, thresholds)\n```\n\n## Sample\n\nSample output from running it for my 490 items long Pocket list\n> `X` under Entities or Categories denotes the NLP client returned those as potential candidates, but we skipped them because it didn't meet the threshold. You can see the last line `Tags: abc, xyz` for list of tags pocket-tagger added for each URL.\n\n```\n(1/490) https://www.reddit.com/r/explainlikeimfive/comments/bvweym/eli5_why_do_coffee_drinkers_feel_more_clear/?utm_source=share&utm_medium=ios_app\n         Title: ELI5: Why do coffee drinkers feel more clear headed after consuming caffeine? Why do some get a headache without it? Does caffeine cause any permanent brain changes and can the brain go back to 'normal' after years of caffeine use? : explainlikeimfive\n         Description: r/explainlikeimfive: **Explain Like I'm Five is the best forum and archive on the internet for layperson-friendly explanations.**   Don't Panic!\n         Entities:\n            X Coffee Drinkers: 0.2438652664422989\n            X Eli5: 0.14941969513893127\n            X Caffeine: 0.12065556645393372\n            X Caffeine: 0.0874909833073616\n            X Some: 0.06917785853147507\n            X Headache: 0.0606028214097023\n            X Brain: 0.03606536239385605\n            X Explainlikeimfive: 0.033727116882801056\n            X Brain Changes: 0.03211209550499916\n            X Caffeine Use: 0.029848895967006683\n            X R: 0.02966366335749626\n            X Forum: 0.028598546981811523\n            X Internet: 0.022404097020626068\n            X Archive: 0.022404097020626068\n            X Explainlikeimfive: 0.017647551372647285\n            X Don'T Panic: 0.009302889928221703\n            X Five: 0.007013489492237568\n            X Five: 0.0\n         Categories:\n              /Food & Drink/Beverages/Coffee & Tea: 0.6700000166893005\n         Tags: Food & Drink, Beverages, Coffee & Tea\n(2/490) https://www.reddit.com/r/television/comments/bnpwe3/enjoy_three_full_minutes_of_the_cast_of_game_of/?utm_source=share&utm_medium=ios_app\n         Title: Enjoy three full minutes of the cast of 'Game of Thrones' expressing disappointment in Season 8. : television\n         Description: r/television:\n         Entities:\n            X Cast: 0.31218624114990234\n            X Disappointment: 0.20341947674751282\n            X Season: 0.20341947674751282\n            X Game Of Thrones: 0.13265934586524963\n            X Television: 0.08712445199489594\n            X Television: 0.06119102984666824\n            X 8: 0.0\n            X Three: 0.0\n         Categories:\n              /Arts & Entertainment/TV & Video/TV Shows & Programs: 0.75\n         Tags: Arts & Entertainment, TV & Video, TV Shows & Programs\n(3/490) https://www.reddit.com/r/homeautomation/comments/awvf5r/local_realtime_person_detection_for_rtsp_cameras/\n         Title: Local realtime person detection for RTSP cameras : homeautomation\n         Description: r/homeautomation: A subreddit focused on automating your home, housework or household activity. Sensors, switches, cameras, locks, etc. Any \u2026\n         Entities:\n            X Realtime Person Detection: 0.3057926297187805\n            X Homeautomation: 0.15315502882003784\n            X Cameras: 0.14035314321517944\n            X Rtsp: 0.07461880147457123\n            X Homeautomation: 0.051411159336566925\n            X Home: 0.047811269760131836\n            X Housework: 0.04366889223456383\n            X Subreddit: 0.04183248057961464\n            X R: 0.04132793843746185\n            X Cameras: 0.032860007137060165\n            X Locks: 0.028899790719151497\n            X Household Activity: 0.012798599898815155\n            X Switches: 0.012735127471387386\n            X Sensors: 0.012735127471387386\n         Categories:\n              /Computers & Electronics: 0.7900000214576721\n         Tags: Computers & Electronics\n```\n\n## References\n- [Pocket API Wrapper for Python](https://github.com/tapanpandita/pocket)\n- [Pocket API Docs](http://getpocket.com/api/docs)\n- [Google Cloud Natural Language Processing](https://cloud.google.com/natural-language/)\n- [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/)\n- [Complete list of content categories from Google Natural Language API](https://cloud.google.com/natural-language/docs/categories)",
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