{"id":21041021,"url":"https://github.com/chfoo/furlat","last_synced_at":"2025-10-01T04:30:57.556Z","repository":{"id":9751743,"uuid":"11716414","full_name":"chfoo/furlat","owner":"chfoo","description":"Find URL Archiving Tool. 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For example on Ubuntu::\n\n    pip3 install selenium\n\n\nRunning\n+++++++\n\nYou can run the package as a script::\n\n    python3 -m furlat find bit.ly --verbose\n\nTo just search Twitter::\n\n    python3 -m furlat find bit.ly --verbose --source twitter\n\nUse the ``--help`` to see details about arguments.\n\nResults are currently stored into a text file. For example, if you run bit.ly, a folder called ``bitly`` will be created with the text files inside the folder. The text files contain the discovered URLs.\n\nInfinitely running commands check for a sentinel file called ``STOP``. If the modified file is newly modified or created after starting the command, the command will stop gracefully::\n\n    touch STOP\n\n\nCommands\n--------\n\nanalyze\n    Print statistics about the URL shortcodes\n\nfind\n    Launch a find URL project\n\nsort\n    Sort the URLs by length, then value\n\n\nLibrary\n+++++++\n\nThe library is not yet stable as an API, but you can read the ``__main__.py`` file to get a overview of how it works.\n\n\nAbout\n=====\n\nThe goal of Furlat is to find valid shortcodes as much as possible, without brute-force discovery, using 3rd party sources such as search engines and microblogs. \n\n\nLinks\n+++++\n\n* Homepage: https://github.com/chfoo/furlat\n\n.. * Questions?: https://answers.launchpad.net/furlat\n\n.. * Bugs?: https://github.com/chfoo/furlat/issues\n\n.. * PyPI: https://pypi.python.org/pypi/furlat/\n\n* Chat: irc://irc.efnet.org/archiveteam-bs (I'll be on #archiveteam-bs on EFnet)\n\nTesting\n+++++++\n\nThe unit tests can be run with ``nosetests``::\n\n    nosetests3\n\n\nRoadmap\n+++++++\n\nThis software is currently in **experimental-but-could-be-useful** state.\n\n\nWhat's Available\n----------------\n\n* Launching a real web browser.\n* Searching through Google, Yahoo, Bing, and Twitter.\n* Random keyword search term generation using word lists and MediaWiki page title dump files.\n\n\nWhat's To-Do\n------------\n\n* Searching Identica\n* Nicer result output options\n* Configurable options such as fetch rate and number of jobs run concurrently\n* Travis CI setup\n* PyPI and other websites setup\n* Inline documentation\n* Launching a fake web browser.\n\n\nSee also\n--------\n\n* https://github.com/chfoo/rdai\n* https://github.com/chfoo/cloaked-octo-nemesis\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchfoo%2Ffurlat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchfoo%2Ffurlat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchfoo%2Ffurlat/lists"}