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    "info": {
        "author": "Jonas Tingeborn",
        "author_email": "tinjon+pip@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: GNU General Public License v2 (GPLv2)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3"
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        "description": "# imdb-sqlite\nImports IMDB TSV files into a SQLite database.\n\nIt will fetch the [files][1] from IMDB unless you've already fetched them earlier.\n\nThe program relies on the following IMDB tab separated files:\n\n* `title.basics.tsv.gz`: Video titles such as movies, documentaries, tv series, episodes etc.\n* `name.basics.tsv.gz`: People in the entertainment business.\n* `title.akas.tsv.gz`: Alternative names for titles, for different languages.\n* `title.principals.tsv.gz`: Mapping of who participated in which title (movie / show).\n* `title.episode.tsv.gz`: Season and episode numbers, for episodes of shows.\n* `title.ratings.tsv.gz`: Current rating and vote count for the titles.\n\n## Installation\n\n    pip install imdb-sqlite\n\n## Usage\n\n    usage: imdb-sqlite [OPTIONS]\n\n    Imports imdb tsv interface files into a new sqlitedatabase. Fetches them from\n    imdb if not present onthe machine.\n\n    optional arguments:\n      -h, --help       show this help message and exit\n      --db FILE        Connection URI for the database to import into. (default:\n                       imdb.db)\n      --cache-dir DIR  Download cache dir where the tsv files from imdb will be\n                       stored before the import. (default: downloads)\n      --verbose        Show database interaction (default: False)\n\nJust run the program with no arguments, and you'll get a file named `imdb.db`\nin the current working directory.\n\n### Hints\n* Make sure the disk the database is written to has sufficient space.\n  About 5 GiB is needed.\n* Use a SSD to speed up the import.\n* To check the best case import performance, use an in-memory database: \n  `--db :memory:`.\n\n## Example\n\n    $ imdb-sqlite\n\n    2018-07-08 16:00:00,000 Populating database: imdb.db\n    2018-07-08 16:00:00,001 Applying schema\n\n    2018-07-08 16:00:00,005 Importing file: downloads\\name.basics.tsv.gz\n    2018-07-08 16:00:00,005 Reading number of rows ...\n    2018-07-08 16:00:11,521 Inserting rows into table: people\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8699964/8699964 [01:23<00:00, 104387.75 rows/s]\n\n    2018-07-08 16:01:34,868 Importing file: downloads\\title.basics.tsv.gz\n    2018-07-08 16:01:34,868 Reading number of rows ...\n    2018-07-08 16:01:41,873 Inserting rows into table: titles\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 5110779/5110779 [00:58<00:00, 87686.98 rows/s]\n\n    2018-07-08 16:02:40,161 Importing file: downloads\\title.akas.tsv.gz\n    2018-07-08 16:02:40,161 Reading number of rows ...\n    2018-07-08 16:02:44,743 Inserting rows into table: akas\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 3625334/3625334 [00:37<00:00, 97412.94 rows/s]\n\n    2018-07-08 16:03:21,964 Importing file: downloads\\title.principals.tsv.gz\n    2018-07-08 16:03:21,964 Reading number of rows ...\n    2018-07-08 16:03:55,922 Inserting rows into table: crew\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 28914893/28914893 [03:45<00:00, 128037.21 rows/s]\n\n    2018-07-08 16:07:41,757 Importing file: downloads\\title.episode.tsv.gz\n    2018-07-08 16:07:41,757 Reading number of rows ...\n    2018-07-08 16:07:45,370 Inserting rows into table: episodes\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 3449903/3449903 [00:21<00:00, 158265.16 rows/s]\n\n    2018-07-08 16:08:07,172 Importing file: downloads\\title.ratings.tsv.gz\n    2018-07-08 16:08:07,172 Reading number of rows ...\n    2018-07-08 16:08:08,029 Inserting rows into table: ratings\n    100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 846901/846901 [00:05<00:00, 152421.27 rows/s]\n\n    2018-07-08 16:08:13,589 Creating table indices ...\n    2018-07-08 16:09:16,451 Import successful\n\n\n### Note\nThe import may take a long time, since there are millions of records to\nprocess.\n\nThe above example used python 3.6.4 on windows 7, with the working directory\nbeing on a SSD.  \n\n## PyPI\nCurrent status of the project is: \n[![Build Status](https://travis-ci.org/jojje/imdb-sqlite.png)](https://travis-ci.org/jojje/imdb-sqlite)\n\nThis project uses an automated build and release process.\nThe module in the [pypi][2] repository is automatically built and released from\nthe github source, upon any version tagged commit to the master branch.\n\nClick the status link and check out the logs if you're interested in the\npackage lineage; meaning how the released pypi module was constructed from\nsource.\n\n[1]: https://www.imdb.com/interfaces/\n[2]: https://pypi.org/project/imdb-sqlite/\n\n",
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