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"description": "courseraresearchexports\n=======================\n\n.. image:: https://travis-ci.org/coursera/courseraresearchexports.svg\n :target: https://travis-ci.org/coursera/courseraresearchexports\n\nThis project is a library consisting of a command line interface and a client\nfor interacting with Coursera's research exports. Up to date documentation\nof the data provided by Coursera for research purposes is available on gitbooks\n, `Coursera Data Exports Guide `_.\n\nInstallation\n------------\n\nTo install this package, execute::\n\n pip install courseraresearchexports\n\n`pip `_ is a python package manager.\n\nIf you do not have ``pip`` installed on your machine, please follow the\n`installation instructions `_ for your platform.\n\nIf you experience issues installing with `pip`, we recommend that you use the\npython 2.7 distribution of `Anaconda `_ and try the above\ncommand again or to use a `virtualenv `_\nfor installation::\n\n virtualenv venv\n source venv/bin/activate\n pip install courseraresearchexports\n\nNote: the ``containers`` subcommand requires ``docker`` to already be installed\non your machine. Please see the `docker installation instructions `_ for platform\nspecific information.\n\nautocomplete\n^^^^^^^^^^^^\n\nTo enable tab autocomplete, please install `argcomplete `_ using\n``pip install autocomplete`` and execute ``activate-global-python-argcomplete``. Open a new shell and\npress tab for autocomplete functionality.\n\nSee the argcomplete documentation for more details.\n\nSetup\n-----\n\nAuthorize your application using `courseraoauth2client `_::\n\n courseraoauth2client config authorize --app manage_research_exports\n\nTo use the ``containers`` functionality, a docker instance must be running.\nPlease see the docker `getting started guide `_\nfor installation instructions for your platform.\n\nUpgrade\n-------\n\nIf you have a previously installed version of `courseracourseexports`, execute::\n\n pip install courseraresearchexports --upgrade\n\nThis will upgrade your installation to the newest version.\n\nCommand Line Interface\n----------------------\n\nThe project includes a command line tool. Run::\n\n courseraresearchexports -h\n\nfor a complete list of features, flags, and documentation. Similarly,\ndocumentation for the subcommands listed below is also available (e.g. for\n``jobs``) by running::\n\n courseraresearchexports jobs -h\n\njobs\n^^^^\nSubmit a research export request or retrieve the status of pending and\ncompleted export jobs.\n\nrequest\n~~~~~~~\nCreates an data export job request and return the export request id. To create a\ndata export requests for all available tables for a course::\n\n courseraresearchexports jobs request tables --course_slug $COURSE_SLUG \\\n --purpose \"testing data export\"\n\nReplace ``$COURSE_SLUG`` with your course slug (The course slug is the part after\n``/learn`` in the url. For ``https://www.coursera.org/learn/machine-learning``,\nthe slug is `machine-learning`).\n\nYou may also use `--course_id` if you know your course id. This is also necessary for non publically\navailable courses.\n\nIf a more limited set of data is required, you can specify which schemas are\nincluded with the export. (e.g. for the demographics tables)::\n\n courseraresearchexports jobs request tables --course_slug $COURSE_SLUG \\\n --schemas demographics --purpose \"testing data export\"\n\nFor more information on the available tables/schemas, please refer to the\n`Coursera Data Exports Guide `_.\n\nIf you are a data coordinator, you can request that user ids are linked between\ndomains of the data export::\n\n courseraresearchexports jobs request tables --course_slug $COURSE_SLUG \\\n --purpose \"testing data export\" --user_id_hashing linked\n\nData coordinators can also request clickstream exports::\n\n courseraresearchexports jobs request clickstream --course_slug $COURSE_SLUG \\\n --interval 2016-09-01 2016-09-02 --purpose \"testing data export\"\n\nBy default, clickstream exports will cache results for days already exported. To ignore the cache and request exports for the entire date range, pass in the flag ``--ignore_existing``.\n\nWe have 2 rate limits for creating jobs: up to 15 jobs per hour per user,\nand for each scope (course/specialization/group), one request per hour.\n\nget_all\n~~~~~~~\nLists the details and status of all data export requests that you have made::\n\n courseraresearchexports jobs get_all\n\nget\n~~~\nRetrieve the details and status of an export request::\n\n courseraresearchexports jobs get $EXPORT_REQUEST_ID\n\ndownload\n~~~~~~~~\nDownload a completed table or clickstream to your local destination::\n\n courseraresearchexports jobs download $EXPORT_REQUEST_ID\n\nclickstream_download_links\n~~~~~~~~~~~~~~~~~~~~~~~~~~\nDue to the size of clickstream exports, we persist download links for completed\nclickstream export requests on Amazon S3. The clickstream data for each day is\nsaved into a separate file and download links to these files can be retrieved\nby running::\n\n courseraresearchexports jobs clickstream_download_links --course_slug $COURSE_SLUG\n\ncontainers\n^^^^^^^^^^\n\ncreate\n~~~~~~\nCreates a docker container using the postgres image and loads export data\ninto a postgres database on the container. To create a docker container\nfrom an export, first ``request`` an export using the ``jobs`` command. Then,\nusing the ``$EXPORT_REQUEST_ID``, create a docker container with::\n\n courseraresearchexports containers create --export_request_id $EXPORT_REQUEST_ID\n\nThis will download the data export and load all the data into the database\nrunning on the container. This may take some time depending on the size of\nyour export. To create a docker container with an already downloaded export\n(please decompress the archive first)::\n\n courseraresearchexports containers create --export_data_folder /path/to/data_export/\n\nAfter creation use the ``list`` command to check the status of the\ncontainer and view the container name, database name, address and port to\nconnect to the database. Use the `db connect $CONTAINER_NAME` command to open\na psql shell.\n\nlist\n~~~~\nLists the details of all the containers created by ``courseraresearchexports``::\n\n courseraresearchexports containers list\n\nstart\n~~~~~\nStart a container::\n\n courseraresearchexports containers start $CONTAINER_NAME\n\nstop\n~~~~\nStop a container::\n\n courseraresearchexports containers stop $CONTAINER_NAME\n\nremove\n~~~~~~\nRemove a container::\n\n courseraresearchexports containers remove $CONTAINER_NAME\n\ndb\n^^\n\nconnect\n~~~~~~~\nOpen a shell to a postgres database::\n\n courseraresearchexports db connect $CONTAINER_NAME\n\ncreate_view\n~~~~~~~~~~~\nCreate a view in the postgres database. We are planning to include commonly\nused denormalized views as part of this project. To create one of these views\n(i.e. for the demographic_survey view)::\n\n courseraresearchexports db create_view $CONTAINER_NAME --view_name demographic_survey\n\nIf you have your own sql script that you'd like to create as a view run::\n\n courseraresearchexports db create_view $CONTAINER_NAME --sql_file /path/to/sql/file/new_view.sql\n\nThis will create a view using the name of the file as the name of the view, in this case \"new_view\".\n\nNote: as `user_id` columns vary with partner and user id hashing, please refer\nto the exports guide for SQL formatting guidelines.\n\nunload_to_csv\n~~~~~~~~~~~~~\nExport a table or view to a csv file. 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To check, simply run::\n\n pep8 courseraresearchexports tests\n",
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