Revenue screener, project för Hershkat

First milestone could be:

A. Add publisher/developer to each line in scraped ranks.

B. Create a wrapper script to invoke all three scripts and run everyday at for example 8 am, zip scraped data with a unique filename including date and time. Do some "sanity checks" that scraped data is "complete", i.e. all ranks are downloaded, if not downloaded - try rerunning the scripts a few times, create some alarm (send email informing about the problem). Store the data safely at two different locations for backup purposes.

C. Install the script on for example GCP (Google Cloud Platform), or other platform - whichever is performance and price effective.

D. As part of the script(s) in B., populate a SQL database on GCP that should be used for the revenue_screener functionality. Do some "sanity checks" that the database data is "complete", i.e. all ranks are downloaded to SQL-database, if not - trey a a few more times, create some alarm (send email informing about the problem).

E. Populate the SQL database with historical app store and GP rankings from [login to view URL] api.

Skills: Django, MySQL, PHP, Python, SQL

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Project ID: #17803361

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