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Sounds awesome. Thanks for posting. It'd be great to be able to import this into a Jupyter notebook or script rather than doing it on the command line. Don't kn

• dmoura 5y ago
  Thank you! One of my main goals was making data processing in the command-line more accessible and intuitive. If you use a shell you can leverage an extensive array of tools. please take a look at the recipes in the Readme. The shell is many times underrated for data processing! Right now you can use it in Jupiter Notebooks using a shell kernel like: https://github.com/takluyver/bash_kernel https://github.com/takluyver/bash_kernel On the mid-term, developing a spyql kernel is appealing because of syntax highlighting, code autocompleting, and more. But unless several people show interest on this, I should tackle other features first.
  • jp0d 5y ago
    Thanks for the reply. It's your tool mate and of course by all means work on the features you want. It's a really neat tool, there is not doubt. I'm sure it'll be helpful to a lot of people. I'm data analyst and I often find writing SQL statements from Python using libraries such as sqlalchemy and psycopg2 etc. I've written a few rudimentary functions that connect to my data sources and run PGSQL code and fetch result into a Pandas dataframe before doing further analysis. When I saw your tool I got excited and was trying figure out how to integrate it into my notebooks. hahaha. Cheers.
    • dmoura 5y ago
      :-) It’s an open-source tool, so it should be community-driven. If you can share an example I can try to understand if spyql can make your life easier.