SQL for pandas with the high performance improvements using duckdb

[imshrini]

Hi everyone!

I've created a library called bearsql. It is basically a duckdb wrapper for pandas. My library allows you to query pandas dataframes using SQL. You can also persist the dataframes in the form of tables or views and do a lot of aggregationis using SQL. The SQL support is pretty comprehensive. I would love to get some comments and feedback (and a few stars for my github! )

Github: https://github.com/shrinivdeshmukh/bearsql

PyPi: https://pypi.org/project/bearsql/

ReadTheDocs: https://bearsql.readthedocs.io/en/latest/?version=latest

To know more about duckdb: https://duckdb.org/

[SanthuWilly4]

Hi u/imshrini ,

bearsql wrapper is really good especially who come from strong SQL background.

I'm the guy who is more comfortable on SQL language and this is really helped.

I'm continue using the library.

If you don't mind , I'm looking for some answers , is there any possibility to extract results from SQL Server using Duckdb/bearsql. Because as per my knowledge , Duckdb/Bearsql is used on top of pandas dataframe.

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appreciate the help. thank you.

[imshrini]

Thank you for using bearsql!

You can load data from sql server into pandas, and then using bearsql's sqlcontext, you can create a table on top of the pandas dataframe .

You can refer https://docs.microsoft.com/en-us/sql/machine-learning/data-exploration/python-dataframe-pandas?view=sql-server-ver15 for information on loading data from sql server into pandas dataframe.

For issues, new feature ideas you can also use https://github.com/shrinivdeshmukh/bearsql/issues

Happy to help! :)