[RESEND WITH CORRECTED LINK] Squint version 0.1.0 has been released: * New query previews provide convenient feedback at the interactive prompt. * Completely rewritten tutorial https://squint.readthedocs.io/en/stable/tutorial/ <https://squint.readthedocs.io/tutorial/> * Added support for Python 3.9 and dropped support for 3.3, 3.2, and 2.6. What is Squint: Squint is a simple query interface for tabular data. A core feature of Squint is that the structure of a query's selection determines the structure of its result. Squint is available from the PyPI: pip install squint With Squint You Can: * Select data using Python literals—sets, lists, dictionaries, etc.—and fetch results in the same format. * Aggregate, map, filter, reduce, and otherwise manipulate data. * Lazily iterate over results, write them to a file, or eagerly evaluate them in memory. * Analyze data from CSV, Excel, SQL, and other data sources. Links: * Docs: https://squint.readthedocs.io/ * PyPI: https://pypi.org/project/squint/ * Source: https://github.com/shawnbrown/squint Syntax Comparison: # SQL SELECT A, SUM(B) FROM mydata WHERE C='xyz' GROUP BY A; # Pandas df[['A', 'B']][df['C'] == 'xyz'].groupby('A').sum() # Squint select({'A': 'B'}, C='xyz').sum() Note: Squint uses `dict` objects to select groups of values—the *key* determines the field to group by, and the *value* determines the contents of each group. Fetching the results of such a query returns a dictionary of selected elements.