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QPD let you run the same SQL (SELECT for now) statements on different computing frameworks with pandas-like interfaces. Currently, it support Pandas, Dask and Ray (via Modin on Ray). QPD directly translates SQL into pandas-like operations to run on the backend computing frameworks, so it can be significantly faster than some other approaches, for example, to dump pandas dataframes into SQLite, run SQL and convert the result back into a pandas dataframe. However, the top priorities of QPD are correctness and consistency. It ensures the results of implemented SQL features following SQL convention, and it ensures consistent behavior regardless of backend computing frameworks.

Uploaded Mon Mar 31 02:01:43 2025
md5 checksum be0098052186af73b752545bf9bded6d
arch x86_64
build py39h06a4308_0
depends adagio, antlr4-python3-runtime >=4.11.1,<4.12, pandas >=1.2.0, python >=3.9,<3.10.0a0, triad >=0.8.0
license Apache-2.0
license_family Apache
md5 be0098052186af73b752545bf9bded6d
name qpd
platform linux
sha1 0c322380eb00b60cb9f713fef1048598ba81e3da
sha256 7bca81a5280352a754dbc4c2d94a20825edb4868c8c6aea327627c1c31986c1a
size 397374
subdir linux-64
timestamp 1682608519963
version 0.4.1