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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 02:01:42 2025
md5 checksum 36994b39fb59f23993d916c328ab1a77
arch x86_64
build py311h06a4308_0
depends adagio, antlr4-python3-runtime >=4.11.1,<4.12, pandas >=1.2.0, python >=3.11,<3.12.0a0, triad >=0.8.0
license Apache-2.0
license_family Apache
md5 36994b39fb59f23993d916c328ab1a77
name qpd
platform linux
sha1 6ea7403c04900141c021da2928ca0d5a9e0384d8
sha256 b1018cc894f3b68681d8dcfbed71433458faadcfbe04eb45f733ad0d2ba6c93f
size 474600
subdir linux-64
timestamp 1682608456649
version 0.4.1