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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 02:01:41 2025
md5 checksum 47ddd85094bce0f33210a38ae8f0b4fe
arch x86_64
build py310h06a4308_0
depends adagio, antlr4-python3-runtime >=4.11.1,<4.12, pandas >=1.2.0, python >=3.10,<3.11.0a0, triad >=0.8.0
license Apache-2.0
license_family Apache
md5 47ddd85094bce0f33210a38ae8f0b4fe
name qpd
platform linux
sha1 ae04cdf5a7eda4508f61dfdd2c3111330ea8f7b2
sha256 c95ed13e3fc30ff52ea18f15afcdaafb9e4e4142d6b0241246a09664f3196886
size 397848
subdir linux-64
timestamp 1682608233002
version 0.4.1