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 02:01:39 2025 |
| md5 checksum | d843255e0fecaaa64207ec66fff340a8 |
| arch | x86_64 |
| build | py310h06a4308_0 |
| constrains | cloudpickle >=1.4.0 |
| depends | adagio, antlr4-python3-runtime >=4.11.1,<4.12, pandas >=1.2.0, python >=3.10,<3.11.0a0, triad >=0.9.0 |
| license | Apache-2.0 |
| license_family | Apache |
| md5 | d843255e0fecaaa64207ec66fff340a8 |
| name | qpd |
| platform | linux |
| sha1 | 0d88eccd99aa71b144c61a7043fc7d7c82abadd3 |
| sha256 | 9e1ccf53eae43841baa1bac3a5e57002d0b3537f875425b4281c54ba0a41f294 |
| size | 358747 |
| subdir | linux-64 |
| timestamp | 1703169493523 |
| version | 0.4.4 |