A wrapper for the pyomnisci libarary http://github.com/omnisci/pyomnisci, maintained for backwards compatibility.
Existing scripts should be migrated to pyomnisci from pymapd, this library will not be updated moving forward.
Quick Install (CPU)
Packages are available on conda-forge and PyPI:
conda install -c conda-forge pymapd pip install pymapd
Quick Install (GPU)
We recommend creating a fresh conda 3.7 or 3.8 environment when installing pymapd with GPU capabilities.
To install pymapd and cudf for GPU Dataframe support (conda-only):
conda create -n omnisci-gpu -c rapidsai -c nvidia -c conda-forge \ -c defaults cudf=0.15 python=3.7 cudatoolkit=10.2 pymapd
2 maintainers
Metadata
2 maintainers
Release files for pymapd 0.26.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| pymapd-0.26.0.tar.gz | 6.3 MB | Without provenance | Details |
Release files / pymapd-0.26.0.tar.gz
| Download URL | pymapd-0.26.0.tar.gz |
|---|---|
| Size | 6.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0edb59ad3eae6238f1f2df37be9b5ff1ea600891efbefab6b4c4acb4c5ed5bb5
|
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BLAKE2b-256 checksum How to use checksums |
3cc400e8dbf8ea21a724cadf61ac3b303cd50135d1f5bfc4c2d705120f85d972
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.7.10
|
Security for pymapd 0.26.0
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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