Data science toolkit support for OmniSciDB
Project description
This package enables using common Python data science toolkits with OmniSciDB. It brings data frame support on CPU and GPU as well as support for arrow. See the documentation for more.
Quick Install (CPU)
Packages are available on conda-forge and PyPI:
conda install -c conda-forge pyomnisci pip install pyomnisci
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=0.18 python=3.7 cudatoolkit=11.0 pyomnisci
Documentation
Further documentation for pyomnisci usage is available at: http://pyomnisci.readthedocs.io/
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file pyomnisci-0.28.1.tar.gz
.
File metadata
- Download URL: pyomnisci-0.28.1.tar.gz
- Upload date:
- Size: 6.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.5.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ed4f41ae6b783d46ae728f61d59f79e6e47ac9c60a2e3a72e603fe9c601acfe5 |
|
MD5 | 7c9faf5eb94e12cb017326dd1648fc69 |
|
BLAKE2b-256 | 7de878f9e2054a246e0a58eb2b7400c907560c0e908229c391a5eda60bb758a6 |
Provenance
File details
Details for the file pyomnisci-0.28.1-py3-none-any.whl
.
File metadata
- Download URL: pyomnisci-0.28.1-py3-none-any.whl
- Upload date:
- Size: 21.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.5.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a703319caa6c78c40dd2ba5107040a96abf1f82c21c068186eb8c60097373123 |
|
MD5 | 5e59dc4cc499e48b76745e13819f9395 |
|
BLAKE2b-256 | b8d5f01185a41cb54f3a64dee99b62fced0e69ab1769b9fa9394e26a12ca27bd |