SLAMA: LightAutoML on Spark
SLAMA is a version of LightAutoML library modified to run in distributed mode with Apache Spark framework.
It requires:
- Python 3.9
- PySpark 3.2+ (installed as a dependency)
- Synapse ML library (It will be downloaded by Spark automatically)
Currently, only tabular Preset is supported. See demo with spark-based tabular automl preset in examples/spark/tabular-preset-automl.py. For further information check docs in the root of the project containing dedicated SLAMA section.
License
This project is licensed under the Apache License, Version 2.0. See LICENSE file for more details.
Installation
First of all you need to install git and poetry.
# Load LAMA source code
git clone https://github.com/fonhorst/LightAutoML_Spark.git
cd LightAutoML/
# !!!Choose only one item!!!
# 1. Global installation: Don't create virtual environment
poetry config virtualenvs.create false --local
# 2. Recommended: Create virtual environment inside your project directory
poetry config virtualenvs.in-project true
# For more information read poetry docs
# Install LAMA
poetry lock
poetry install
Metadata
Release files for sparklightautoml-dev 0.3.2
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 | Actions |
|---|---|---|---|---|
| SparkLightAutoML_DEV-0.3.2.tar.gz | 116.5 kB | Without provenance | Details for SparkLightAutoML_DEV-0.3.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| SparkLightAutoML_DEV-0.3.2-py3-none-any.whl | Python 3 | none | any | Details for SparkLightAutoML_DEV-0.3.2-py3-none-any.whl |
Total release size: 262.7 kB
Release files / SparkLightAutoML_DEV-0.3.2.tar.gz
| Download URL | SparkLightAutoML_DEV-0.3.2.tar.gz |
|---|---|
| Size | 116.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0dedb0647d56bb5fce4a1853fae58f234a6b6ce5a05c7af9d771f5cb13479517
|
|
BLAKE2b-256 checksum How to use checksums |
b8142e0542c7a298825eb703341815ddeea3451fb6131c775764dd41ccc700a0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.15 CPython/3.9.12 Linux/5.14.18-100.fc33.x86_64
|
Release files / SparkLightAutoML_DEV-0.3.2-py3-none-any.whl
| Download URL | SparkLightAutoML_DEV-0.3.2-py3-none-any.whl |
|---|---|
| Size | 146.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
feb53abbeb2aacddfd16f8ac425c920ee6bac928b08f7fe160d0135192b46d30
|
|
BLAKE2b-256 checksum How to use checksums |
786e1791fda6784101da24d17fd38641faa7234daed50e62ad3238ed53b436bc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.15 CPython/3.9.12 Linux/5.14.18-100.fc33.x86_64
|
Security for sparklightautoml-dev 0.3.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.