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Ploomber is the fastest way to build data pipelines ⚡️. Use your favorite editor (Jupyter, VSCode, PyCharm) to develop interactively and deploy ☁️ without code changes (Kubernetes, Airflow, AWS Batch, and SLURM). Do you have legacy notebooks? Refactor them into modular pipelines with a single command.
Installation
Compatible with Python 3.7 and higher.
Install with pip:
pip install ploomber
Or with conda:
conda install ploomber -c conda-forge
Getting started
Try the tutorial:
Community
Main Features
⚡️ Get started quickly
A simple YAML API to get started quickly, a powerful Python API for total flexibility.
https://user-images.githubusercontent.com/989250/150660813-fc289c6c-0ed5-432d-b6df-063ce98c0093.mp4
⏱ Shorter development cycles
Automatically cache your pipeline’s previous results and only re-compute tasks that have changed since your last execution.
https://user-images.githubusercontent.com/989250/150660820-9a3a0abd-5904-492b-97ff-5494285dfebf.mp4
☁️ Deploy anywhere
Run as a shell script in a single machine or distributively in Kubernetes, Airflow, AWS Batch, or SLURM.
https://user-images.githubusercontent.com/989250/150660830-3f81c9a2-5392-49e5-976d-cb8a38441ecb.mp4
📙 Automated migration from legacy notebooks
Bring your old monolithic notebooks, and we’ll automatically convert them into maintainable, modular pipelines.
https://user-images.githubusercontent.com/989250/150660840-b0c12f85-504c-4233-8c3d-6724d291f1aa.mp4
I want to migrate my notebook.
Resources
- Documentation
- PyData Chicago talk (covers motivation and demo)
- Develop and deploy an ML pipeline in 30 minutes (EuroPython 2021)
- Guest blog post on the official Jupyter blog
- Examples (Machine Learning pipeline, ETL, among others)
- Blog
- Comparison with other tools
- More videos
About Ploomber
Ploomber is a big community of data enthusiasts pushing the boundaries of Data Science and Machine Learning tooling.
Whatever your skillset is, you can contribute to our mission. So whether you're a beginner or an experienced professional, you're welcome to join us on this journey!
2 maintainers
Metadata
2 maintainers
Release files for ploomber 0.23.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ploomber-0.23.3.tar.gz | 299.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ploomber-0.23.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 632.0 kB
Release files / ploomber-0.23.3.tar.gz
| Download URL | ploomber-0.23.3.tar.gz |
|---|---|
| Size | 299.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
|
Release files / ploomber-0.23.3-py3-none-any.whl
| Download URL | ploomber-0.23.3-py3-none-any.whl |
|---|---|
| Size | 332.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
|
