Meadowrun is a library for data scientists and data engineers who run python code on AWS, Azure, or Kubernetes. Meadowrun:
- scales from a single function to thousands of distributed tasks.
- syncs your local code and libraries for a faster, easier iteration loop. Edit your code and rerun your analysis without worrying about building packages or Docker images.
- optimizes for cost, choosing the cheapest instance types and turning them off when they're no longer needed.
For more context, see our case studies of how Meadowrun is used in real life, or see the project homepage
To get started, go to our documentation, or join the chat on Gitter
Quickstart
First, install Meadowrun using pip:
pip install meadowrun
Next, assuming you've configured the AWS CLI and are a root/administrator user, you can run:
import meadowrun
import asyncio
print(
asyncio.run(
meadowrun.run_function(
lambda: sum(range(1000)) / 1000,
meadowrun.AllocEC2Instance(),
meadowrun.Resources(logical_cpu=1, memory_gb=8, max_eviction_rate=80),
meadowrun.Deployment.mirror_local()
)
)
)
The documentation has examples of how to use other package managers (conda, poetry), and other platforms (Azure, GKE, Kubernetes).
2 maintainers
Metadata
2 maintainers
Release files for meadowrun 0.2.16
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 | |
|---|---|---|---|---|
| meadowrun-0.2.16.tar.gz | 279.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| meadowrun-0.2.16-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 624.2 kB
Release files / meadowrun-0.2.16.tar.gz
| Download URL | meadowrun-0.2.16.tar.gz |
|---|---|
| Size | 279.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
84867ad358a2101a97096a8f19a0d490562b6bf40dde7b9766a923d2511a1963
|
|
BLAKE2b-256 checksum How to use checksums |
4e10437ebd3e0778d92576125d6634966d1039b9309ffafdb870dc0bcc95484a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.2.1 CPython/3.9.10 Windows/10
|
Release files / meadowrun-0.2.16-py3-none-any.whl
| Download URL | meadowrun-0.2.16-py3-none-any.whl |
|---|---|
| Size | 345.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
eb91095825709027b658f9edbfc4d7dccc1e7cd929f1baaa2e5827b3c2823add
|
|
BLAKE2b-256 checksum How to use checksums |
231e2bc4ec1fe1dd8973e69e87a8dea9748fe034e3190faef258d9fdb2a887b8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.2.1 CPython/3.9.10 Windows/10
|
Security for meadowrun 0.2.16
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.
