Metadata-Version: 2.4
Name: repster
Version: 0.1.1
Summary: Developer-first replication platform — SDK and CLI
Project-URL: Homepage, https://docs.repster.online
Project-URL: Documentation, https://docs.repster.online
Project-URL: Repster Cloud, https://repster.online
Author: The Repster Authors
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: data-engineering,data-pipeline,dlt,elt,etl,ingestion,orchestration,replication,repster,scheduler
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Database
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.12
Requires-Dist: croniter>=6.2.2
Requires-Dist: dlt>=1.27.2
Requires-Dist: fastapi>=0.115.0
Requires-Dist: httpx>=0.28.1
Requires-Dist: jinja2>=3.1.4
Requires-Dist: pydantic>=2.13.4
Requires-Dist: python-dotenv>=1.2.2
Requires-Dist: questionary>=2.1.1
Requires-Dist: typer>=0.26.4
Requires-Dist: uvicorn>=0.34.0
Description-Content-Type: text/markdown

# Repster

**Lightweight scheduling and observability for dlt pipelines.**

[dlt](https://dlthub.com) loads your data; Repster runs it. Add one decorator to an existing dlt pipeline and get a scheduler, run history, retries, and a web UI. No orchestrator to deploy, no service to babysit. When pipelines need to run without your laptop open, `rp deploy` moves the same code to Repster Cloud (managed scheduling and an isolated serverless worker per run).

```bash
uv add repster
```

## Docs

User documentation is published to [docs.repster.online](https://docs.repster.online).

| Section | Purpose |
|---------|---------|
| [Quickstart](https://docs.repster.online/tutorials/quickstart/) | build and run your first flow |
| [Why Repster?](https://docs.repster.online/explanation/why-repster/) | how it compares to cron, orchestrators, and managed ELT |
| [CLI reference](https://docs.repster.online/reference/cli/) | all `rp` commands |
| [Configuration](https://docs.repster.online/reference/configuration/) | profiles, env vars, pyproject.toml |
| [How-to guides](https://docs.repster.online/how-tos/manage-secrets/) | recipes for specific tasks |
| [Explanation](https://docs.repster.online/explanation/how-repster-works/) | concepts and background |

## Local UI

`repster dev` starts a local web UI at `http://localhost:8080`: see all discovered flows, trigger runs, and stream logs. No account needed. Deployments, secrets, and team management live in the Repster Cloud UI ([repster.online](https://repster.online)).

## Philosophy

Pipelines belong in code, state should be visible and replayable, and pricing should reflect actual compute consumed, nothing more. Pipelines are code and every operation around them is a CLI command, which makes Repster as operable by AI coding agents as by humans. The SDK is open source (Apache-2.0) so developers can trust it: everything the CLI transmits to Repster Cloud is inspectable. The managed layer exists because running reliable distributed infrastructure is genuinely hard, and that's what Repster takes off your plate. The code is yours; we help you run it.

## Developing the docs

The docs site is built with [MkDocs Material](https://squidfunk.github.io/mkdocs-material/); dependencies are declared in `pyproject.toml`. From the `repster/` directory:

```bash
uv run --group docs mkdocs serve   # live-reload server at http://127.0.0.1:8001
uv run --group docs mkdocs build   # static site in site/ (what GitHub Pages deploys)
```
