semvec/pypi-packages huggingface dataset:
jetbrains-cadence 1.2.1
JetBrains Cadence CLI
Requires Python: >=3.11

# Cadence CLI

## Install

```shell
pip install jetbrains-cadence
```

This will create a `cadence` script in your current environment.

## Getting Started

```shell
cadence login
```

If you want to use Cadence CLI in the non-interactive environment, you
can [create the token manually](https://api.cadence.jetbrains.com/app/jettrain/token.html) and pass it via
`CADENCE_TOKEN` environment variable

### Start the execution from YAML config

```shell
cadence execution start --preset path/to/config.yaml
```

This will print the ID of the started execution.

### Basic Example

```yaml
working_dir: .
cmd:
  - python3 main.py
description: basic preset

provisioning:
  gpu_type: H200
  gpu_count: 1

env:
  python:
    version: 3.11
    pip:
      requirements_path: requirements.txt

project_sync:
  local:
    root: .
    storage_name: Cadence Storage
    uri: ""
    storage_type: DEFAULT

outputs:
  - type: OUTPUT
    storage_name: Cadence Storage
    uri: ""
    path: outputs # `./outputs` will be saved to S3
    storage_type: DEFAULT
```

### More Examples

Please see the [cadence-examples](https://github.com/JetBrains/cadence-examples) repository for more in-depth examples.
pspipe 0.7.2
Power spectra pipeline for Cosmic Dawn, Epoch of Reionization radio interferometric experiments
Requires Python: <4.0,>=3.10

Power Spectra Generation pipeline for CD/EoR experiments
========================================================

pspipe is an analysis pipeline which aims to make generation of high precision power-spectra for Cosmic Dawn and Epoch of Reionization experiments as easy and reproducible as possible. pspipe is the default analysis pipeline of the [Lofar-EoR](http://www.lofar.org/astronomy/eor-ksp/epoch-reionization.html) and [NenuFAR](https://nenufar.obs-nancay.fr/en/homepage-en/) CD projects. It performs all tasks from calibrated data to final the power-spectra, including:

- Post-calibration flagging (using [AOflagger](https://sourceforge.net/p/aoflagger/wiki/Home/) and [SSINS](https://arxiv.org/abs/1906.01093))
- Visibility gridding (using [WSClean](https://sourceforge.net/p/wsclean/wiki/Home/))
- Foregrounds modeling and removal (using [GPR](https://doi.org/10.1093/mnras/sty1207), [GMCA](https://arxiv.org/abs/1209.4769), polynomial fitting)
- Optimal power-spectra generation (using [ps_eor](https://gitlab.com/flomertens/ps_eor))

Thanks to its multi-nodes concurrent processing, pspipe is also very fast at crunching hundreds of hour of calibrated data.

Installation
------------

pspipe can be installed via pip:

    $ pip install pspipe

and requires Python 3.7.0 or higher. For certain tasks, you will also need [DPPP](https://github.com/lofar-astron/DP3/tree/master/DPPP) and [WSClean](https://sourceforge.net/p/wsclean/wiki/Home/)

Documentation
--------------

Please check the [wiki page](https://gitlab.com/flomertens/pspipe/-/wikis/home).
supacrawler-py 0.1.8
Typed Python SDK for Supacrawler API (scrape, jobs, screenshots, watch)
Requires Python: >=3.9

# supacrawler-py

Typed Python SDK for Supacrawler API.

## Install

- From PyPI (when published):
```bash
pip install supacrawler-py
```

- With uv (PEP 621 aware):
```bash
uv add supacrawler-py
# or for local dev
uv pip install -e .
```

- From local path (development):
```bash
pip install -e .
```

- From GitHub (direct):
```bash
pip install git+https://github.com/Supacrawler/supacrawler-py.git#subdirectory=sdk/supacrawler-py
```

## Usage

```python
from supacrawler import SupacrawlerClient, ScrapeParams, JobCreateRequest, ScreenshotRequest, WatchCreateRequest

client = SupacrawlerClient(api_key="YOUR_API_KEY")

# Scrape
scrape = client.scrape(ScrapeParams(url="https://example.com", format="markdown"))
print(scrape)

# Create crawl job
job = client.create_job(JobCreateRequest(url="https://supabase.com/docs", type="crawl", depth=2, link_limit=10, format="markdown"))
status = client.wait_for_job(job.job_id)
print(status.status)

# Screenshot job
sjob = client.create_screenshot_job(ScreenshotRequest(url="https://example.com", device="desktop", full_page=True))
print("job:", sjob.job_id)

# Wait and fetch a fresh signed URL (recommended)
signed = client.wait_for_screenshot(sjob.job_id)
print("screenshot:", signed.screenshot)

# Watch
watch = client.watch_create(WatchCreateRequest(url="https://example.com/pricing", frequency="daily", notify_email="me@example.com"))
print(watch.watch_id)
```

### Advanced
- See [`examples/*.ipynb`](https://github.com/Supacrawler/supacrawler-py/tree/main/examples) for full parameter coverage:
  - Scrape: format, wait, device, depth, max_links, fresh
  - Jobs: format, link_limit, depth, include_subdomains, patterns
  - Screenshots: device/full_page/format/quality/viewport/device_scale, waits, selectors, blocking, modes
  - Watch: frequency, selector, include_html/image, full_page, quality, pause/resume/check/delete

## API coverage
- GET `/v1/scrape` (all params)
- POST `/v1/crawl`, GET `/v1/crawl/{id}`
- POST `/v1/screenshots`
- POST `/v1/watch`, GET `/v1/watch`, GET `/v1/watch/{id}`, DELETE `/v1/watch/{id}`, PATCH `/v1/watch/{id}/pause`, PATCH `/v1/watch/{id}/resume`, POST `/v1/watch/{id}/check`

## Development
- Env var: `SUPACRAWLER_API_KEY` for examples.
- Not needed: `requirements.txt` for end-users (deps declared in `pyproject.toml`). Optional `requirements-dev.txt` if you add tests or notebooks tooling.