semvec/pypi-packages huggingface dataset:
sparkctl 0.3.1
Orchestrates Spark standalone clusters on HPCs.
Requires Python: <3.14,>=3.11

# sparkctl
This package implements configuration and orchestration of Spark clusters with standalone cluster
managers. This is useful in environments like HPCs where the infrastructure implemented by cloud
providers, such as AWS, is not available. It is particularly helpful when users want to deploy Spark
but do not have administrative control of the servers.

## Example usage
There are two main ways to use this package:

First, allocate compute nodes. For example, with Slurm (1 compute node for the Spark master and
4 compute nodes for Spark workers):
   
```console
$ salloc -t 01:00:00 -n4 --partition=shared --mem=30G : -N4 --account=<your-account> --mem=240G
```
  
1. Configure a Spark cluster and run Spark jobs with `spark-submit` or `pyspark`.
```console
$ sparkctl configure
$ sparkctl start
$ spark-submit --master spark://$(hostname):7077 my-job.py
$ sparkctl stop
```

2. Run Spark jobs in a Python script using the `sparkctl` library to manage the cluster.
```python
from sparkctl import ClusterManager, make_default_spark_config

config = make_default_spark_config()
mgr = ClusterManager(config)
with mgr.managed_cluster() as spark:
    df = spark.createDataFrame([(x, x + 1) for x in range(1000)], ["a", "b"])
    df.show()
```

Refer to the [user documentation](https://nrel.github.io/sparkctl/) for a description of features
and detailed usage instructions.

## Project Status
The package is actively maintained and used at the National Renewable Energy Laboratory (NREL).
The software is primarily geared toward HPCs that use Slurm. It also supports a generic list of
servers as long as the servers have access to a shared filesystem and are accessible via SSH without
password login.

It would be straightforward to extend the functionality to support other HPC resource managers.
Please submit an issue or idea or discussion if you have interest in this package but need that
support.

Contributions are welcome.

## License
sparkctl is released under a BSD 3-Clause [license](https://github.com/NREL/sparkctl/blob/main/LICENSE).

## Software Record
This package is developed under NREL Software Record SWR-25-109.
boxclever 0.1.0
Shared business logic for BoxClever services
Requires Python: >=3.13

# BoxClever Core Package

Shared business logic package for BoxClever services (API, workers, future services).

## Structure

- `boxclever/integrations/` - Vendor integrations (OpenAI, ElevenLabs)
- `boxclever/models/` - Shared domain models (options, media, firestore)
- `boxclever/utils/` - Shared utilities (payload builders, serialization)
- `boxclever/clients.py` - Shared client initialization

## Usage

This package is used as a local dependency in `apps/api` and `apps/workers`:

```toml
dependencies = [
    "boxclever @ file://../packages/core",
]
```

## Critical Constraints

- **No Circular Dependencies**: This package must NEVER import from `apps/api`, `apps/workers`, or any app-specific code.
- **Pure Business Logic**: Contains only vendor integrations and shared domain models, not infrastructure-specific code.
nextline-alert 0.10.1
A plugin of nextline-graphql. Emit alerts to Campana
Requires Python: >=3.10
Keywords: alert, campana, graphql, nextline, plugin

# nextline-alert

[![PyPI - Version](https://img.shields.io/pypi/v/nextline-alert.svg)](https://pypi.org/project/nextline-alert)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/nextline-alert.svg)](https://pypi.org/project/nextline-alert)

[![Test Status](https://github.com/simonsobs/nextline-alert/actions/workflows/unit-test.yml/badge.svg)](https://github.com/simonsobs/nextline-alert/actions/workflows/unit-test.yml)
[![Test Status](https://github.com/simonsobs/nextline-alert/actions/workflows/type-check.yml/badge.svg)](https://github.com/simonsobs/nextline-alert/actions/workflows/type-check.yml)
[![codecov](https://codecov.io/gh/simonsobs/nextline-alert/branch/main/graph/badge.svg)](https://codecov.io/gh/simonsobs/nextline-alert)

A plugin for [nextline-graphql](https://github.com/nextline-dev/nextline-graphql).
Emit alerts to [Campana](https://github.com/simonsobs/campana)

## Installation

```console
pip install nextline-alert
```

## Alert types

- **Run failed:** The script execution by `nextline` ended with an uncaught
  exception except for `KeyboardInterrupt`.
- **Idle:** The time specified by `NEXTLINE_ALERT__IDLE_TIMEOUT_MINUTES`
  minutes has passed without the script execution since the last run ended or
  the backend started.

## Configuration

| Environment variable                   | Default value             | Description                 |
| -------------------------------------- | ------------------------- | --------------------------- |
| `NEXTLINE_ALERT__CAMPANA_URL`          | `http://httpbin.org/post` | The CAMPANA endpoint        |
| `NEXTLINE_ALERT__PLATFORM`             | `localhost`               | The platform name           |
| `NEXTLINE_ALERT__IDLE_TIMEOUT_MINUTES` | 20.0                      | The idle timeout in minutes |
eo4eu-data-utils 1.0.0
General data access utilities for EO4EU
Requires Python: >=3.10

![The EO4EU logo](./docs/source/eo4eu-logo.png)

Funded by the EU.

# Data utilities for EO4EU

This package provides classes and functions that help with common tasks involving:

- Reading data from configMaps and secrets
- Uploading to and downloading from S3 buckets
- Configuring components in general

The current API is unstable and the previous readme was outdated. New documentation will be provided once the package stabilizes.
diffweave-ai 1.2.2
Assists with git workflows using LLMs.
Requires Python: >=3.9

# DiffWeave AI

DiffWeave is a tool that automatically generates meaningful Git commit messages using large language models (LLMs). It analyzes your staged changes and creates descriptive commit messages, saving you time and ensuring consistent documentation.

[Documentation available here](https://block.github.io/diffweave-ai/)

![Demo](docs/images/demo.png)

## Installation & Quick Start

You can run DiffWeave via `uvx diffweave-ai` or from a local checkout using `uv run diffweave-ai` while developing this repo.

DiffWeave is installed as an isolated tool using `uv`:

```bash
# Make sure you have uv installed first
# https://docs.astral.sh/uv/getting-started/installation/

uvx diffweave-ai
```

## Usage

### Configure a model

Before generating commit messages, configure at least one model endpoint:

```bash
uvx diffweave-ai add-model \
  --model "name-of-your-model" \
  --endpoint "https://endpoint-url" \
  --token "$TOKEN"
```

Then set the default model to use:

```bash
uvx diffweave-ai set-model "name-of-your-model"
```

You can still override the model per invocation with the `--model` / `-m` flag.

### Generate a commit message

Once you have a model configured and some changes staged in your current Git repository you can run:

```bash
uvx diffweave-ai
```

This will:

- Show the current `git status`.
- Optionally stage files for you (interactive by default).
- Generate a commit message using your configured model.
- Let you review/refine the message.
- Attempt `git commit` (and optionally `git push` and PR open if a URL is printed).

To specify a model for a single run:

```bash
uvx diffweave-ai -m "your-model-name"
```

If you prefer a simpler, more natural-language commit style rather than Conventional Commits, pass `--simple`:

```bash
uvx diffweave-ai --simple
```

You can also run in dry-run mode (generate and print a commit message without committing):

```bash
uvx diffweave-ai --dry-run
```

Or in a non-interactive mode, which will generate a message and attempt to commit and push without asking follow-up questions:

```bash
uvx diffweave-ai --non-interactive
```

## Features

- AI-powered commit message generation based on staged diffs
- Interactive or non-interactive workflows
- Support for configuring custom LLM HTTP endpoints
- Ability to set and override the default model
- Optional simpler commit style via `--simple`
- Optional push and PR-open flow when `git push` prints a URL