semvec/pypi-packages huggingface dataset:
arcane-pubsub 1.5.1
Override pubsub client
Requires Python: <4.0,>=3.6

# Arcane PubSub

This package is base on [google-cloud-pubsub](https://pypi.org/project/google-cloud-pubsub/).

## Get Started

```sh
pip install arcane-pubsub
```

## Example Usage

```python
from arcane import pubsub

# Import your configs
from configure import Config

client = pubsub.Client(Config.KEY)

client.push_to_topic('project', 'topic', {"parameter": "value"})
```

Publish with a new schema

```python
result = pubsub_client.publish_with_schema(
    project='my-project',
    topic_name='my-topic-with-schema',
    message=message,
    await_response=True,
)
```

Note: `publish_with_schema` caches the topic schema. If you call it in a loop to publish many messages to the same schema topic, it will fetch the schema once and reuse it for the next messages. This avoids excessive `SchemaServiceClient.get_schema(...)` calls and prevents quota errors when publishing at high volume.
kash-media 0.3.19
The knowledge agent shell (media kit)
Requires Python: <3.14,>=3.13

# kash-media

See the main [kash](https://github.com/jlevy/kash) repo for general instructions.

To run kash with the the media kit features enabled, ensure you have uv set up then:

```shell
uv tool install kash-media --upgrade --force
kash
```

Or for dev builds from within this git repo:

```shell
# Install all deps and run tests:
make
# Run kash with all media kit features enabled:
uv run kash
```

* * *

*This project was built from
[simple-modern-uv](https://github.com/jlevy/simple-modern-uv).*
tszip 0.3.0
Compression utilities for tree sequences
Requires Python: >=3.10
Keywords: tree sequence, tskit

# tszip
[![License](https://img.shields.io/github/license/tskit-dev/tszip)](https://github.com/tskit-dev/tszip/blob/main/LICENSE) [![PyPI version](https://img.shields.io/pypi/v/tszip.svg)](https://pypi.org/project/tszip/) [![Supported Python Versions](https://img.shields.io/pypi/pyversions/tszip.svg)](https://pypi.org/project/tszip/) [![Docs Build](https://github.com/tskit-dev/tszip/actions/workflows/docs.yml/badge.svg)](https://github.com/tskit-dev/tszip/actions/workflows/docs.yml) [![Binary wheels](https://github.com/tskit-dev/tszip/actions/workflows/wheels.yml/badge.svg)](https://github.com/tskit-dev/tszip/actions/workflows/wheels.yml) [![Tests](https://github.com/tskit-dev/tszip/actions/workflows/tests.yml/badge.svg)](https://github.com/tskit-dev/tszip/actions/workflows/tests.yml) [![codecov](https://codecov.io/gh/tskit-dev/tszip/branch/main/graph/badge.svg)](https://codecov.io/gh/tskit-dev/tszip)

Gzip-like compression for [tskit](https://tskit.dev/software/tskit.html) tree sequences. Compression is lossless for supported tskit tree sequences.

Please see the [documentation](https://tskit.dev/tszip/docs/stable/) ([latest](https://tskit.dev/tszip/docs/latest/)) for more details
and [installation instructions](https://tskit.dev/tszip/docs/stable/installation.html).

## Installation

Install from PyPI or conda-forge:

```
python -m pip install tszip
# or
conda install -c conda-forge tszip
```

## Quickstart

CLI usage:

```bash
# Compress a .trees file to a .tsz archive
tszip data.trees

# Decompress back to .trees
tsunzip data.trees.tsz
```

Along with the CLI, tszip can be used directly from Python:

```python
import tskit
import tszip

ts = tskit.load("data.trees")
tszip.compress(ts, "data.trees.tsz")  # write compressed archive

restored = tszip.load("data.trees.tsz")  # load handles .tsz archives and plain .trees files
print(restored.equals(ts))  # True
```