semvec/pypi-packages huggingface dataset:
sbcli-mc 1.2.7
CLI for managing SimplyBlock cluster


# Simply Block
[![Docker Image Build](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml)

[![Python Unit Testing](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml)

 
## Install
Add the package repo from AWS CodeArtifact using [awscli](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)

```bash
aws codeartifact login --tool pip --repository sbcli --domain simplyblock --domain-owner 565979732541 --region eu-west-1
```
Install package
```bash
pip install --extra-index-url https://pypi.org/simple sbcli-dev
```

# Components 

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
Please see this document 
[README.md](../main/simplyblock_cli/README.md)


## Simply Block Web API
Please see this document 
[README.md](../main/simplyblock_web/README.md)
fuzzycollections 0.0.4
Fuzzy collections
Requires Python: >=3.7

# fuzzycollections

Find values in a collection which are similar according to some distance function.

## Install

- `pip install fuzzycollections[all]` to install with all dependencies. If installed without dependencies, the requirements will depend on which collection class is used.

## Collections

- `BkCollection`: Uses a BK-Tree to find similar matches quickly. Requires a real mathematical metric as distance function.
- `LinearCollection`: Simply uses a linear search through all collection items to find close matches. Distance function can be anything.
plex-assets-manager 0.1.1
A Python project for managing and organizing Plex media library
Requires Python: >=3.11

# Plex Assets Manager

A Python project for managing and organizing Plex media library.

## Features

- Reorganize movie folders
- Rename movie files
- Download trailers
- Download subtitles

## Installation

To install the package, you can use `pip`:

```bash
pip install plex-assets-manager
```

## Usage

You can use the package by running the main script with the desired function:

```bash
python -m plex_assets_manager <function_id> [options]
```

### Functions

1. **Reorganize folders**: Reorganize movie folders.
2. **Rename movie files**: Rename movie files to a standard format.
3. **Download trailers**: Download trailers for movies.
4. **Download subtitles**: Download subtitles for movies.

### Example

To reorganize folders, you would run:

```bash
python -m plex_assets_manager 1
```

## Command Line Options

- `-q`, `--quiet`: Quiet Mode: no logging of intermediate steps.
- `-l`, `--log`: Writes logs to a log file. Default is to show on console.
- `-t`, `--token`: Plex API token. If not specified, the value is taken from the conf file.
- `-u`, `--url`: Plex URL. If not specified, the value is taken from the conf file.
- `-m`, `--movielib`: Name of the Films library in Plex. If not specified, the value is taken from the conf file.

## Configuration

Configuration settings are managed in the `conf.py` file. Ensure you update this file with your specific settings.

```python
# conf.py
PLEX_API_TOKEN = 'your_plex_api_token_here'
OPENSUBTITLES_API_KEY = 'your_opensubtitles_api_key_here'
PLEX_URL = "http://127.0.0.1:32400"
MOVIES_LIBRARY = 'Movies'
LOG = True
QUIET = False
MIN_VIEWS = 10000
MAX_FILESIZE_MB = 100
MIN_FILESIZE_MB = 1
MAX_SLEEP_DURATION = 15
MAX_DAILY_SUB_DOWNLOADS = 20
SUB_DOWNLOAD_TRACK_FILE = "sub_download_tracker.txt"
```

## Running the Package

To run the package, use the following command format:

```bash
python -m plex_assets_manager <function_id> [options]
```

### Example Command

To download all trailers:

```bash
python -m plex_assets_manager 3
```

## Contributing

Contributions are welcome! Please fork the repository and submit a pull request.

## License

This project is licensed under the MIT License.
```
quantagonia-api-client 0.85
This package contains APIs for accessing Quantagonia's HybridSolver for solving MIPs and QUBOs through native file formats or PuLP resp. PyQUBO, Qiskit, or Ocean
Keywords: Optimization, Linear Programming, Operations Research

# Quantagonia API Client

This package contains Quantagonia's CLI client and client-side APIs for using HybridSolver in the cloud.

## Installation

Python >= 3.8 is required. Then, do
```
python -m pip install quantagonia-api-client
```
In order to use HybridSolver through Quantagonia's cloud system, you'll need to sign up for an API key and set it system-wide by
```
export QUANTAGONIA_API_KEY=<your API key here>
```

## Quick start: using the CLI client

This package provides the script `hybridsolver` to interact with the
cloud solver. In order to solve a MIP (supported formats: `.mps, .lp,
.mps.gz, .lp.gz`) or QUBO (spported formats: `.qubo, .qubo.gz`), just
use
```
hybridsolver solve path/to/example.mps
```
which will automatically set all parameters and solver controls to their default value, which is a good compromise for many middle-sized
optimization problems out there.

The `solve` call has a few options (try `hybridsolver solve --help`) and will, after submitting the problem, stream the logs and output the
solution vector if one is found.

To start a job without attaching to its log stream and leave it running in the background, use
```
hybridsolver submit path/to/example.mps
```
which supports the same parameters as `solve` and returns a `job_id`.
using this ID, logs, results and job status as well as time billed can
be retrieved using
```
hybridsolver (logs | solution | status | time_billed) job_id
```
Lastly, in order to cancel a runnning job and avoid unnecessary
costs, use `hybridsolver cancel job_id`. To list `k` active and/or past jobs,
use `hybridsolver list --n=k`.

## Using the API client in your own code

The capabilities of the API client include, but are not limited to:
- a plugin for PuLP to solve PuLP-generated models locally and in the client,
- a simple API to model QUBOs locally and solve them in the cloud and
- an importer to convert PyQUBO models into our format - allowing to solve PyQUBO models in QUantagonia's cloud.

For starters, you can run the examples in `examples/` through, e.g.,
```
QUANTAGONIA_API_KEY="<redacted>" python examples/submit_qubo.py
```
with a valid Quantagonia API key.

For more details, we refer to our [API reference](https://docs.quantagonia.com).