semvec/pypi-packages huggingface dataset:
promplate 0.3.5.6
Prompt engineering framework for humans
License: MIT
Requires Python: <4.0,>=3.10
Keywords: prompt, template, nlp, llm

# Promplate

```text
</Promplate/> = <template> // prompt
```

**Promplate** is a prompting framework focusing on developing experience. However, it can also be a super-convenient SDK for simple LLM calls. Promplate progressively enhance your prompting workflow. And it values flexibility as well as perfect conventions. [Try online](https://promplate.dev/py)

## Installation

```shell
pip install promplate
```

**Promplate** supports both CPython and PyPy, from `3.8` to `3.13`. It even supports running in browsers through wasm implementations of python.

## Documentation

You can visit our official docs site at [docs.py.promplate.dev](https://docs.py.promplate.dev/).

## IDE Support 🌹

**Promplate** is fully typed, which means static type checker will find bugs correctly (if you use `pyright` for type checking).

We recommend using VS Code as your IDE when coding with promplate, because it natively uses pyright.

The language design of promplate is similar to `Jinja2`. So you can use the `.j2` file extension for template files for syntax highlight.

## Development

- use `poetry` to manage dependencies.
- use `isort` to sort import statements.
- use `black` to format code.
- use `pyright` to check type annotations.

Development should be done on `dev` branch, using `>=3.10` language features. The `master` branch is used for `py3.8` compatible releases.

**Promplate** is well tested with `pytest`. GitHub Actions are used to run tests and linting. And there are test results continually generated on [Vercel](https://promplate-core.vercel.app/) and [Netlify](https://promplate-core.netlify.app/). There is [a coverage report](https://promplate-python-coverage.onrender.com/) too.

## Future Features (or TODOs?)

- [ ] more documentation
- [ ] javascript implementation
- [x] improved error handling
  - display compiled code when error occurs through `linecache` or `tempfile`
yottactl 0.1.6
This is a lightweight library that works as a connector to Yottalabs public API.
License: MIT
Requires Python: >=3.8
Keywords: yotta, Public API

# Yottalabs Public API Connector (Python)

A lightweight Python library for connecting to
the [Yottalabs public API](https://docs.yottalabs.ai/yotta-labs/api-and-sdk/api-spec).  
Easily interact with `/openapi/v1/*` endpoints, with support for custom base URLs, request timeouts, HTTP proxies, and
more.

## Requirements

- Python 3.8 or higher

## Installation

```bash
pip install yottactl
```

## Quickstart

```python
from yotta.pod import PodApi

# API key is required for user data endpoints
client = PodApi(api_key='<api_key>')

params = {
    "image": "yottalabsai/pytorch:2.8.0-py3.11-cuda12.8.1-cudnn-devel-ubuntu22.04-2025090101",
    "gpu_type": "NVIDIA_L4_24G",
    "gpu_count": 1,
    "expose": [
        {"port": 22, "protocol": "SSH"}
    ]
}

response = client.new_pod(**params)
print(response)
```

## Customization

- **Base URL:**  
  If not provided, defaults to `https://api.yottalabs.ai`.

- **Timeout:**  
  Set the `timeout` parameter (in seconds) to control how long to wait for a server response.  
  By default, requests do not time out.

  ```python
  client = PodApi(timeout=1)
  ```

- **Logging:**  
  Set the log level to `DEBUG` to log request URLs, payloads, and responses.

  ```python
  client = PodApi(debug=True)
  ```

## Error Handling

Two types of errors are raised:

- `yotta.error.ClientError`  
  Raised for 4XX client errors. Properties:
    - `status_code`: HTTP status code
    - `error_code`: Server error code (if available)
    - `error_message`: Server error message
    - `header`: Full response headers
    - `error_data`: Additional data (if provided)

- `yotta.error.ServerError`  
  Raised for 5XX server errors.

## Contributing

Contributions are welcome! Please open issues or pull requests.

## License

[MIT](LICENSE)
PyGCGOpt 1.0.0b0
Python interface and modeling environment for GCG
License: MIT
Requires Python: >=3.8

PyGCGOpt
=========

This project provides an interface from Python to the [GCG Solver](https://gcg.or.rwth-aachen.de/).

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

See [CHANGELOG.md](CHANGELOG.md) for added, removed or fixed functionality.

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

**Using Conda**

[![Conda version](https://img.shields.io/conda/vn/conda-forge/pygcgopt?logo=conda-forge)](https://anaconda.org/conda-forge/pygcgopt)
[![Conda platforms](https://img.shields.io/conda/pn/conda-forge/pygcgopt?logo=conda-forge)](https://anaconda.org/conda-forge/pygcgopt)

Conda will install `GCG`, `SCIP` and `PySCIPOpt` automatically, hence everything can be installed in a single command:
```bash
conda install --channel conda-forge pygcgopt
```

**Using PyPI and from Source**

See [INSTALL.md](INSTALL.md) for instructions.
Please note that the latest PyGCGOpt version is usually only compatible with the latest major release of the SCIP Optimization Suite and the GCG Solver.
Information which version of PyGCGOpt is required for a given GCG version can also be found in [INSTALL.md](INSTALL.md).