semvec/pypi-packages huggingface dataset:
Invenio-Theme-TUW 2026.0.1
TU Wien corporate design for InvenioRDM.
Requires Python: >=3.12
Keywords: corporate design, invenio, theme, tu wien

..
    Copyright (C) 2020 - 2026 TU Wien.

    Invenio-Theme-TUW is free software; you can redistribute it and/or
    modify it under the terms of the MIT License; see LICENSE file for more
    details.

===================
 Invenio-Theme-TUW
===================

This package belongs to the `TU Wien suite of InvenioRDM customizations <https://gitlab.tuwien.ac.at/crdm>`__ that make up `TU Wien Research Data <https://researchdata.tuwien.ac.at>`__.

It provides various frontend components to give it the distinct look and feel of TU Wien services.
Also, it also brings some extra functionality and new endpoints.



Features
========

Some of the features provided by this package:

* TU Wien corporate design
* Form to contact the owner of records
* Guarded record deposit & community creation pages
* Per-community page with summarized download statistics for its records
* Extra pages with information related to the service at TU Wien (policies, contact, "about" pages, ...)
* Web UI for composing outreach emails to users in the system
* Small bespoke admin pages geared towards use at TU Wien
* Greetings from the Easter Bunny
* Etc.


Even though not strictly a provided feature, the extended testing setup is also noteworthy (see below).



Installation
============

After installing Invenio-Theme-TUW (e.g. via ``pip``), Invenio's assets have to be updated:

.. code-block:: console

   $ pip install invenio-theme-tuw  # or another package manager
   $ invenio-cli assets build



Tests
=====

To execute the tests, the project has to be installed locally.
Then, the ``run-tests.sh`` script can be executed.

.. code-block:: console

   $ uv sync --all-extras
   $ source .venv/bin/activate
   $ ./run-tests.sh
   $ deactivate



Testing setup
-------------

In addition to the usual events like merge requests, the tests are run nightly via GitLab CI/CD.

The definition for the installed environment (``uv.lock``, also exported as ``requirements.txt``) is provided as job artifacts to developers.
This makes it easier to diagnose breakage due to dependency upgrades.

Further, we're checking our overrides (like Jinja templates and JS) against the latest upstream definitions as part of the tests.
In combination with the nightly tests, this provides us with an early warning system about changes that need chasing.
transactions-mcp 1.0.0
Add your description here
Requires Python: >=3.12

# mcp-name: io.github.manoharanRajesh/python-version

## Pre-requisites

* Python
* uv
* NodeJs
* NPX
* Cert and key needs to be added in root directory with the name "client_cert.pem", "client_key.pem"

## Set Up

```uv sync```
```npm install @modelcontextprotocol/inspector```

## Run Inspector

```npx @modelcontextprotocol/inspector uv  run main```

##Commands that might help
```uv init <<project name>>```
strangeworks-optimization 0.2.44
This SDK extends the Strangeworks SDK to provide access to the Strangeworks Optimization API.
Requires Python: <3.14,>=3.11

[![PyPI version](https://img.shields.io/pypi/v/strangeworks-optimization.svg)](https://pypi.org/project/strangeworks-optimization/)
[![Python version](https://img.shields.io/pypi/pyversions/strangeworks-optimization.svg)](https://pypi.org/project/strangeworks-optimization/)
[![Documentation](https://img.shields.io/badge/docs-strangeworks.com-blue)](https://docs.strangeworks.com/optimization/)

# Strangeworks Optimization

The **Strangeworks Optimization SDK** provides an abstraction layer for solving optimization problems using classical, quantum-inspired, and quantum solvers. It enables you to seamlessly switch between different optimization backends while maintaining a consistent interface.

## Features

- **Unified API** for multiple optimization solvers (quantum, quantum-inspired, and classical)
- **Support for multiple problem formats** including QUBO, MPS, LP, and more
- **Solver-agnostic interface** that allows easy switching between providers
- **Job management** with status tracking and result retrieval

## Installation

```bash
pip install strangeworks-optimization
```

## Quick Start

```python
import strangeworks as sw
from dimod import BinaryQuadraticModel
from strangeworks_optimization import StrangeworksOptimizer

# Authenticate with your API key
sw.authenticate("your-api-key")

# Create a QUBO model
linear = {1: -2, 2: -2, 3: -3, 4: -3, 5: -2}
quadratic = {(1, 2): 2, (1, 3): 2, (2, 4): 2, (3, 4): 2, (3, 5): 2, (4, 5): 2}
model = BinaryQuadraticModel(linear, quadratic, "BINARY")

# Create and run the optimizer with Quantagonia
optimizer = StrangeworksOptimizer(model=model, solver="quantagonia.qubo")
job = optimizer.run()

# Get results
results = optimizer.results(job.slug)
print(results.solution)
```

## Documentation

Comprehensive documentation is available at [docs.strangeworks.com/optimization](https://docs.strangeworks.com/optimization/).

The documentation includes:
- Getting started guides
- API reference
- Supported solvers and providers
- Problem format specifications
- Examples and tutorials

## Supported Solvers

The SDK supports a wide range of optimization solvers including:

- **Classical solvers**: Gurobi, Quantagonia
- **Quantum annealers**: D-Wave Leap, D-Wave Sampler
- **Quantum-inspired**: Hitachi, NEC, Toshiba
- **Hybrid solvers**: D-Wave Hybrid, Strangeworks Hybrid

For a complete list and solver-specific configuration options, see the [documentation](https://docs.strangeworks.com/optimization/).

## Requirements

- Python 3.11 or higher
- A Strangeworks account and API key ([Get started](https://portal.strangeworks.com))

## License

This project is licensed under the Apache License 2.0.

## Support

For support, questions, or feature requests, please visit:
- [Documentation](https://docs.strangeworks.com/optimization/)
- [Strangeworks Portal](https://portal.strangeworks.com)