semvec/pypi-packages huggingface dataset:
sr.comp.http 1.9.0
HTTP API for Student Robotics Competition Software
Requires Python: >=3.9

SR Comp HTTP
============

|Build Status| |Docs Status|

A HTTP interface around `SRComp <https://github.com/PeterJCLaw/srcomp/wiki/SRComp>`__,
the fifth round of `Student Robotics <https://studentrobotics.org>`__ competition
software.

This repository provides a JSON API to accessing information about the
state of the competition. It is a lightweight
`Flask <https://palletsprojects.com/p/flask/>`__ application wrapping the
`SRComp <https://github.com/PeterJCLaw/srcomp>`__ python
APIs to the competition state.

Usage
-----

**Install**:

.. code:: shell

    pip install sr.comp.http

**Configuration**

In deployment you should configure the app by setting the ``COMPSTATE`` key of
the app's config to the absolute path of the compstate which the server intends
to serve.

.. code:: python

    from sr.comp.http import app
    app.config['COMPSTATE'] = '/path/to/compstate'

Development
-----------

**Clone**:

For tests to work, you will need to clone the `tests/dummy` submodule too:

``git submodule update --init``

**Install**:

.. code:: shell

    pip install -e .

**Run**:
``./run $COMPSTATE``.

**Test**:
``./run-tests``

Developers may wish to use the `SRComp Dev`_ repo to setup a dev instance.

State Caching
~~~~~~~~~~~~~

Since loading a given state repo takes a non-trivial amount of time,
this is cached within the Flask application. Updates to the state repo
are not tracked directly, and must be signalled by running the
``./update`` script provided.


.. |Build Status| image:: https://circleci.com/gh/PeterJCLaw/srcomp-http.svg?style=svg
   :target: https://circleci.com/gh/PeterJCLaw/srcomp-http

.. |Docs Status| image:: https://readthedocs.org/projects/srcomp-http/badge/?version=latest
   :target: https://srcomp-http.readthedocs.org/

.. _`SRComp Dev`: https://github.com/PeterJCLaw/srcomp-dev
py-solana-cli 1.4
SolanaCLI on Python

# py-solana-cli

`py-solana-cli` — это библиотека для взаимодействия с блокчейном Solana с использованием Python. Библиотека предоставляет основные функции для работы с Solana, включая показ баланса, переводы средств и работу с контрактами.

## Установка

Для установки библиотеки используйте pip:

pip install py-solana-cli

Использование

Импорт и создание клиента

from py_solana_cli.client import SolanaClient

from py_solana_cli.account import SolanaAccount

from py_solana_cli.contract import SolanaContract

# Инициализация клиента

client = SolanaClient(rpc_url="http://localhost:8899")

# Показ баланса

balance = client.get_balance("your_public_key")

print(f"Баланс: {balance}")

# Перевод средств

client.transfer(from_key="your_from_key", to_key="your_to_key", amount=10.0)

# Работа с аккаунтами

account = SolanaAccount()

account_info = account.get_account_info("your_public_key")

print(f"Информация об аккаунте: {account_info}")

# Деплой контракта

contract = SolanaContract()

contract.deploy_contract("your_contract_code")

# Вызов функции контракта

contract.call_contract("contract_address", "function_name", ["arg1", "arg2"])

Функции

get_balance(public_key: str): Показать баланс указанного публичного ключа.

transfer(from_key: str, to_key: str, amount: float): Перевести указанную сумму от одного ключа к другому.

create_account(): Создать новый аккаунт.

get_account_info(public_key: str): Получить информацию об аккаунте.

deploy_contract(contract_code: str): Деплой контракта.

call_contract(contract_address: str, function_name: str, args: list): Вызов функции контракта.

Пример использования

Вот как можно использовать библиотеку для различных задач:

from py_solana_cli.client import SolanaClient

client = SolanaClient(rpc_url="http://localhost:8899")

# Показ баланса

balance = client.get_balance("your_public_key")

print(f"Баланс: {balance}")

# Перевод средств

client.transfer(from_key="your_from_key", to_key="your_to_key", amount=10.0)

Контрибьюция

Если вы хотите внести изменения или добавить новые функции, пожалуйста, создайте форк репозитория и отправьте pull request.

Лицензия

Этот проект лицензирован под MIT License. См. LICENSE для подробностей.
SupervisedMF 0.0.4
A package for various supervised matrix factorization methods
Requires Python: >=3.10
Keywords: supervised matrix factorization, matrix factorization, dimensionality reduction, low-rank compression, classification

# Supervised Matrix Factorization

This Python package contains source codes for algorithms for Supervised Matrix Factorization (SMF) in the papers [1] and [2]: 

## Installation

To install the package, run the following command in your environment:

```
python3 -m pip install SupervisedMF
```

Check your installation by trying to import the main classes in this package:

```
>>> from SMF import SMF_BCD
>>> from SMF import SMF_LPGD
```

## Pytorch Version

If you are looking to use the Pytorch version of the Supervised Matrix Factorization algorithms, please first install `torch` and its related dependencies in your environment using the appropriate command from [the official installation page](https://pytorch.org/get-started/locally/). 

For example, if you want to install `torch` for Linux with CUDA 12.1 using `pip`, run the following command:

```
pip3 install torch torchvision torchaudio
```

## References

[1] Lee, Joowon, Hanbaek Lyu, and Weixin Yao. [*"Exponentially convergent algorithms for supervised matrix factorization."*](https://papers.nips.cc/paper_files/paper/2023/hash/f2c80b3c9cf8102d38c4b21af25d9740-Abstract-Conference.html) Advances in Neural Information Processing Systems 36 (2024).

[2] Lee, Joowon, Hanbaek Lyu, and Weixin Yao. [*"Supervised Matrix Factorization: Local Landscape Analysis and Applications."*](https://proceedings.mlr.press/v235/lee24p.html) Forty-first International Conference on Machine Learning (2024).