semvec/pypi-packages huggingface dataset:
pyoci 0.3.4
OCI-runtime spec represented as python objects.
Requires Python: >=3.13

# pyoci

[![image](https://img.shields.io/pypi/v/pyoci.svg)](https://pypi.python.org/pypi/pyoci)
[![image](https://img.shields.io/pypi/l/pyoci.svg)](https://pypi.python.org/pypi/pyoci)
[![image](https://img.shields.io/pypi/pyversions/pyoci.svg)](https://pypi.python.org/pypi/pyoci)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)

**What**: A library to define OCI [Runtime](https://github.com/opencontainers/runtime-spec) and [Image](https://github.com/opencontainers/image-spec) specification compliant container instances.

**When**: When you need to run or modify a container at the lowest level, without docker, containerd or podman.

**Why**: The full OCI specifications can be quite large to read, and even trickier to implement. This library saves you all the json-wrangling and validation, without abstracting any features away.

# notes

* This project has nothing to do with [PyOCI](https://github.com/AllexVeldman/pyoci) - the oci registry proxy for python packages. The current name of this library will most likely be changed in the future.
* This library is heavily WIP, so there are no guarantees about API stability until a 1.x release.
* This is a low-level library. If you want to simply run a container, without configuring all the inner workings, i'd suggest [docker-py](https://github.com/docker/docker-py).
aiocrystal 0.1.1
crystlpay easy interaction
Requires Python: >=3.13

![]('image/aiocrystal_logo.png')


Библиотека полностью повтраяет структуру вложоности https://docs.crystalpay.io/

Создания счета & проверка(не рекомендуеться иза лимита)
``` python
from aiocrystal import CrystalPay
from aiocrystal.utils.types import InvoiceState
import asyncio

cp=CrystalPay(auth_login='name',
              auth_secret='Secret',
              salt='salt'
              )

async def main():
    invoice=await cp.invoice.create(amount=100, description='aiocrystal<3')
    invoice_id=invoice.id
    print(invoice.url)
    while True:
        invoice_state=(await cp.invoice.info(invoice_id)).state
        if InvoiceState.payed == invoice_state:
            print('Succes')
            break
        await asyncio.sleep(5)


asyncio.run(main())
```

WebHook Fastapi & пример фильтров
``` python
from typing import Union

from fastapi import FastAPI

from aiocrystal.v3.async_crystal import CrystalPay
from aiocrystal.utils.types import CallbackInvoice, InvoiceState
from aiocrystal.webhook import FastApiManager

import uvicorn
import asyncio

host=''

app = FastAPI()

cp=CrystalPay(auth_login='name',
     auth_secret='Secret',
     salt='Salt',
     webhook_manager=FastApiManager(
        app_fastapi=app,
        end_point_invoice='/pay/crystalpay'
     )
     )
# пример фильтрации
async def IsPayed(invoice: CallbackInvoice): 
    return invoice.rub_amount >= 100 

async def AntiUnavailableIsPayed(invoice: CallbackInvoice):
    return invoice.state == InvoiceState.payed

@cp.callback_invoice(IsPayed, AntiUnavailableIsPayed) #<- вохможность добавлять несколько фильтров
async def pay_cp(invoice: CallbackInvoice):
    print(f'Пришло: {invoice.rub_amount}')

async def main():
    invoice=await cp.invoice.create(100, callback_url=f'{host}/pay/crystalpay')
    print(invoice.url)


asyncio.run(main())

uvicorn.run(app, host="localhost", port=5000)
simsity 0.8.0
A similarity search library
Requires Python: >=3.8


![landing](https://user-images.githubusercontent.com/1019791/222645884-fd88cd66-3dd0-4b6e-98f4-65586040e538.png)

# simsity

> Simsity is a Super Simple Similarities Service[tm]. <br>
> It's all about building a neighborhood. Literally! <br>

This simple library is partially inspired by [this blogpost by Max Woolfe](https://minimaxir.com/2025/02/embeddings-parquet/). You don't always need a full fledged vector database. Polars and numpy might be all you need. And for those moments, `simsity` is all you need to build a neighborhood!

## Install

You can install simsity via pip.

```
uv pip install simsity
```

The goal of simsity is to be minimal, to make rapid prototyping very easy and to be "just enough" for medium sized datasets. You will mainly interact with these two functions. 

```python
from simsity import create_index, load_index
```

As their names imply, you can use these to create an index or to load one from disk. 

## Quickstart

```python
from simsity import create_index, load_index
from simsity.datasets import fetch_recipes

# Let's fetch some demo data
recipes = fetch_recipes()["text"].to_list()

# Let's use model2vec for embeddings 
from model2vec import StaticModel
model = StaticModel.from_pretrained("minishlab/potion-base-8M")

# Populate the ANN vector index and use it. 
index = create_index(recipes, model.encode)
texts, dists = index.query("pork")

# You can also query using vectors
v_pork = model.encode(["pork"])[0]
texts, dists = index.query_vector(v_pork)
```

You can also provide a path and then you'll be able to store/load everything.

```python
# Make an index with a path
index = create_index(recipes, encoder, path="demo")

# Load an index from a path
reloaded_index = load_index(path="demo", encoder=encoder)
texts, dists = reloaded_index.query("pork")
```

That's it! Happy hacking!
skip-pip 0.1.2
A pip wrapper that installs packages from requirements files while skipping packages that fail.

# Skip-Pip

Skip-Pip is a command-line tool that acts like pip but with enhanced resilience during package installation. When installing from a requirements file, it skips packages that fail to install while continuing with the rest.

## Features

- **Resilient Installation:** Installs each package individually from requirements files.
- **Error Logging:** Prints error details for packages that fail to install.
- **Familiar Interface:** Supports standard pip commands and arguments.

## Installation

You can install Skip-Pip via pip (after publishing on PyPI):

```bash
pip install skip-pip
```

## Usage

Use `skip-pip` in place of `pip`. Here are a few examples:

- **Installing from a Requirements File:**

  ```bash
  skip-pip install -r requirements.txt
  ```

  This command reads the `requirements.txt` file, installs each package one by one, and prints a summary of any packages that failed to install.

- **Installing a Specific Package:**

  ```bash
  skip-pip install requests
  ```

  This installs the `requests` package.

- **Passing Additional Pip Arguments:**

  You can also pass extra pip arguments, such as upgrading packages:

  ```bash
  skip-pip install -r requirements.txt -- --upgrade
  ```

  The `--` separator indicates that the following options should be forwarded to pip.

```