semvec/pypi-packages huggingface dataset:
pip-fc 0.1.12
一款轻量级的 Python 工具，用于高效测试多个镜像源的连接速度，帮助用户选择最优的镜像源以提高包管理效率。
Requires Python: <4,>=2.7
Keywords: mlc-mirror mirror speed pip

# pip-fc

> pip-fc 全称是：pip fast check

`pip-fc` 是一个轻量级的 Python 工具，旨在测试多个镜像源的连接速度，并帮助用户选择最快的镜像源进行软件包安装。支持 Python 2.7 和 3.x 版本，能够自动根据环境选择适合的并发模式（`asyncio` 或 `threading`）。

---

## 功能

- 测试多个镜像源的连接速度。
  - v0.1.12: 丢弃了部分过时的mirror，使用**文件实际下载速度**进行测速
- 自动选择连接速度最快的镜像源。
- 支持 Python 2.7 和 3.x 版本。
- 使用异步（`asyncio`）或线程池（`threading`）来提高测试效率。
- 简单易用的命令行界面。

## 安装

### 使用 `pip` 安装：

```bash
pip install pip-fc
```

## 使用方法

通过运行以下命令启动：

`pip-fc` 或者 `python -m pip_fc`

此命令将会测试预设的镜像源，并显示连接速度最快的镜像源。你也可以自定义镜像源进行测试。

### 设置全局镜像源

如果你希望将测试中找到的最快镜像源设置为全局 `pip` 镜像源，可以在运行完成后输入 `y` 来确认：

```bash
Do you want to set the fastest mirror as the global pip mirror? (y/n): y
```

此操作将更新 `pip` 的配置文件，设置全局镜像源和回退镜像源。

## 依赖

* `pip`：用于安装和管理 Python 包。
* `futures`：仅在 Python 2.7 环境下需要，安装时自动处理。

## 示例输出 v2

```
Detected Python Version: 3.12.12 (asyncio)
========================================
--- Starting HTTP download (v2) for speedtest (4096 bytes, 3 times average) ---

Mirror HTTP Download Test Results (sorted by speed):
----------------------------------------
Speed (KB/s)    URL                                                         
----------------------------------------
27.53           https://mirrors.cloud.tencent.com/pypi/simple/
26.83           https://mirrors.ustc.edu.cn/pypi/simple/
16.45           https://pypi.tuna.tsinghua.edu.cn/simple/
16.39           https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/
2.33            https://repo.huaweicloud.com/repository/pypi/simple/
0.51            https://mirrors.aliyun.com/pypi/simple/
----------------------------------------

*** Fastest mirror is: https://mirrors.cloud.tencent.com/pypi/simple/ (speed: 27.53 KB/s)

= = = = = = = = = = = = = = = = = = = = 

Do you want to set the fastest mirror as the global pip mirror? (y/n): 

Timeout reached! No input received.
Skipping mirror setup.
```

## 示例输出 v1

```
Detected Python Version: 3.8.5 (asyncio)
--- Starting connection speed test using asyncio mode ---
Successfully tested 6 mirrors.
Fastest Mirror: https://pypi.tuna.tsinghua.edu.cn/simple/
Latency: 50.12345 ms

--- All Successful Connection Results (URL, Latency in ms) ---
  https://pypi.tuna.tsinghua.edu.cn/simple/: 50.12345 ms
  https://mirrors.aliyun.com/pypi/simple/: 65.67890 ms
  ...
```

## 贡献

欢迎提出问题、提交 bug 或者贡献代码。如果你有任何问题，或者希望添加新特性，请提交 [issue](https://github.com/harmonsir/pip-fc/issues)。

## 许可

该项目采用 MIT 许可证，详情请见 [LICENSE](LICENSE) 文件。
dvc-yadisk 0.1.8
Yandex Disk remote storage plugin for DVC
Requires Python: >=3.9
Keywords: data-version-control, dvc, mlops, storage, yadisk, yandex, yandex-disk

# dvc-yadisk

Yandex Disk remote storage plugin for [DVC](https://dvc.org) (Data Version Control).

## Installation

```bash
# Using uv
uv add dvc-yadisk

# Using pip
pip install dvc-yadisk
```

After installation, enable the plugin:

```bash
# Run the enable script to register the plugin with DVC
dvc-yadisk-enable
```

This creates a `sitecustomize.py` file in your Python environment that loads the plugin automatically when DVC starts.

## Configuration

### 1. Get Yandex Disk OAuth Token

1. Go to [Yandex Poginon](https://yandex.ru/dev/disk/poligon)
2. Create a token
3. Copy the token

### 2. Configure DVC Remote

```bash
# Add a Yandex Disk remote
dvc remote add -d myremote yadisk://my-dvc-data

# Set the OAuth token (use --local to avoid committing token to git)
dvc remote modify --local myremote token YOUR_OAUTH_TOKEN
```

Or use environment variable:

```bash
export YADISK_TOKEN=YOUR_OAUTH_TOKEN
```

### 3. Use DVC as Normal

```bash
# Track data
dvc add data/

# Push to Yandex Disk
dvc push

# Pull from Yandex Disk
dvc pull
```

## Configuration Options

| Option | Environment Variable | Description |
|--------|---------------------|-------------|
| `token` | `YADISK_TOKEN` | OAuth access token (required) |

## Example Usage

```python
from dvc_yadisk import YaDiskFileSystem

# Create filesystem instance
fs = YaDiskFileSystem(token="your_oauth_token")

# List files
files = fs.ls("my-folder")

# Check if file exists
exists = fs.exists("my-folder/data.csv")

# Read file
data = fs.cat_file("my-folder/data.csv")

# Write file
fs.pipe_file("my-folder/output.txt", b"Hello, World!")
```

### Async Usage

```python
import asyncio
from dvc_yadisk import get_async_filesystem

async def main():
    AsyncFS = get_async_filesystem()
    fs = AsyncFS(token="your_oauth_token")

    # List files
    files = await fs.ls("my-folder")

    # Read file
    data = await fs.cat_file("my-folder/data.csv")

asyncio.run(main())
```

## Limitations

- Maximum file size: 1GB (50GB for Yandex 360 subscribers)
- Upload URLs are valid for 30 minutes
- API rate limits apply

## Development

```bash
# Clone repository
git clone https://github.com/Suro4ek/dvc-yadisk.git
cd dvc-yadisk

# Install with dev dependencies
uv sync --dev

# Run tests
uv run pytest

# Run tests with coverage
uv run pytest --cov=dvc_yadisk

# Type checking
uv run mypy src/dvc_yadisk

# Linting
uv run ruff check src/dvc_yadisk
```


## License

Apache License 2.0
nodepasta 2.0.6
A Node Based Visual Scripting System
Requires Python: >=3.7

## NodePasta
Want to implement a visual scripting system into your program but don't want to write it yourself? NodePasta has got you covered.

NodePasta is a node based-visual scripting framework that lets you define your own nodes and it will take care of the rest.
A NodePasta NodeGraph is UI agnostic, meaning you can load and run graphs without needing a UI implented, but the real magic comes from letting your users
develop their own graphs. NodePasta comes pre-packaged with a editor UI written for imgui and TKInter, that you can embed into your application.