semvec/pypi-packages huggingface dataset:
dbt-snowflake 1.11.2
The Snowflake adapter plugin for dbt
Requires Python: >=3.10.0
Keywords: adapter, adapters, database, dbt, dbt Cloud, dbt Core, dbt Labs, dbt-core, elt, snowflake

<p align="center">
    <img
        src="https://raw.githubusercontent.com/dbt-labs/dbt/ec7dee39f793aa4f7dd3dae37282cc87664813e4/etc/dbt-logo-full.svg"
        alt="dbt logo"
        width="500"
    />
</p>

<p align="center">
    <a href="https://pypi.org/project/dbt-snowflake/">
        <img src="https://badge.fury.io/py/dbt-snowflake.svg" />
    </a>
    <a target="_blank" href="https://pypi.org/project/dbt-snowflake/" style="background:none">
        <img src="https://img.shields.io/pypi/pyversions/dbt-snowflake">
    </a>
    <a href="https://github.com/psf/black">
        <img src="https://img.shields.io/badge/code%20style-black-000000.svg" />
    </a>
    <a href="https://github.com/python/mypy">
        <img src="https://www.mypy-lang.org/static/mypy_badge.svg" />
    </a>
    <a href="https://pepy.tech/project/dbt-snowflake">
        <img src="https://static.pepy.tech/badge/dbt-snowflake/month" />
    </a>
</p>

# dbt

**[dbt](https://www.getdbt.com/)** enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

dbt is the T in ELT. Organize, cleanse, denormalize, filter, rename, and pre-aggregate the raw data in your warehouse so that it's ready for analysis.

## dbt-snowflake

`dbt-snowflake` enables dbt to work with Snowflake.
For more information on using dbt with Snowflake, consult [the docs](https://docs.getdbt.com/docs/profile-snowflake).

# Getting started

Review the repository [README.md](../README.md) as most of that information pertains to `dbt-snowflake`.

## Contribute

- Want to help us build `dbt-snowflake`? Check out the [Contributing Guide](CONTRIBUTING.md).
dbt-redshift 1.10.1
The Redshift adapter plugin for dbt
Requires Python: >=3.10.0
Keywords: adapter, adapters, amazon, amazon web services, aws, database, dbt, dbt Cloud, dbt Core, dbt Labs, dbt-core, elt, redshift

<p align="center">
    <img
        src="https://raw.githubusercontent.com/dbt-labs/dbt/ec7dee39f793aa4f7dd3dae37282cc87664813e4/etc/dbt-logo-full.svg"
        alt="dbt logo"
        width="500"
    />
</p>

<p align="center">
    <a href="https://pypi.org/project/dbt-redshift/">
        <img src="https://badge.fury.io/py/dbt-redshift.svg" />
    </a>
    <a target="_blank" href="https://pypi.org/project/dbt-redshift/" style="background:none">
        <img src="https://img.shields.io/pypi/pyversions/dbt-redshift">
    </a>
    <a href="https://github.com/psf/black">
        <img src="https://img.shields.io/badge/code%20style-black-000000.svg" />
    </a>
    <a href="https://github.com/python/mypy">
        <img src="https://www.mypy-lang.org/static/mypy_badge.svg" />
    </a>
    <a href="https://pepy.tech/project/dbt-redshift">
        <img src="https://static.pepy.tech/badge/dbt-redshift/month" />
    </a>
</p>

# dbt

**[dbt](https://www.getdbt.com/)** enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

dbt is the T in ELT. Organize, cleanse, denormalize, filter, rename, and pre-aggregate the raw data in your warehouse so that it's ready for analysis.

## dbt-redshift

`dbt-redshift` enables dbt to work with Amazon Redshift.
For more information on using dbt with Redshift, consult [the docs](https://docs.getdbt.com/docs/profile-redshift).

# Getting started

Review the repository [README.md](../README.md) as most of that information pertains to `dbt-redshift`.

## Contribute

- Want to help us build `dbt-redshift`? Check out the [Contributing Guide](CONTRIBUTING.md).
py-123pan-client 0.1.13
Unnoficial Python SDK for 123Pan Open Platform
Requires Python: >=3.9

# py-123pan-client

**123云盘开放平台 (123Pan Open Platform) 非官方 Python SDK**

基于 `httpx` 和 `pydantic` 构建，提供现代化、类型安全且易于使用的接口封装。支持自动鉴权、智能断点续传、大文件上传、直链管理、离线下载等核心功能。

## ✨ 特性

- **🔐 自动鉴权**：自动管理 Access Token 生命周期，过期自动刷新，开发者无需操心。
- **🚀 智能上传**：
    - 小文件 (<100MB) 自动使用单步上传。
    - 大文件自动切换为分片上传 (Chunked Upload)，支持秒传检测。
    - 自动计算 MD5，内存占用低（流式处理）。
- **⚡ 高性能**：底层使用 `httpx`，支持 HTTP/2 (依赖服务端支持)，为未来异步化预留空间。
- **📦 类型安全**：所有请求与响应均通过 `Pydantic` 模型验证，提供完美的 IDE 代码补全体验。
- **🛠 全功能覆盖**：文件管理、分享管理（含付费分享）、离线下载、直链加速、开发者安全配置。

## 📦 安装

推荐使用 `uv` 或 `pip` 进行安装：

```bash
# 使用 pip
pip install py-123pan-client

# 或者使用 uv (推荐)
uv add py-123pan-client