semvec/pypi-packages huggingface dataset:
duckdb-ext 0.1.2
pip installable DuckDB extensions
Requires Python: >=3.9
Keywords: duckdb, extensions

# duckdb-ext

![PyPI Version](https://img.shields.io/pypi/v/duckdb-ext)

This package provides pip installable DuckDB extensions.

## Installation

Change the extras to match which extensions you wish to install e.g.:

```
pip install duckdb-ext[aws,httpfs,delta]
```

## Usage

### Option 1: Automatic

```python
import duckdb
import duckdb_ext

with duckdb_ext.init(duckdb.connect()) as con:
    ...
```

### Option 2: Manual

```python
import duckdb
import duckdb_ext

with duckdb.connect() as con:
    con.execute("SET extension_directory = ?;", (duckdb_ext.get_extension_dir(),))
    # Ideally also:
    con.execute("SET autoinstall_known_extensions = false;")
```
dev-toolbox 0.2.0
A collection of useful tools for Python developers.
Requires Python: >=3.9

# dev-toolbox

[![PyPI - Version](https://img.shields.io/pypi/v/dev-toolbox.svg)](https://pypi.org/project/dev-toolbox)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/dev-toolbox.svg)](https://pypi.org/project/dev-toolbox)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/FlavioAmurrioCS/dev-toolbox/main.svg)](https://results.pre-commit.ci/latest/github/FlavioAmurrioCS/dev-toolbox/main)

-----

**Table of Contents**

- [dev-toolbox](#dev-toolbox)
  - [Installation](#installation)
  - [License](#license)

## Installation

```console
pip install dev-toolbox
```

## License

`dev-toolbox` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
init-gitee 0.1.8
Gitee repository initialization tool
Requires Python: >=3.8

# Gitee 仓库管理工具

一个命令行工具，用于管理 Gitee 代码仓库，支持创建、列出和删除仓库等操作。

## 功能特性

- 创建个人或组织仓库
- 列出用户所有仓库
- 删除指定仓库
- 支持多种仓库配置选项

## 安装

### 通过 pip 安装

```bash
pip install init-gitee
```

## 使用说明

### 基本命令

```bash
init-gitee [OPTIONS] COMMAND [ARGS]...
```

## 命令列表

### 创建仓库

```bash
init-gitee create-repo <仓库名称> [OPTIONS]
```

选项：

-g, --org TEXT 组织名称
-p, --path TEXT 仓库路径
-d, --description TEXT 仓库描述
-h, --homepage TEXT 项目主页
-r, --private 设为私有仓库 (默认: True)
-a, --auto-init 创建初始提交

### 列出仓库

```bash
init-gitee list-repos [OPTIONS]
```

选项：

-p, --page INTEGER 页码 (默认: 1)
-r, --repos-per-page INTEGER 每页数量 (默认: 20)

### 删除仓库

```bash
init-gitee delete-repos <仓库名称> [OPTIONS]
```

选项：

-o, --owner TEXT 仓库所有者 (必须)

### 配置

工具会默认读取 ~/.init-gitee/config.ini 配置文件，格式如下：


```ini
Apply
[auth]
access_token = 您的Gitee访问令牌
```

## 示例

创建个人仓库：

```bash
init-gitee create-repo my-project --description "我的项目"
```

创建组织仓库：

```bash
init-gitee create-repo org-project --org my-org
```

列出仓库：

```bash
init-gitee list-repos --page 2
```

删除仓库：

```bash
init-gitee delete-repos my-project --owner my-username
```

许可证

MIT License
fileslicer 0.1.0
Efficient file slicing and memory-mapped line iteration.
Requires Python: >=3.9

# fileslicer

[![PyPI - Version](https://img.shields.io/pypi/v/fileslicer.svg)](https://pypi.org/project/fileslicer)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/fileslicer.svg)](https://pypi.org/project/fileslicer)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/FlavioAmurrioCS/fileslicer/main.svg)](https://results.pre-commit.ci/latest/github/FlavioAmurrioCS/fileslicer/main)

-----

**fileslicer** is a lightweight Python library for efficiently reading and splitting large files using memory mapping. It allows you to iterate over lines within a file slice and split files into chunks without loading the entire file into memory, making it ideal for processing very large files.

---

## Features

- Memory-efficient line iteration using `mmap`.
- Split large files into chunks while respecting newline boundaries.
- Simple and Pythonic API.
- Works with files of arbitrary size.

---

## Installation

Install via pip:

```bash
pip install fileslicer
````

---

## Usage

### Basic Example: Iterate over a file

```python
from fileslicer import FileSlice

# Create a FileSlice for an entire file
slice = FileSlice.from_file("large_file.txt")

# Iterate over lines in the slice
for line in slice.iter_lines():
    print(line.decode().strip())
```

### Split a File into Chunks

```python
from fileslicer import FileSlice

# Split a file into 4 chunks
chunks = FileSlice.split_file("large_file.txt", splits=4)

for chunk in chunks:
    print(f"Processing bytes {chunk.start_offset}-{chunk.end_offset}")
    for line in chunk.iter_lines():
        print(line.decode().strip())
```

### Create a Custom File Slice

```python
from fileslicer import FileSlice

# Only read bytes 1000 to 5000
slice = FileSlice("large_file.txt", 1000, 5000)

for line in slice.iter_lines():
    print(line.decode().strip())
```

---

## API

### `FileSlice`

* `FileSlice(file_path: str, start_offset: int, end_offset: int)`: Represents a slice of a file.

* `iter_lines() -> Generator[bytes]`: Iterate over lines in the file slice as bytes.

* `@staticmethod from_file(file_path: str) -> FileSlice`: Create a `FileSlice` covering the entire file.

* `@staticmethod split_file(file_path: str, splits: int) -> list[FileSlice]`: Split a file into multiple slices, aligned to newline boundaries.

---

## Why Use fileslicer?

Processing extremely large files with standard file reading can be slow and memory-intensive. **fileslicer** uses memory mapping to efficiently slice and iterate over file data without reading everything into memory. Inspired by the "1 Billion Row Challenge" in Python, it is perfect for data processing pipelines, log analysis, and ETL tasks.

---

## License

`fileslicer` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.