semvec/pypi-packages huggingface dataset:
nb-mypy 1.0.6
Nb Mypy is a facility to automatically run mypy on Jupyter notebook cells as they are executed, whilst retaining information about the execution history.
Requires Python: >=3.11
Keywords: Type Checking, Notebooks, IPython, MyPy

# Nb Mypy

_Nb Mypy_ is a facility to automatically run [`mypy`](http://mypy-lang.org/) on Jupyter notebook cells as they are executed, whilst retaining information about the execution history.


## Installation

* _Nb Mypy_ relies on the packages mypy and astor, but those should be automatically installed.
* _Nb Mypy_ can be installed like:
```bash
python3 -m pip install nb_mypy
```

Once installed, you can load it via `%load_ext nb_mypy` in a cell of  a Jupyter notebook using the IPython kernel.

### Installation from source
The package can also be installed from source, using pip:
```bash
python3 -m pip install .
```

## Usage

In Jupyter notebooks where you want to apply
automatic type checking,
you can load this extension to do type checking by executing
(in a code cell) the line magic `%load_ext nb_mypy`.

With the line magic `%nb_mypy` you can modify the behaviour of _Nb Mypy_

Here are the ways to use the line magic `%nb_mypy`
* `%nb_mypy -v`: show version
* `%nb_mypy`: show the current state
* `%nb_mypy On`: enable automatic type checking
* `%nb_mypy Off`: disable automatic type checking
* `%nb_mypy DebugOn`: enable debug mode
* `%nb_mypy DebugOff`: disable debug mode
* `%nb_mypy mypy-options` [OPTIONS]: Provide extra options to mypy (for example --strict)

### Load automatically
This package is an iPython extension, thus it can be loaded automatically by adding the following line to your iPython configuration file.
```python
c.InteractiveShellApp.extensions = ['nb_mypy']
```
The configuration file can (probably) be found at `~/.ipython/profile_default/ipython_config.py` or created by executing `ipython profile create`.
To add options, for instance, always have strict type checking on, you can add the following.
```python
c.InteractiveShellApp.exec_lines = ['%nb_mypy mypy-options --strict']
```


## Examples

For examples, see the Jupyter notebook [`Nb_Mypy.ipynb`](https://gitlab.tue.nl/jupyter-projects/nb_mypy/-/blob/master/Nb_Mypy.ipynb).
pyupgradex 0.0.1
This is a tool that provides advanced features of pyupgrade.
Requires Python: <4.0,>=3.8

## 使用说明

pyupgradex 提供了一个命令行工具，支持以下子命令：

### plugins
列出所有注册的插件模块名称。

```bash
python -m pyupgradex plugins
```

### run
运行 pyupgrade，并支持禁用指定插件。

```bash
python -m pyupgradex run --disable-plugins plugin_name1 plugin_name2 -- other_args
```

`--disable-plugins` 参数用于禁用指定的插件，`other_args` 是传递给 pyupgrade 的额外参数。
Linkedin-saved-posts-search 0.3.0
A CLI tool to scrape and search your LinkedIn saved posts.
Requires Python: >=3.7

# LinkedIn Saved Posts Search
        
        A simple Python CLI tool to **scrape** and **search** your LinkedIn saved posts.
        
        ## 🚀 Features
        
        - Login manually via browser
        - Continue scraping in headless mode
        - Extracts full post text, author, and timestamps
        - Fuzzy keyword search with AND/OR logic
        - Optional date filtering
        - Export matched results to JSON
        
        ## 📦 Installation
        
        ```bash
        pip install Linkedin-saved-posts-search
sparql-grammar-pydantic 0.1.11
Pydantic models for the SPARQL Grammar.
Requires Python: <4.0,>=3.11

# SPARQL Grammar Pydantic

This library defines Pydantic models for most SPARQL Grammar classes.

This facilitates programmatic generation of SPARQL queries.

Source code is available at https://github.com/Kurrawong/sparql-grammar-pydantic

## TODO 
- remove dependency on rdflib
spring-initializer 1.0.3
下载并解压 Spring 框架代码
Requires Python: >=3.6

# spring-initializer

# 能做什么

从 Spring 官网下载并解压以生成 spring boot 框架代码。

# 存在的意义

一般通过 Idea 从 https://start.spring.io/ 下载框架代码，但很诡异的是，经常会出现浏览器可以访问，但 Idea 无法下载的问题，尝试通过 curl 等 Linux 命令行 web 客户端下载，依然有概率出现连接超时的问题。

网上给出的解决方案是将 Spring 官网源替换为阿里源，我本来也打算这么干，但发现阿里源使用的是过时版本，版本支持上与官网不一致，因此就有了这个工具。

本工具的旨在通过其它方式无法快速下载 Spring 框架代码时，可以通过这个工具从官网下载，工具内设置了超时重试机制，默认是尝试10次，每次 2s 超时后重新尝试。

下载完后会自动解压，解压完成后会删除原始压缩包。

使用这个工具的另一个好处是可以扩展框架代码部署行为，比如最近几个版本的 Spring 中默认的 Lombok 存在 bug，需要将其指定为最新版，每次创建项目都要来这么一下，否则运行就会报错，完全可以在这个工具中自定义 pom 修改逻辑，让修改 pom 自动化完成。当然，目前没有这个功能，等以后更新或者你自行 fork。

# 安装

本工具用 Python 编写，通过 pip 安装：

```
pip install spring-initializer
```

更新使用以下命令：

```
pip install --upgrade spring-initializer
```

# 使用

通过 Python 模块方式运行：

```
python -m spring_initializer
```

更推荐以短命令方式运行：

```
pysi
```

不使用任何参数执行命令，会在工作目录下生成一个`spring_demo`目录，框架代码部署在其中。默认生成的是 Maven 项目，包含（spring-web 和 lombok）这两个常用依赖，使用的 Java 语言级别是 21。

可以通过命令行参数修改默认行为，比如指定目录名或生成 Gradle 项目等，参数说明可以通过以下命令查看：

```
pysi -h
```

# 运行环境

原则上本工具支持多平台，但并未在 Linux/Mac OS 中经过充分验证。

# 问题反馈

可以给我发邮件：icexmoon@qq.com

或者通过 github：[Issues · icexmoon/spring-initializer](https://github.com/icexmoon/spring-initializer/issues)

# 更新记录

## 1.0.2

修复使用短命令时程序会执行两次的 bug

## 1.0.1

增加 Readme 说明

## 1.0.0

创建。
fakedpy 1.5
A Python library for generating fake data with various output formats.
Requires Python: >=3.10

# FakedPy

A Python library for generating fake data with various output formats.

## Installation

```bash
pip install fakedpy
```

## Features

- Generate various types of fake data
- Support multiple output formats (CSV, JSON, Excel, Parquet), but CSV as a default
- Support localization (including Indonesian)
- Generate related/dependent data
- Easy to use and flexible

## Basic Usage

```python
from fakedpy import FakedGenerator

# Initialize generator
generator = FakedGenerator(locale='id_ID')  # For Indonesian data
# orr
generator = FakedGenerator(locale=['id_ID', 'en_US'])  # For mixed data

# Generate simple data
df = generator.generate(
    rows=5,
    fields=["name", "email", "address"]
)

# Save to different formats
df = generator.generate(
    rows=5,
    fields=["name", "email", "job"],
    output_format="json",
    output_path="data/output"
)
```

## Available Fields

### Personal Information
- name: Full name
- first_name: First name
- last_name: Last name
- email: Email address
- phone_number: Phone number
- date: Date
- gender: Gender

### Address Information
- address: Full address
- street_address: Street address
- city: City
- state: State/Province
- country: Country
- postcode: Postal code
- latitude: Latitude
- longitude: Longitude

### Internet Information
- username: Username
- password: Password
- domain_name: Domain name
- url: URL address
- ipv4: IPv4 address
- ipv6: IPv6 address
- mac_address: MAC address

### Company Information
- company: Company name
- job: Job title

### Financial Information
- credit_card_number: Credit card number
- credit_card_provider: Credit card provider
- currency_code: Currency code

### Technology
- file_name: File name
- file_extension: File extension
- mime_type: MIME type

### Miscellaneous
- text: Text paragraph
- word: Single word
- sentence: Single sentence
- paragraph: Full paragraph
- color_name: Color name
- hex_color: HEX color code
- rgb_color: RGB color code

## Advanced Usage

### Related Data
```python
# Generate data with ID and department
df = generator.generate(
    rows=5,
    fields=["user_id", "name", "department"],
    related_fields={
        "user_id": {"type": "counter", "start": 1000},
        "department": {
            "type": "choice",
            "values": ["IT", "HR", "Finance", "Marketing"]
        }
    }
)
```

### Different Output Formats
```python
# CSV
df = generator.generate(
    rows=10,
    fields=["name", "email"],
    output_format="csv",
    output_path="data/users"
)

# JSON
df = generator.generate(
    rows=10,
    fields=["name", "email"],
    output_format="json",
    output_path="data/users"
)

# Excel
df = generator.generate(
    rows=10,
    fields=["name", "email"],
    output_format="excel",
    output_path="data/users"
)

# Parquet
df = generator.generate(
    rows=10,
    fields=["name", "email"],
    output_format="parquet",
    output_path="data/users"
)
```

## Contributing

Feel free to contribute by creating issues or pull requests in this repository.

## License

[MIT License](LICENSE)