semvec/pypi-packages huggingface dataset:
send-the-raven 0.1.2
A collection of toolkit and algorithms for handling US addresses
Requires Python: >=3.10,<4.0

.. |.`~send_the_raven.address.Address`| replace:: ``Address``
.. _.`~send_the_raven.address.Address`: https://send-the-raven.jimmtganteng.com/_autosummary/send_the_raven.address.Address.html#send_the_raven.address.Address

Send The Raven
===============

Send the Raven is a Python library that provides a comprehensive collection of toolkits and algorithms for handling US addresses. It aims to simplify the process of working with US addresses, offering functionalities such as parsing, validation, formatting, and more.

.. image:: https://raw.githubusercontent.com/Fazatholomew/send-the-raven/ed0e3a63bc8d4602fe06d33f3af75b8a38ec568b/source/_static/d782276f-b708-4c7d-a077-5354d19f06fe.gif
   :alt: Game of Thrones Send the Ravens GIF
   :align: center

Checkout the official `documentation <https://send-the-raven.jimmyganteng.com>`_.

Features
---------

- **Address Parsing**: Extract structured information from US addresses, including street names, house numbers, city, state, and ZIP codes.
- **Address Validation**: Validate US addresses to ensure accuracy and compliance with USPS standards.  
- **Address Formatting**: Format US addresses in a consistent and standardized manner for various purposes.
- **Address Geocoding**: Convert US addresses into Longitude and Latitude.
- **Additional Utilities**: Additional utilities to enhance address handling, such as address comparison, address normalization, and more.

Installation
-------------

send_the_raven can be installed from PyPI:

.. code-block:: bash

   pip install send-the-raven

Usage
------

Here is a quick example of using send_the_raven to validate addresses into USPS Database:

.. code-block:: python

   from send_the_raven import Validator
   
   addresses = [
      {"street": "123 Main St", "city": "Anytown", "state": "CA", "zip_code": "12345"},
      {"street": "456 Oak Rd", "city": "Forest", "state": "VT", "zip_code": "67890"}
   ]
   
   validator = Validator(addresses, usps_id="MY_ID")
   valid_addresses = validator()
   
send_the_raven handles parsing the address data, constructing the validation requests, and returning the corrected addresses.

The :py|.`~send_the_raven.address.Address`|_ class also provides methods for normalizing, geocoding, and working with addresses.


Acknowledgments
----------------

send_the_raven uses the following open source libraries:

- `usaddress-scourgify <https://github.com/GreenBuildingRegistry/usaddress-scourgify>`_ for parsing addresses.
- `xmltodict <https://github.com/martinblech/xmltodict>`_ for working with XML. 
- `aiohttp <https://github.com/aio-libs/aiohttp>`_ for asynchronous HTTP requests.
- `geopy <https://github.com/geopy/geopy>`_ for geocoding.
- `h3-py <https://github.com/uber/h3-py>`_ for geospatial indexing.

We thank the developers of these libraries for their contributions.

* `Examples <https://send-the-raven.jimmtganteng.com/example.html>`_
* `API Reference <https://send-the-raven.jimmtganteng.com/api.html>`_
* `Contributing <https://send-the-raven.jimmtganteng.com/contribute.html>`_
Mongodb-tool 0.0.1
Mongodb数据操作工具
Requires Python: >=3.8.5,<4.0.0

# mongodb-tool

mongodb操作工具

## 环境准备

### 安装happy-python & pymongo
```bash
pip install happy-python

python -m pip install "pymongo[srv]" --trusted-host pypi.tuna.tsinghua.edu.cn
```

## 单元测试

```bash
cd tests && pytest
```

## 使用举例

### 增加数据

```bash
python main.py -i '{"name": "John", "age": 30, "city": "New York"}'
```

### 增加数据
```bash
python main.py -i '{"name": "John", "age": 30, "city": "New York"}'
```

### 删除数据
```bash
python main.py -d '{"name": "John", "age": 30, "city": "New York"}'
```

### 查找数据

#### 查找指定键值对数据
```bash
python main.py -s '{"name": "John"}'
```

#### 查找集合中所有数据
```bash
python main.py -s 
```

### 修改数据
```bash
python main.py -u '{"name": "John", "age": 34, "city": "Shanghai"}'
```
### 导入导出数据

#### 导出数据至指定文件
```bash
python main.py --dump filename
```

#### 从指定文件导入数据
```bash
python main.py --import filename
```

## 使用详细
请使用python main.py --help/-h
```
$ python main.py -h
2023-09-26 14:40:07 10537 [INFO] 未启用日志配置文件，加载默认设置
2023-09-26 14:40:07 10537 [INFO] 日志配置文件 '/home/colamps/workspace/github/mongodb-tool/method/../conf/log.ini' 加载成功
usage: mongodb_tool [-i <data>] [-d <data>] [-s <data>] [-u <data>] [--dump <filename>] [--import <filename>]

MongoDB工具

options:
  -h, --help            show this help message and exit
  -i INSERT_DATA        执行插入操作，提供数据（JSON格式）
  -d DELETE_DATA        执行删除操作，提供查询条件（JSON格式）
  -s [SEARCH_DATA]      执行查询操作，提供查询条件（JSON格式）
  -u UPDATE_DATA        执行更新操作，提供查询条件和更新数据（JSON格式）
  --dump DUMP_FILE      导出数据到指定文件（JSON格式）
  --import IMPORT_FILE  从指定文件导入数据（JSON格式）
```
mongo-cmd 0.0.0.2
一个mongodb命令行操作版本界面
Requires Python: >=3.8.5,<4.0.0

# geekcamp-calculator
一款mongodb 命令行操作工具

## 环境准备

```bash
pip install --upgrade build twine

```
改写pyproject.toml文件


## 本地安装

```bash
poetry -m build 
```

列出 Python 包文件列表：

```bash
pip show mongo-cmd  -f
```

### 运行

```bash
~/.mongo

### 操作界面

1. Exit
2. Insert Data
3. View Data
4. Update Data
5. Delete Data
Enter Choice: 3 

1. View All
2. View as per mentioned key:value
Enter Choice: 1
123 123 123 123 123 {'model': '123', 'year': '123', 'value': '123'}
zhang san 123 456 6 {'model': '789', 'year': '2011', 'value': 'sss'}