semvec/pypi-packages huggingface dataset:
sentry-dingtalk-henryhaoson2 9.0.3
A sentry extension integrates DingTalk robot webhook forked from Jedore/sentry-dingtalk
License: MIT
Requires Python: >=3.6.13
Keywords: sentry dingtalk


# Sentry DingTalk

Sentry 集成钉钉机器人通知

## Requirments
- sentry >= 21.5.1

## 特性
- 发送异常通知到钉钉
- 配置 @ 成员，逗号分隔
- webhook optional 可以配置一个额外的 webhook，但是会抹除 `@信息`
## 快速使用
### 安装
1. 写入依赖文件 `onpremise-xxx/sentry/requirements.txt`
    ```bash
    $ echo sentry-dingtalk-henryhaoson2 >> requirements.txt
    ```

### 钉钉机器人
[配置](https://developers.dingtalk.com/document/app/custom-robot-access)钉钉机器人并拿到对应的 webhook, 可以对机器人设置 关键词、签名、IP限制

### 配置
在 Sentry 面板 Settings > Integrations 中找到 DingTalk 并配置 webhook等信息，添加项目，创建告警规则

### 测试
1. Enable Plugin
2. Test Plugin
cythoneuclideandistance 0.11
Calculate Euclidean distances between two sets of coordinates (Cython and Numexpr)
License: MIT
Keywords: Calculate Euclidean


# Calculate Euclidean distances between two sets of coordinates (Cython and Numexpr)

## Tested against Windows / Python 3.11 / Anaconda

## pip install cythoneuclideandistance

```python
Calculate Euclidean distances between two sets of coordinates.

This function computes the Euclidean distance matrix between two sets of coordinates.

Args:
    coords1 (numpy.ndarray): An array of shape (n, 2) containing the first set of coordinates.
    coords2 (numpy.ndarray): An array of shape (m, 2) containing the second set of coordinates.

Returns:
    numpy.ndarray: A 2D array of shape (n, m) containing the Euclidean distances between all pairs of coordinates.

Example:
    import random
    import cythoneuclideandistance
    import numpy as np

    coords1 = np.array(
        [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(23000)],
        dtype=np.int32,
    )
    coords2 = np.array(
        [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(22150)],
        dtype=np.int32,
    )

    distance_matrix = cythoneuclideandistance.calculate_euc_distance(coords1, coords2)
    print(distance_matrix)

```