semvec/pypi-packages huggingface dataset:
sbcli-ndm 1.0.9
CLI for managing SimplyBlock cluster


# Simply Block
[![Docker Image Build](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml)

[![Python Unit Testing](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml)


## Install
Add the package repo from AWS CodeArtifact using [awscli](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)

```bash
aws codeartifact login --tool pip --repository sbcli --domain simplyblock --domain-owner 565979732541 --region eu-west-1
```
Install package
```bash
pip install --extra-index-url https://pypi.org/simple sbcli-dev
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
Please see this document
[README.md](../main/simplyblock_cli/README.md)


## Simply Block Web API
Please see this document
[README.md](../main/simplyblock_web/README.md)



### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```

setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.


```
sudo docker compose -f docker-compose-dev.yml up --build -d
```
sbcli-fdm 1.0.6
CLI for managing SimplyBlock cluster


# Simply Block
[![Docker Image Build](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml)

[![Python Unit Testing](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml)


## Install
Add the package repo from AWS CodeArtifact using [awscli](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)

```bash
aws codeartifact login --tool pip --repository sbcli --domain simplyblock --domain-owner 565979732541 --region eu-west-1
```
Install package
```bash
pip install --extra-index-url https://pypi.org/simple sbcli-dev
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
Please see this document
[README.md](../main/simplyblock_cli/README.md)


## Simply Block Web API
Please see this document
[README.md](../main/simplyblock_web/README.md)



### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```

setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.


```
sudo docker compose -f docker-compose-dev.yml up --build -d
```
credold 0.1.2
A package for managing credentials
Requires Python: >=3.11

## localstack

locakstackを利用することで、AWSのリソースをローカルで扱うことができる。

### 利用のための準備

`~/.aws/credentials`に、以下のようなアカウントを作成

```
[localstack]
aws_access_key_id = dummy
aws_secret_access_key = dummy
region=ap-northeast-1
```

### 利用例

```shell
aws --endpoint-url=http://localhost:4567 --profile localstack {awsコマンド}
```

たとえばS3バケットを作成した場合は、以下のようなコマンドを実行する。

```shell
# バケット作成
aws --endpoint-url=http://localhost:4567 --profile localstack s3 mb s3://credold-sample

# バケット一覧表示
aws --endpoint-url=http://localhost:4567 --profile localstack s3 ls
```

## PyPi

`pip install twine` が完了しており、`~/.pypirc`がある状態で、以下を実行

```shell
python setup.py sdist bdist_wheel
# テスト
twine upload --repository pypitest dist/*
# 本番
twine upload dist/*
```
Mangrove 0.2.6
A PostgreSQL extension manager
Requires Python: >=3.6

## Mangrove - 基于 Python 制作的 PostgreSQL 拓展管理器

Mangrove 是一款基于 Python 制作的 PostgreSQL 拓展管理器，它可以简化你安装 PostgreSQL 的流程。

## 安装与部署

```shell
# 请确保你已经安装 Python & pip 包管理器
pip install mangrove
# 安装成功后，使用 mangrove 的帮助指令学习更多用法
python -m mangrove --help
```

## 参与 Mangrove 生态建设

[我们所建设的文档网站](http://zouxiangneihe.atomgit.net/website_public/docs/Mangrove%20%E6%8B%93%E5%B1%95%E7%AE%A1%E7%90%86%E5%99%A8/) 详细阐述了向 Mangrove 贡献 PostgreSQL 拓展，借助 Mangrove 安装 PostgreSQL 拓展，以及 Mangrove 程序自身的原理的有关内容，阅读他们可以快速帮助你成为一名 PostgreSQL 的开发者。

倘若你遇到了任何疑问，或是希望分享你的所知所学，欢迎参与到[社区](https://atomgit.com/zouxiangneihe)的讨论之中。

我们真诚祝愿你成为一名一流的 PostgreSQL 内核开发者！

## 特别感谢

[徐浩荣](https://atomgit.com/haorongxu)   
[张凯老师](https://atomgit.com/kyle)   
[开放原子开源基金会](https://www.openatom.org/)   
[中国 PostgreSQL 分会](https://www.postgresqlchina.com/)   
[青年数据库学习会 MOP 社区](https://mp.weixin.qq.com/s/WC2erGNwky9qUFhwGnQ96w)
pySQLExport 0.1.4
A command line tool to interact with MySQL databases and export to other formats.
Requires Python: >=3.6

# pySQLExport

A command line tool to interact with multiple databases and export to various formats.

## Installation

You can install the package using pip:

```sh
pip install pySQLExport
```
## Configuration

Before using `pySQLExport`, ensure you have a configuration file or environment variables set up for your database connection.

## Usage
You can run pySQLExport in either interactive mode, which allows you to run multiple queries and export to multiple formats. You can also pass command line arguments for single-run exports or queries.


### Interactive Mode

If you run `pySQLExport` without arguments, it will start in interactive mode:

```sh
pySQLExport
```

### Command Line Interface

#### Running a Query

To run a query and display the results in the terminal:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml
```

#### Exporting Results

To export query results to a CSV file:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=csv --outfile results.csv
```

To export query results to a JSON file:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=json --outfile results.json
```
To export query results to a XML file:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=json --outfile results.xml
```
To export query results to a html file:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=json --outfile results.html
```

In interactive mode, you can enter the database information, run queries, and choose how to export the results.

### Example

Hereâ€™s a complete example of how to use `pySQLExport`:

```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output csv --outfile results.csv
```

1. **Run the command above.**
2. **The results will be exported to a file named `results.csv`.**

### Summary of Commands

- **Run a query and display results**:
  ```sh
  pySQLExport --query "YOUR_QUERY_HERE" --config-file config.yaml
  ```

- **Export results to CSV**:
  ```sh
  pySQLExport --query "YOUR_QUERY_HERE" --config-file config.yaml --output csv --outfile results.csv
  ```

- **Export results to JSON**:
  ```sh
  pySQLExport --query "YOUR_QUERY_HERE" --config_file config.yaml --output json --outfile results.json
  ```
- **Export results to html**:
```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=json --outfile results.xml
```
- **Export results to xml**:
```sh
pySQLExport --query "SELECT * FROM employees" --config-file config.yaml --output=json --outfile results.html
```

## Contributing

Contributions are welcome! Please read the [contributing guidelines](CONTRIBUTING.md) first.

## License

This project is licensed under the GPLv3 License. See the [LICENSE](LICENSE) file for details.
airport-manager 0.2.29
Airport Manager: One-stop shop for all airport management needs.
Requires Python: >=3.6

# Airport Manager

Airport Manager is a comprehensive terminal-based client designed to meet all your airport management needs. It provides various functionalities such as retrieving API tokens, fetching airport coordinates, finding areas by coordinates, and more.

## Features

- **Get API Token**: Retrieve the API token for a given airport code.
- **Get Airport Coordinates**: Fetch the coordinates for a specified airport.
- **Find Area by Coordinates**: Identify the area within the airport for given coordinates.
- **Find Areas for Coordinates**: Find multiple areas based on a list of coordinates.

## Installation

You can install Airport Manager using pip:

```sh
pip install airport-manager
```
parallize 0.1.5
Parallize is a Python package that provides utilities to parallelize both synchronous and asynchronous functions using the `concurrent.futures.ProcessPoolExecutor`.
Requires Python: <4.0,>=3.10

# Parallize

Parallize is a Python package that provides utilities to parallelize synchronous functions using the `concurrent.futures.ProcessPoolExecutor` and convert it into async functions to prevent the main thread from blocking. This allows you to execute functions in separate processes, leveraging multiple CPU cores for improved performance.

## Features

- **Parallelize Synchronous Functions**: Execute synchronous functions in parallel using multiple processes.
- **Parallelize Asynchronous Functions**: Execute asynchronous functions in parallel using multiple processes.
- **Customizable Worker Count**: Specify the maximum number of worker processes to use, or let the package use the number of available CPU cores by default.

## Mini Benchmark

Here are the updated benchmark results comparing serial and parallel execution times using the `test_aparallize.py` test case:

| Test Case            | Concurrent Execution Time | Parallel Execution Time | Speedup | Tasks Count |
| -------------------- | ------------------------- | ----------------------- | ------- | ----------- |
| `test_aparallize_fn` | 0:00:17.215937            | 0:00:08.293026          | 2.08x   | 2           |
| `test_aparallize_10` | 0:01:25.070893            | 0:00:13.997451          | 5.94x   | 10          |

### Benchmark Details

- **Concurrent Execution Time**: The time taken to execute the CPU-bound task concurrently using a `ThreadPoolExecutor`.
- **Parallel Execution Time**: The time taken to execute the same task in parallel using the `aparallize` decorator.
- **Speedup**: The ratio of serial execution time to parallel execution time, indicating the performance improvement achieved by parallelizing the task.

## Installation

To install Parallize, you can use pip:

```bash
pip install parallize
```

## Usage

```python
from parallize import aparallize

def my_function(x, y):
    return x + y

# Call the function as usual
result = await aparallize(my_function)(1, 2)
print(result)  # This will be executed in a separate process
```

### Customizing the Number of Workers

You can specify the maximum number of worker processes to use by passing the `max_workers` argument to the decorator:

```python
def my_function(x, y):
    return x + y

result = await aparallize(my_function, max_workers=4)(1, 2)
```

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## Issues

If you encounter any issues or have suggestions for improvements, please open an issue on the [GitHub repository](https://github.com/vikyw89/parallize/issues).

## Acknowledgments

- Thanks to the Python community for providing powerful tools and libraries for parallel processing.

@vikyw89-20240804