semvec/pypi-packages huggingface dataset:
myfilesize 1.0.0
A package to find small and large files in a directory
Requires Python: >=3.6

# myfilesize

`myfilesize` is a Python package designed to help you easily find small and large files within a directory structure.

## Installation

You can install the package using pip:

```bash
pip install myfilesize
```

## Usage

### Finding Small Files

```python
from myfilesize import find_small_files

directory_to_search = "/path/to/directory"
small_file_max_size_in_bytes = 1024  # Files smaller than 1KB
small_files = find_small_files(directory_to_search, small_file_max_size_in_bytes)

print("Small files:")
for file in small_files:
    print(file)
```

### Finding Large Files

```python
from myfilesize import find_large_files

directory_to_search = "/path/to/directory"
large_file_min_size_in_bytes = 10485760  # Files larger than 10MB
large_files = find_large_files(directory_to_search, large_file_min_size_in_bytes)

print("Large files:")
for file in large_files:
    print(file)
```

## Benefits

- **Simplicity**: Easily find files based on size criteria with straightforward functions.
- **Efficiency**: Quickly navigate through directories to locate files that meet your size requirements.
- **Integration**: Seamless integration into your Python projects for file management tasks.

## Contributing

Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change.

## License

This project is licensed under the [MIT License](https://choosealicense.com/licenses/mit/).

---

Thank you for using `myfilesize`! If you find this package helpful, consider starring the repository on [GitHub](https://github.com/ByteBreach/myfilesize). Your support is greatly appreciated!
fino2py 0.1.0.7
A package to help researchers and clinicians work with data produced by the Finapress Finometer and Nova devices
Requires Python: <4.0,>=3.11

fino2py: A Python Package for Finometer Data Processing
================================================

fino2py is a Python package that provides tools for processing raw data produced by either the Finapress Finometer or the Finapress Novapress. It offers a range of functions for ingesting, reshaping, and aggregating data, making it easier to work with cardiovascular data collected using these devices.

Features
--------
- Import raw data from `.txt` or `.csv` files generated by the finometer without needing to manually copy/paste from Beatscope, or mannualy merge multiple files
- Reshape  data into a minute-by-minute format to allow for trends to be identified
- Generate experimental protocol averages for each cardiovascular measure
- Append cardiovascular data from multiple files
- Save the processed data to `.csv` format for importing into python, R, SPSS or other stats software

Installation
------------
You can install fino2py using pip:

Windows

```
$ pip install fino2py
```


Documentation
-------------
The complete documentation for fino2py, including installation instructions and usage examples, can be found at [Read the Docs](https://fino2py.readthedocs.io/en/latest/).

Citing
------
If you use fino2py in your research or project, please cite it as:

Package Name: fino2py
Version: 0.1.1
Authors: Kev O'Malley, Ailbhe Dempsey, Siobhan Howard, Grace McMahon, Siobhan Griffin
Publication Date: May 2023

APA Style:
------------
```
O'Malley, K., Dempsey, A., Howard, S., McMahon, G., Griffen, S., (2023). fino2py (Version 0.1.0)[Software].            Available from https://pypi.org/project/fino2py
```

BibTeX:
------------
```
@misc{fino2py,
  title = {fino2py},
  version = {1.0},
  author = {O'Malley, Kev and Dempsey, Ailbhe and Howard, Siobhan and McMahon, Grace and Griffin, Siobhan},
  year = {2023},
  month = {June},
}
```

Contributing
------------
Contributions are welcome! If you find any issues or have suggestions for improvements, please submit them to the [GitHub repository](https://github.com/spider-z3r0/fino2py).


License
-------
This project is licensed under the MIT License
mw-sdk-python 0.0.2
ModelWhale SDK
Requires Python: >=3.8

# mw-sdk-python

## 简介
`mw-sdk-python` 是一个用于与 Heywhale 平台交互的 Python SDK，旨在简化数据集的获取和管理。

## 安装

```bash
pip install mw-sdk-python
```

## 示例代码

以下是一个示例代码，展示了如何使用 `mw-sdk-python` 获取数据集的详细信息。

```python
from mw-sdk-python.api import get_dataset
# 示例用法
if __name__ == "__main__":
    dataset_id = "替换为你的数据集ID"  # 替换为你的数据集ID
    token = "替换为你的token"  # 替换为你的token或留空以使用MW_TOKEN

    try:
        dataset_details = get_dataset(dataset_id, token)
        print(dataset_details)
    except requests.exceptions.HTTPError as err:
        print(f"HTTP错误: {err}")
    except Exception as err:
        print(f"发生错误: {err}")
```

## 环境变量

- `MW_TOKEN`: 用于身份验证的令牌。如果未提供 token 参数，SDK 将使用此环境变量。
- `HEYWHALE_HOST`: Heywhale 平台的主机地址（可选）。默认值为 `https://www.heywhale.com`。

## 许可证
MIT
python-runtime-metrics 1.2.1
A Prometheus metrics collector for runtime metrics
Requires Python: >=3.6

# MetricsCollector

MetricsCollector is a Python module that allows you to collect and expose metrics of python applications using prometheus.

## Features

- This provides metrics like garbage collections,cpu,memory,fds,thread count.
- Exposes metrics via an HTTP server for Prometheus to scrape.

## Installation

You can install MetricsCollector using pip:

```shell
pip install metricscollector
```

## How to use

    from coreTeamMetrics import MetricsCollector
    
    server_port = server_port 
    metrics_collector = MetricsCollector(server_port)
    metrics_collector.start()