semvec/pypi-packages huggingface dataset:
code-20220301-rayeesck 0.0.1
A sample package to calculate bmi
License: MIT
Requires Python: >=3.6

# BodyMassIndex Calculator

This repository consists of a simple BodyMassIndex calculator using Python.

## Summary

### About BodyMassIndex

Body mass index is a value derived using weight and height of a person.
Formula : - **BodyMassIndex(kg/m2) = mass(kg) / height(m)2**

#### Chart

| Category | Range | Health risk |
| --- | --- | --- |
| Underweight | 18.4 and below  | Malnutrition risk |
| Normal weight | 18.5 to 24.9 | Low risk |
| Overweight | 25 to 29.9 | Enhanced risk |
| Moderately obese  | 30 to 34.9 | Medium risk |
| Severely obese  | 35 to 39.9 | High risk |
| Very severely obese | 40 and above | Very high risk |

### About Calculator

1. It accepts Json file as input and returns number of overwieght people count (considering all the count above 25 BodyMassIndex) and stores the output as Json/CSV
2. Output file contains output BodyMassIndex along with Category and Health risk data.

### Future work

We can returns the people details with approximate weight to be lost or increase to reach normal BodyMassIndex.

### Install and Run

- Install the module using following command
    ```
        pip install code_20220301_rayeesck
    ```
- Import the module in your code and call the process with passing the parameters
    ```
        from code_20220301_rayeesck import process
        output = process('InputJsonPath',output_format = 'csv')
    ```
- ouput will have the number of over weight count and stores the output file in same directory with appending 'output' into the name of file.
- Parameters
    - InputJsonPath = path of input json file
    - output_format = csv/json, which format output to be stored
code-20220301-rayees 0.0.1
A sample package to calculate bmi
License: MIT
Requires Python: >=3.6

# BodyMassIndex Calculator

This repository consists of a simple BodyMassIndex calculator using Python.

## Summary

### About BodyMassIndex

Body mass index is a value derived using weight and height of a person.
Formula : - **BodyMassIndex(kg/m2) = mass(kg) / height(m)2**

#### Chart

| Category | Range | Health risk |
| --- | --- | --- |
| Underweight | 18.4 and below  | Malnutrition risk |
| Normal weight | 18.5 to 24.9 | Low risk |
| Overweight | 25 to 29.9 | Enhanced risk |
| Moderately obese  | 30 to 34.9 | Medium risk |
| Severely obese  | 35 to 39.9 | High risk |
| Very severely obese | 40 and above | Very high risk |

### About Calculator

1. It accepts Json file as input and returns number of overwieght people count (considering all the count above 25 BodyMassIndex) and stores the output as Json/CSV
2. Output file contains output BodyMassIndex along with Category and Health risk data.

### Future work

We can returns the people details with approximate weight to be lost or increase to reach normal BodyMassIndex.

### Install and Run

- Install the module using following command
    ```
        pip install code_20220301_rayees
    ```
- Import the module in your code and call the process with passing the parameters
    ```
        from code_20220301_rayees import process
        output = process('InputJsonPath',output_format = 'csv')
    ```
- ouput will have the number of over weight count and stores the output file in same directory with appending 'output' into the name of file.
- Parameters
    - InputJsonPath = path of input json file
    - output_format = csv/json, which format output to be stored
remoteweb 0.6.0
Publish your website from local environment
License: MIT
Requires Python: >=3.9

# RemoteWeb
This package enables you to publish your web site in your local environment.

If you rent a server and have a more powerful local machine than the server, 
this library will help you to run your web app computing a lot in the local machine.

Targets of this libirary:

- You are developing a web app, which requires much resource such as memory or cpu.
- You have have a machine poworful enough to run the app.
- Too large cost to prepare a cloud computing environment for the app.


## Requirements

- Python 3.9 or later  
- Go1.16 or later (if you build from the source)

## Installation
```shell
pip install remoteweb
```

## Example

```python
""" Example of RemoteWeb """
import time
import webbrowser
from threading import Thread
from http.server import HTTPServer, SimpleHTTPRequestHandler

from remoteweb import RemoteWebServer, RemoteWebClient


def run_remoteweb_server() -> None:
    """Run RemoteWebServer Application"""
    server = RemoteWebServer()
    server.run()


def run_remoteweb_client() -> None:
    """Run RemoteWebClient Application"""
    client = RemoteWebClient("http://127.0.0.1:8000", "ws://127.0.0.1:6171/remoteweb/ws")
    client.run()


server_thread = Thread(target=run_remoteweb_server, daemon=True)
client_thread = Thread(target=run_remoteweb_client, daemon=True)

with HTTPServer(("127.0.0.1", 8000), SimpleHTTPRequestHandler) as server:
    server_thread.start()
    time.sleep(3)  # wait RemoteWebServer starts
    client_thread.start()
    webbrowser.open("http://localhost:8000")  # original http server
    webbrowser.open("http://localhost:6171")  # via RemoteWeb application
    server.serve_forever()
```

You can try this code by running:
```
python -m remoteweb.demo
```


## CLI
```shell
$ remoteweb --help
Usage: remoteweb [OPTIONS] COMMAND [ARGS]...

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.

Commands:
  client  Run the client application
  keygen  Generate a pair of key
  server  Run the server application
```


## Build
 
Go1.16 or later is required

```
python setup.py build
```

## License
MIT License
catchment 0.0.1
A python package for catchment delineation
License: MIT
Requires Python: ==3.7.*


<div align="center">

# catchment

An open-source Python package for catchment delineation 🔥<br>

</div>
<br>

<div align="center">

Figure Here

</div>
<br>


## ⚡&nbsp;&nbsp;Usage

### Install
```bash
pip install catchment
```
<br>


### Example
```python
import catchment

path = f'{catchment._path}/example.csv'
Q, date = catchment.load_streamflow(path)
b, KGEs = catchment.delineation(Q, date, area=276)
print(f'Best Method: {b.dtype.names[KGEs.argmax()]}')
```
<br>



## Project Structure
The directory structure of catchment looks like this:
```
├── methods                 <- implements for 12 catchment delineation methods
│
├── recession_analysis      <- tools for estimating recession coefficiency
│
├── param_estimate          <- backward and calibration approaches to estimate other parameters
│
├── comparison              <- an evaluation criterion to comparison different methods
│
├── requirements.txt        <- File for installing catchment dependencies
│
└── README.md
```
<br>

## 📌&nbsp;&nbsp;Todo


### Nolinear reservoir assumption
- Implement the nolinear reservoir assumption from the [paper](https://github.com/xiejx5/watershed_delineation/releases)
- Employ a time-varing recession coefficiency for catchment delineation
<br>

### Applicable to other time scales
1. The current version only applies to the daily scale
2. The package needs to be updated to support hourly catchment delineation
<br>

## 🚀&nbsp;&nbsp;Publications

### The following articles detail the 12 catchment delineation methods and their evaluation criterion.
- Xie, J., Liu, X., Wang, K., Yang, T., Liang, K., & Liu, C. (2020). Evaluation of typical methods for catchment delineation in the contiguous United States. Journal of Hydrology, 583, 124628. https://doi.org/10.1016/j.jhydrol.2020.124628
zipbomb 1.0.3
Create zipbombs using python
License: MIT
Requires Python: >=3.0

# zipbomb

Create zipbombs using python

Based on [David Fifield's project](https://www.bamsoftware.com/hacks/zipbomb/)

## Installation

### From PyPI

```sh
pip3 install zipbomb
```

### From GitHub

```sh
pip3 install git+https://github.com/donno2048/zipbomb
```

## Usage

```sh
$ zipbomb -h
usage: zipbomb [-h] [-o OUTPUT] [-n NUM_FILES] [-s COMPRESSED_SIZE]

Create a zip bomb

optional arguments:
  -h, --help            show this help message and exit
  -o OUTPUT, --output OUTPUT
                        output file [default: bomb.zip]
  -n NUM_FILES, --num-files NUM_FILES
                        number of files in the zip [default: 100]
  -s COMPRESSED_SIZE, --compressed-size COMPRESSED_SIZE
                        compressed size of each file (in Kb) [default: 1000]

```