semvec/pypi-packages huggingface dataset:
Topsis-Jashan-101916123 0.1
Topsis

# Topsis Result Calculator
It runs on terminal and takes a csv file , weights of column, impacts and name of the output file as input and gives an output csv file that contains topsis performance score and the rank of a particular entity.

## Installation
On your terminal run the command below:<br>
```pip install Topsis-Jashan-101916123```

## Importing and using in source file
use the package in source file as follows:<br>

```
tbj=__import__("Topsis-Jashan-101916123")
tbj.TopsisCalc("input.csv","1,1,1,1,1","+,-,-,-,+","output.csv")
```

## How to get output?
output is taken by running the command on terminal as : python "sourcefile.py" "input.csv" "weights(separateed by ',')" "impact(separated by ','))" 
use impact as '+' for maximizing the feature and '-' for minimizing.
On your terminal run the command:<br>
```python source_file_name.py input_file.csv "1,1,0,1" "+,-,+,+" output_file_name.csv```
Output will be stored in your present working directory as a csv file.

## Constraints
### Number of columns in input file(other than the name of the entity) should be equal to length of impacts and length of weights.
### Input file should not have blank values
### Number of Columns in Input files should not be less than 3
### There should not be any csv file with same name as your output file in present directory
### Number of Arguments should be equal to the number as specified above
zoil 0.0.4
Generates random Oil and Gas Data
Keywords: python,oil,dca,reservoir engineering

# ZOil

![Language](https://img.shields.io/badge/Language-Python-success?style=flat)
![License](https://img.shields.io/badge/License-MIT-informational?style=flat)
![Version](https://img.shields.io/badge/Version-0.0.4-informational?style=flat)

ZOil is a python library used to generate random Oil and Gas data. Most Oil and Gas data is either propreitary or costly to aquire. ZOil lets you quickly generate an unlimited amount of production data that can be used to for testing, anonymization and much more. ZOil was inspired by the [`Faker`](https://github.com/joke2k/faker) library.

## Installation

```bash
pip install zoil
```

## Usage

ZOil generates random production data using the `get_production_data` shown below with default keyword arguements

```python
zoil.get_production_data(start_date=datetime(year=1950,month=1,day=1), end_date=datetime.now(), qio_min=100, qio_max=2500, qig_min=500, qig_max=5000, qiw_min=100, qiw_max=2500)
    
"""
get_production_data generates a dictionary containing random production data.

:param granularity: 'monthly' | 'daily' Granularity of data
:param start_date: The start date of the production history
:param end_date: The end date of the production history
:param qio_min: The minimum initial oil production rate
:param qio_max: The maximum initial oil production rate
:param qig_min: The minimum initial gas production rate
:param qig_max: The maximum initial gas production rate
:param qiw_min: The minimum initial water production rate
:param qiw_max: The maximum initial water production rate
:return: A dictionary containing random production data
"""
```


See the example below to visualize a random wells production decline curve using [`pandas`](https://github.com/pandas-dev/pandas) and [`matplotlib`](https://github.com/matplotlib/matplotlib)

```python
from zoil import get_production_data
import matplotlib.pyplot as plt
import pandas as pd

production_data = get_production_data()

df = pd.DataFrame(production_data)

df.plot(x='date'
        , y=['oil', 'gas', 'water']
        , color=['green','red','blue']
        , title='Production History for a Random Well'
        , xlabel='Date'
        , ylabel='Production'
    )

plt.show()
```


Each time the `get_production_data` function is called a new dictionary of production data will be generated. The occasional halts in production are to represent workovers where the well is shut-in for repair for sometime.


<p align="center">
  <img width="auto" src="https://github.com/davidzajac1/zoil/blob/main/img/example_well.png?raw=true">
</p>

## To Do

- Make data more chaotic and realistic

- Create more keyword arguements

- Create new functions for other types of data (drilling, logging, etc.)

## Contribute

For any bugs, issues, suggestions please create an Issue or a Pull Request. 

## License
ZOil is released under the MIT License. See the bundled [LICENSE](https://github.com/davidzajac1/zoil/blob/main/LICENSE) file for details.
PySuperGui 0.0.5.1
This library creates guis in a simpler way using Tkinter
Keywords: python,gui,tkinter,UI,Simple Ui,Simple Gui,window


# PySuperGui V0.0.5.1
This library creates guis in a simpler way using Tkinter.
***Remembering this library is in Development, more stuff will be added and bugs will be fixed!***
### Installing
The best way to install is using **pip** or **pip3**
Just type in cmd:
`pip install PySuperGui`
or
`pip3 install PySuperGui`
###Get Started
To create a Gui we will use **Start()**. These are the different parameters or "options" that one may use:

| Option  | Description  |
| ------------ | ------------ |
| title  | Window Title  |
| color  | Background Color  |
| width  | The width of the window  |
| height  | The height of the window  |
| posX  | The X position of the window  |
| posY  | The Y position of the window |
Example:
```python
gui = Start(title="Test",color="grey", width=200, height=200, posX=0.025, posY=0.05)
```
When creating the window it will not appear, to make it appear use:
```python
gui.show()
```
ORF-News 2.0.0
Simple orf news scraper

# ORF News Wrapper #

A simple News Wrapper of https://orf.at/ made by mcbabo

## How to use ##

Install package with

```
pip install orfnews
```

### Get top news ###
Create your main.py file

```python
import orf_news
import asyncio

# Create orf class
orf = orf_news.ORF_News()

# Call getTopicNews
newest_post = asyncio.run(orf.getTopPost("inland"))

# Print out dictionary
print(newest_post)
```

### Get top news ###
Create your main.py file

```python
import orf_news
import asyncio

# Create orf class
orf = orf_news.ORF_News()

# Call getTopicNews
newest_post = asyncio.run(orf.getTopPosts("inland", amount : int))

# Print out list with dictionaries
print(newest_post)
```

### Get all available topics ###

```python
import orf_news
import asyncio

# Create orf class
orf = orf_news.ORF_News()

# Call getTopics
topics = asyncio.run(orf.getTopics())

# Print out dictionary
print(topics)
```