semvec/pypi-packages huggingface dataset:
CalculatorPackage.rsertv-DWWP.1 1.0
A simple python package that allows users to perform the most basic arithmetic functions.
Requires Python: >=3.7

## CalclculatorPackage

### Description
'Calculator' is a simple python package that allows users to perform the most basic arithmetic functions.

### Available functions:
- Addition (`.add(n)`)
- Subtraction (`.subtract(n)`)
- Multiplication (`.multiply(n)`)
- Division (`.divide(n)`)
- N Root (`.nRoot(n)`)

### Prerequisites
- Python
- Git

### Installation
Package is available to download from GitHub, simply clone the project and run `pip install .` inside the directory after setting up virtual python environment. Furthermore, if user wants to access the package from a different virtual environment, it can be done by running the following command:
```
import sys
sys.path.append("PATH_WHERE_PACKAGE_IS_INSTALLED")
from calculator.calculator import Calculator
```

Package could also be imported more elegantly by just running the following command in the command line
`pip install git+https://github.com/TuringCollegeSubmissions/rsertv-DWWP.1#egg=Calculator`
,but since the project is currently in a private GitHub directory, this method will not work.

### How to use
After successfully importing the package to the project, a `Calculator()` object must be created by running the following command:
`calculator = Calculator()`.
Now to use the calculator user can run the aforementioned commands as such:
```calculator.add(5)  # OUTPUT: 0 + 5 = 5  
calculator.subtract(2) #OUTPUT: 5 - 2 = 3  
calculator.multiply(9) #OUTPUT: 3 * 9 = 27  
calculator.divide(3)   #OUTPUT: 27 / 3 = 9  
calculator.nRoot(2)    #OUTPUT: 9 ^ (1/2) = 3  
calculator.reset()     #OUTPUT: Memory cleared

```

### Tests
Package also includes tests which are located inside tests/calculator_test.py. One of the ways to run the test is to simply run `calculator_test.py` from command line when inside the test directory.
vpselector 1.0.2
Visualize and interactively select time-series data from a pandas DataFrame.
Requires Python: >=3.8
Keywords: python,dataframe,pandas,visualization,data selection,time-series data,data tools,data science,data-driven engineering,machine learning,system identification

# vpselector

The Visual Pandas Selector is a tool to visually select portions of numeric time-series data from a pandas dataframe. The tool is intended to provide an fast interactive way for manual data selection, as can be very useful in for example machine learning, regression or system identification.

Easily configure the tool to plot dataframe columns in vertically stacked subplots and view data distributions with the included histogram feature. With a simple click and drag, you can then select horizontal data windows, and let the tool automatically combine them into a new dataframe.

The user can subsequentially select different horizontal data windows via click and drag and he tool then automatically combines the visually selected sections into a new dataframe.

![ezgif com-gif-maker(1)](https://github.com/manumerous/visual-pandas-curator/assets/18735094/b5ebbb99-d2f7-4901-b101-cbeed6c230aa)


## Install

Install the package using:

```bash
pip install vpselector
```

## Use in your project

Then simply import it using `import vpselector`. Then simply use:

- If your project does not contain a pyqt application: `vpselector.select_visual_data(data : pd.DataFrame, plot_config : dict)` 

- To add the vpselector to an existing pyqt application: `vpselector.select_visual_data_in_pyqt_app(data : pd.DataFrame, plot_config : dict, pyqt_app)` 


## Run the Example 

```bash
python3 vpselector_example.py
```

#### Use the Tool

- Left click with your mouse and drag to define the desired horizontal window of the data to be selected.
  - The current selection distribution is now visualized in the histogram plot on the right.
- Confirm or cancel data selection.
  - The already selected data is now marked by a grey span in the plot on the left.
  - The plot on the right contains now the histogram of all selected data.
- repeat as many times as needed.
- Once you could select all desired horizontal data windows click "Done selecting"
dynatype 0.0.1
A dynamic type checker in Python.
Requires Python: >=3.7

# dynatype
A dynamic type checker for Python.
## What happens?
When you import the module, it silently decorates all your functions with a type checker.
## How do I use it?
Type annotate it like you would in regular Python except using the annotation object (e.g. `def f(a: dynatype.annotation(lambda x: type(x) is float or type(x) is int, lambda x: x < 0.5))`). That annotation only allows numbers less than 0.5 to be passed into the function.
## What happens when an innapropriate value is passed?
A `TypeError` is raised, allowing you to catch the error if you don't want the program to stop.
parspy 0.0.1.1
A lightweight parsing library.
Requires Python: >=3.7

# parspy
A tool to parse text into a list where it can be interpreted and executed.
## Install
Install using `pip install parspy`.
## Usage
First, import and initiate the class:
```python
import re
import parspy
parsertool = parspy.Parser()
```
Then, add elements to the alphabet:
```python
parsertool.addelems("ad", "bc", " ")
```
If you have things more complicated than static elements, use the `setregelems` method by feeding it compiled regex objects:
```python
parsertool.setregelems(number = re.compile("Number: \d+"), string = re.compile("String: '.*'"))
```
But what use is this without using it to parse something? None. Here is how you parse a string with this:
```python
parsertool.parse("adbcbcbcad  Number: 123      String: 'banana!'")
```
The output should be:
```python
['ad', 'bc', 'bc', 'bc', 'ad', ' ', ' ', {'number':'Number: 123'}, ' ', ' ', ' ', ' ', ' ', ' ', {'string':"String: 'banana!'"}]
```
Now you can pass this into a program where it can be processed more easily.

If something goes wrong during parsing, a `ParseError` will be thrown.
## Notes
It seems to have an issue when executing in a REPL environment (`name 're' is not defined`).
streamlit-copy-to-clipboard 0.0.1
Streamlit component that allows you to copy to clipboard via button
Requires Python: >=3.7

# streamlit-custom-component

Streamlit component that allows you to do X

## Installation instructions

```sh
pip install streamlit-custom-component
```

## Usage instructions

```python
import streamlit as st

from my_component import my_component

value = my_component()

st.write(value)
```