semvec/pypi-packages huggingface dataset:
funcenter 1.4.1
Some random functions I made... includes color formatting, text formatting, basic math, and most of all... dumb algorithms. Enjoy.
License: MIT
Requires Python: >=3.8,<4.0
Keywords: color,math,printing,simple

# Funcenter

This is a simple package. You can use it however you want! Please let me know if there are any errors.

### Color/Text Formatting
This package offers some basic color and text formatting, in the form of:
- bold(`str`), b(`str`)
  - <span style="color:magenta">bold('str')</span> --> **str**
- italic(`str`), i(`str`)
 - <span style="color:magenta">italic('str')</span> --> *str*
- underline(`str`), underl(`str`), ul(`str`)
 - <span style="color:magenta">underline('str')</span> --> <u>str</u>
- format(`option`), color(`option`)
  - Sets the format or color.
- clear()
  - Clears all formatting.
- fprint(`option`, `str`), cprint(`option`, `str`)[^1]
  - Print `str` in the format of `option`.
  - <span style="color:magenta">fprint('bold, 'str')</span> --> **str**

### Printing
Some simple printing functions.
- println(`str`, `x`)
  - Prints *`x`* new lines after the `str` (default is 1).
- printsln(`str`)
  - Print the following print statement on the same line as `str`.
- printx(`str`, `x`)
  - Print `str` *`x`* times. <span style="color:magenta">`printx('str', 3)`</span> prints the following
  
    ```
    str
    str
    str
    ```
- typewriter(`str`, `speed`)[^1]
  - Print `str` character-by-character (typewriter-like effect) using `speed` *(from slowest to fastest: 1, 2, 3)*.
  - **<span style="color:red">`DO NOT USE WITH ESCAPE CHARACTERS`</span>**

### Math
Very very minimal and basic:
- is_decimal(`var`)
  - Returns <span style="color:blue">`True`</span> if `var` is a decimal.
- factorial(`num`)
  - Returns the factorial of `num`

### Other
- charsplit(`str`)
  - Returns a <span style="color:blue">list</span> of each character in `str`.
- uncharsplit(`list`)
  - Exactly what it sounds like. The reverse of the above; Returns a <span style="color:blue">string</span> of `list`. And yes I know how easy this is. I wanted it.

Any other functions not listed here are in development. Check back later.
  
[^1]: Work in progress. Use caution.
zermelo.py 1.0.2
Zermelo api wrapper library for python.
License: MIT

# Zermelo.py

[![Build Status](https://travis-ci.org/wouter173/zermelo.py.svg?branch=master)](https://travis-ci.org/wouter173/zermelo.py) [![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A Python implementation of the [Zermelo API](https://zermelo.atlassian.net/wiki/spaces/DEV).

## Features

1. Get appointments from a zermelo calendar.
2. Get data of a zermelo user.
3. Get announcements.

## Installation

To install the package run this command:

```bash
  pip install zermelo.py
```

## Usage

### Client

```python
Client()
```

params:
```
School: String ? Name of the school.
```

Result:
```
Client: Zermelo.Client()
```

Demo:
```python
from zermelo import Client

cl = Client("scalacollege")
```

### Authentication

```python
Client.authenticate()
```

Params:

```
Code: String ? A connect code you get from https://YOURSCHOOLNAME.zportel.nl/main/#connectionsModule-connectApp
```

Result:

```
Token: dict()
```

Demo:

```python
token = cl.auhtenticate("441 440 997 507")
print(token["access_token"])
```

### User

```python
Client.get_user()
```

Params: 
```
Token: String ? Access_token you get from the Client.Authenticate() function
```

Result:

```
User: dict()
```

Demo:

```python
user = cl.get_user(token["access_token"])
print(user)
```

### Appointments

```python
Client.get_appointments()
```

Params: 
```
Token: String ? Access_token you get from the Client.Authenticate() function
StartUnix: int ? Unix timestamp for the first date you want to get the appointments from.
EndUnix: int ? Unix timestamp for the last date you want to get the appointments from.
```

Result:

```
Appointments: dict()
```

Demo:

```python
appointments = cl.get_appointments(token["access_token"], 1567468800, 1568073600)
print(appointments)
```

### Announcements

```python
Client.get_announcements()
```

Params: 
```
Token: String ? Access_token you get from the Client.Authenticate() function
```

Result:

```
Announcements: dict()
```

Demo:

```python
announcements = cl.get_announcements(token["access_token"])
print(announcements)
```

### Enrollments

```python
Client.get_liveschedule()
```

Params: 
```
Token: String ? Access_token you get from the Client.Authenticate() function
Week: String ? The ISO-week for which you want to request the schedule
Usercode: String ? The code of the student you want to request the schedule of 
```

Result:

```
Enrollments: dict()
```

Demo:

```python
usercode = cl.get_user(token["access_token"])["response"]["data"][0]["code"]
enrollments = cl.get_liveschedule(token["access_token"], "202150", usercode) # Requests week 50 of the year 2021
print(enrollments)
```

# License
[MIT](https://github.com/wouter173/zermelo.py/blob/master/LICENSE)
ossuary 0.1.0a0
dice analysis toolkit
License: MIT
Requires Python: >=3.11.0rc2
Keywords: dice,probability

# ossuary 🎲 probability analysis toolkit

A Python package for analyzing dice and other randomizers.

Features:

* Exact values for probability computations.
* Statistical analysis (mean, mode, standard deviation).
* Graph plotting with visualization of median and other quantiles.
* Support for symbolic as well as numeric dice.
* Command-line evaluator for ease of use.
* Python API for extensibility.

Installation
------------
```
pip install ossuary
pip install matplotlib  # optional graphing support
```

Commands
--------
Roll a die.
```
ossuary d6
```
Roll d4+1 three times and add the results.
```
ossuary '3 @ (d4+1)'
```
Roll 4d6 and add the highest 3 dice.
```
ossuary 'Dice.NdX(4, d6, kh=3).sum()'
```
Take the middle die out of three d20 rolls.
```
ossuary 'Dice.NdX(3, d20, km=1).sum()'
```
Graph 12d6 with the results partitioned by deciles.
```
ossuary '(12 @ d6).plot(q=10)'
```