semvec/pypi-packages huggingface dataset:
monash-battery 0.1.3
A python package for scheduling batteries of the Monash Clayon batteries
Requires Python: >=3.6

# User Guide

#### Purpose

This Python package is developed for managing the batteries to minimise the peak demand charges for Victories C&I customers. 
Instructions of running this algorithm on Mac are as the following: 

#### Installation Instructions

1.	Install MiniZinc IDE

The purpose of this step is to install the solver required for running the optimisation model. 
The instructions for installing the MiniZinc IDE are provided in the following website:

https://www.minizinc.org/software.html

2.	Prepare the Python environment

a)	Install PIP: https://phoenixnap.com/kb/install-pip-windows

b)	Install the required packages:

```pip3 install pandas minizinc numpy pandas-bokeh pathlib```


#### Run the Program 

1. Call the operation function

```
batteries_json, charges_json, previous_solutions_json = \
                opt.operation(batteries_json=batteries_json, batteries_json_file=batteries_json_file,
                              charges_json=charges_json, charges_json_file=charges_json_file,
                              loads_json=loads_json, loads_json_file=loads_json_file,
                              previous_solutions_json=previous_solutions_json,
                              previous_solutions_json_file=previous_solutions_json_file,
                              solver=solver)
```

* Examples of ```batteries_json```, ```charge_json``` and ```previous_solutions_json``` are provided in the ```tests/data``` folder.
preceptron-pypi-om 0.0.2
it's implimentation of preceptron
Requires Python: >=3.7

# preceptron_pypi
preceptron_pypi

## How to use this

```python
from synapses.perceptron import Perceptron

## get X and y and then use below commands
model = Perceptron(eta=eta, epochs=epochs)
model.fit(X, y)
```
preceptron-pypi-omkarsingh1008 0.0.1
it's implimentation of preceptron
Requires Python: >=3.7

# preceptron_pypi
preceptron_pypi

## How to use this

```python
from synapses.perceptron import Perceptron

## get X and y and then use below commands
model = Perceptron(eta=eta, epochs=epochs)
model.fit(X, y)
```
codelessalgorithms 0.0.3
This is a package that is still under developement and it is highly recommended to only use this for some very long and advanced programs and you dont want to code all the algortithms from scratch.
Keywords: python,math,algorithms,prime-numbers,sequences

This package contains only 2 functions at the moment. They are "prime_number_detector" and "arithmetic_sequence_n". To use "prime_number_detector" call it like this 

prime_number_detector("m", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) 

In here, the m stands for "manual". This means you will have to give your prime numbers manually. And the list is the prime numbers list 


 Another way to call it is like this 

prime_number_detector("s", [0, 200]) 
 In here, "s" stands for series. If you give this, you just have to put 2 numbers in the second argument and it will find all the prime numbers between the first number you put and the second number you put (including the second number)


 The second function is "arithmetic_sequence_n". This program finds the nth term of the arithmetic sequence you provide. This also takes in 2 arguments. Here is an example: 

 arithmetic_sequence_n([1, 5, 9], 65) 

 The first argument is a list of numbers which make up an arithmetic sequence. Only 3 numbers are needed in the list. the second argument is the number in the sequence you want to find.


I hope this package helps you in coding not cheating in yourmath test. :)
codelessAlgorithms 0.0.2.2
This is a package that is still under developement and it is highly recommended to only use this for some very long and advanced programs and you dont want to code all the algortithms from scratch.
Keywords: python,math,algorithms,prime-numbers,sequences

This package contains only 2 functions at the moment. They are "prime_number_detector" and "arithmetic_sequence_n". To use "prime_number_detector" call it like this 

prime_number_detector("m", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) 

In here, the m stands for "manual". This means you will have to give your prime numbers manually. And the list is the prime numbers list 


 Another way to call it is like this 

prime_number_detector("s", [0, 200]) 
 In here, "s" stands for series. If you give this, you just have to put 2 numbers in the second argument and it will find all the prime numbers between the first number you put and the second number you put (including the second number)


 The second function is "arithmetic_sequence_n". This program finds the nth term of the arithmetic sequence you provide. This also takes in 2 arguments. Here is an example: 

 arithmetic_sequence_n([1, 5, 9], 65) 

 The first argument is a list of numbers which make up an arithmetic sequence. Only 3 numbers are needed in the list. the second argument is the number in the sequence you want to find.


I hope this package helps you in coding not cheating in yourmath test. :)
codeless-algorithms 0.0.2.1
This is a package that is still under developement and it is highly recommended to only use this for some very long and advanced programs and you dont want to code all the algortithms from scratch.
Keywords: python,math,algorithms,prime-numbers,sequences

This package contains only 2 functions at the moment. They are "prime_number_detector" and "arithmetic_sequence_n". To use "prime_number_detector" call it like this 

prime_number_detector("m", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) 

In here, the m stands for "manual". This means you will have to give your prime numbers manually. And the list is the prime numbers list 


 Another way to call it is like this 

prime_number_detector("s", [0, 200]) 
 In here, "s" stands for series. If you give this, you just have to put 2 numbers in the second argument and it will find all the prime numbers between the first number you put and the second number you put (including the second number)


 The second function is "arithmetic_sequence_n". This program finds the nth term of the arithmetic sequence you provide. This also takes in 2 arguments. Here is an example: 

 arithmetic_sequence_n([1, 5, 9], 65) 

 The first argument is a list of numbers which make up an arithmetic sequence. Only 3 numbers are needed in the list. the second argument is the number in the sequence you want to find.


I hope this package helps you in coding not cheating in yourmath test. :)
XNode2Vec 0.0.1
A small example package
Requires Python: >=3.6

# XNode2Vec
Description
-----------
This repository is meant to show the strength of Node2Vec prediction algorithm and to apply it to very different types of networks. In addition, the original [Node2Vec](https://github.com/aditya-grover/node2vec) algorithm was replaced with an extremely faster version, called [FastNode2Vec](https://github.com/louisabraham/fastnode2vec). The application of the algorithm is provided by a function that works with **networkx** objects, that are quite user-friendly.

Note
-----------
9/17/2021: I had some issues when installing the fastnode2vec package; in particular, the example given by Louis Abraham gives an error. I noticed that after the installation, the declaration of the file "node2vec.py" wasn't the same as the latest version available on its GitHub (at the moment). My brutal solution was simply to just copy the whole content into the node2vec.py file. This solves the problem.

# Examples
Most Similar Nodes, Balanced Tree
---------------------------------
![tree_15](https://user-images.githubusercontent.com/79590448/132143490-64ac2417-4d21-4a87-aa42-e9e0784bcb58.png)

Most Similar Nodes Distribution, E-R
------------------------------------
![E-R_Nodes](https://user-images.githubusercontent.com/79590448/132143507-94807c17-4656-44b0-bac1-6af945d50fbf.png)

Comunity Network
----------------
![Families](https://user-images.githubusercontent.com/79590448/133808870-0c045f12-60d5-49d2-971f-e39c16aa1852.png)
PyAltium-tgross 0.0.3
A package for reading Altium files
Requires Python: >=3.6

# PyAltium

A tool to process Altium file types. Currently only supports reading of .SchLib files.

## Information & Usage

### SchLib
Currently the only schematic library capability is creating a list of
library items, with some details

Sample usage:

```python
import pprint
from pyaltium import SchLib

# Set up our pretty printer so our output is understandable
pp = pprint.PrettyPrinter(indent=4)

sl = SchLib('my_file_name.SchLib')
print(SchLib.list_items())

```

Returns 

```JSON
[
    {
        "libref": "ref1",
        "description": "My description",
        "sectionkey": "Section Key" // This is unneeded, just for internals
    },
    // ...
]
```

### PCBLib
Currently the only PCB library capability is creating a list of footprints

Sample usage:

```python
import pprint
from pyaltium import SchLib

# Set up our pretty printer so our output is understandable
pp = pprint.PrettyPrinter(indent=4)

sl = SchLib('my_file_name.SchLib')
print(SchLib.list_items())

```

Returns:

```JSON
[
    {
        "footprintref": "ref1",
        "height": "2.8", // mm
        "description": "My description"
    },
    // ...
]
```