semvec/pypi-packages huggingface dataset:
EVsSimulator 0.0.12
A realistic V2X environment using gym
Requires Python: >=3.6
Keywords: gym,Reinforcement Learning,V2X,EVs,EVsSimulator,Electric Vehicles,Electric Vehicle Simulator

# EVsSimulator
A realistic V2X Simulation Environment for large scale EV charging optimization!

<!-- Bullet points with all the benefits -->
## Features

* The simulator can be used to evaluate any type of algorithm to gain insights into its efficiency.
* The “gym environment” can readily support the development of RL algorithms.
* Uses only open-source data.
* Replays of simulations are saved and can be solved optimally using the Gurobi Solver.
* Easy to incorporate additional functionality for any use-case.
* Does not simulate the grid yet, but groups EV chargers at the level of the transformer/ parking lot, etc, so extra functionality can be easily added.


Focused on **realistic** parameters and **fully customizable**:
* Transformer models
  * Max Current
* Charging Stations models
  * Min and Max charge/discharge power/ Current
  * Voltage and phases, AC or DC
  * Charge and discharge efficiency
  * List of connected transformers
* Electric Vehicles models
  * Connected charging station and port
  * Min and Max battery energy level
  * Time of arrival and departure
  * Energy at arrival/ desired energy at departure
  * Min and Max current /power levels
  * Constant-Current/ Constant-Voltage load-curve option 


## Data sources
* The number and the topology of Transformers, Charging stations, and Electric Vehicles are parameterizable.
* Charging/ Discharging prices are based on historical day-ahead prices.
* EV spawn rate, time of stay, and energy required are based on realistic distributions ElaadNL,time, day, month and year.
* EV and Charger characteristics are based on real EVs and chargers existing in NL.

## File Structure
```bash
├── EVsSimulator
│   ├── __init__.py
│   ├── baselines
│   │   ├── __init__.py
│   │   ├── DDPG
│   │   ├── DT
│   │   ├── gurobi_models

```

## Citation
If you use this code in your research, please cite it using the following BibTeX entry:
```bibtex
@misc{EVsSimulator,

}
```

## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
```
erpy 0.1.1
Leverages the existing Term package to implement a simple Erlang port driver that communicates over standard input and output.
Requires Python: >=3.10

# ERPY

This library wraps around the Python version of the Term library to provide
a simple mechanism for communicating between an Erlang process and a Python
process.

## Installation

As always, use `pip`, preferably within a virtual environment.

```
pip install erpy
```

## Usage

### Encoding and Decoding Erlang Terms

Use the `term` library. Their documentation is [here](https://pyrlang.github.io/Term/), 
and the python version of their library is bundled with this library. If you 
want to get the Rust one working with PyPi, I'm sure that they would apprecate 
it `:)`.

## Basic Communication over STDIO

### Sending Messages From Python

```python
from erpy import stdio_port_connection

inbox, port = stdio_port_connection()
for i in range(100):
    port.send(i)

```

### Receiving Messages In Python

```python
from erpy import stdio_port_connection
from term import Atom

inbox, port = stdio_port_connection()

for msg in inbox:
    if msg == Atom("close"):
        break
    
    with open("output.txt", "a") as f:
        print(f"got {msg}", file=f)
```