semvec/pypi-packages huggingface dataset:
Frontiersman 2.0.2
Network Multiplayer Board Game
Requires Python: >=3.8

# CSI4930 Frontiersman

## README Requirements for class

Description of Project: 

A clone of Settlers of CATAN (base game, 1-4 players local multiplayer)
The game rules are included in the Help Doc.pdf

Package Name on PyPI: Frontiersman

Executable Line to Run Server: FMServer

Executable Line to Run Clients: FMClient

Gitlab Link: [https://gitlab.com/csi4930-frontiersman/csi4930-frontiersman](https://gitlab.com/csi4930-frontiersman/csi4930-frontiersman)

## Notes
FMServer must be running in order to player. Multiple clients should connect. The server can also host multiple games using different invite codes.
caispp 0.4.14
High level ML library used in CAIS++ Curriculum

# Caispp

## About
This package allows for high level ML model creation.  It uses Keras with a Tensorflow backend, and was originally created to be used for the curriculum of USC's CAIS++ (Center for AI in Society, Student Branch).  

## Use Cases
The package currently supports Image Classification.

## Installation
To install run `pip install caispp`.  This package uses Tensorflow 2.0. 

## Example usage

You can see a jupyter notebook with ouputs in the `examples/` directory.  The notebook runs the code below:

```
from caispp import ImageDataset, ImageClassifier, Path

path = Path('example_dataset/') # Path to dataset
dataset = ImageDataset(path, show_distribution=True)

classifier = ImageClassifier(dataset)
classifier.train(epochs=10)

classifier.show_history()

classifier.test(show_distribution=True)
```
## Dataset directory structure
```
├── example_dataset         
│   ├── test
│   │   ├── class1      # Directory with images of class1
│   │   ├── class2      # Directory with images of class2
│   │   └── ...       
│   ├── train
│   │   ├── class1      # Directory with images of class1
│   │   ├── class2      # Directory with images of class2
│   │   └── ...         
│   ├── valid           # Optional validation set    
│   │   ├── class1
│   │   ├── class2
│   │   └── ... 
└──  
```
Each of the `test/`, `train/`, and `valid/` directories contain subdirectories for each class.  In those subdirectories, put the images files of that class.  

## Build the package

To build the package run the `build.sh` script in the directory.  The output is stored in `dist/`.
PyVidarDB 0.1.0
Python Wrapper for VidarDB
Requires Python: >=3.5

# PyVidarDB

[![Build Status](https://dev.azure.com/vidardb/PyVidarDB/_apis/build/status/vidardb.PyVidarDB?branchName=master)](https://dev.azure.com/vidardb/PyVidarDB/_build/latest?definitionId=1&branchName=master)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pyvidardb)
[![PyPI version](https://badge.fury.io/py/PyVidarDB.svg)](https://badge.fury.io/py/PyVidarDB)

A simple python wrapper for [VidarDB](https://github.com/vidardb/vidardb-engine).

## Use PyVidarDB

PyVidarDB guarantees to support `Python >= 3.5`.
There is no need to have VidarDB installed in advance, PyVidarDB will install it automatically for you.

### Dependencies

For Linux users (Ubuntu as an example):

```bash
sudo apt-get update
sudo apt-get install git python3-pip build-essential cmake
```

For MacOS users (Please install [Homebrew](https://brew.sh/) at first):

```bash
sudo brew install git python3 cmake
```

For Windows users:

The compiler should support C++11 (at least Visual Studio 2015 update 3).

### PyVidarDB Installation

From PyPI:

```bash
pip3 install PyVidarDB
```

From Github:

```bash
git clone --recursive https://github.com/vidardb/PyVidarDB.git
pip3 install ./PyVidarDB
```

## Basic Usage

Here is the basic usage for PyVidarDB:

```python
import pyvidardb

db = pyvidardb.DB()

# Open the database, will create one if not exist.
db.open("./hello_world")

# Put a map from 'key1' to 'value1' into the database.
db.put(b"key1", b"value1")

# Get the value(s) of the provided key, will return None
# if there is no such key in the database.
value = db.get(b"key1")
assert value == [b"value1"]

# 'key2' does not exist in the database. So we will get None here.
value = db.get(b"key2")
assert value is None

# Remove 'key1' from the database.
db.delete(b"key1")

# Put a map from 'key2' to multiple values into the database.
db.put(b"key2", [b"value1", b"value2", b"value3"])

# Get the value(s) of the provided key.
value = db.get(b"key2")
assert value == [b"value1", b"value2", b"value3"]

# Remove 'key2' from the database.
db.delete(b"key2")

# Close the database.
db.close()
```

PyVidarDB supports storing one key with multiple values. For example,
`db.put(b"key", [b"value1", b"value2", b"value3"])` will put a map
from `key` to `[b"value1", b"value2", b"value3"]` into the database.
To store one key with one value, simply call `db.put(b"key", b"value")`
or `db.put(b"key", [b"value"])`. For `db.put()`, the passed key's type
must be `bytes`, while the values' type can be `bytes` or a list of `bytes`. 

For `db.get(key: bytes)` and `db.delete(key: bytes)`, the passed arguments'
types must be `bytes`. The return type of `db.get(key: bytes)` is a list of
`bytes` which contains all the values of that key. If the provided key does
not exist in the database, `None` will be returned.

More examples can be found at here: https://github.com/vidardb/PyVidarDB/tree/master/examples 

See our [wiki](https://github.com/vidardb/PyVidarDB/wiki) page for more information.