semvec/pypi-packages huggingface dataset:
CharActor 1.0.5
A module for creating and managing rpg characters.
Requires Python: >=3.8
Keywords: rpg character dnd d&d dungeons and dragons dungeons & dragons player character actor charactor

# CharActor

### Description

CharActor provides a convenient collection of character-based operations. It allows you to easily create, modify and employ characters in a variety of different ways.

### Installation

```bash
pip install CharActor
```

## Usage

```python
from CharActor import character_bank, create

# Create a randomized character
character = create()

# Create a character with a specific name
character = create(name='John Doe')

# Create a character with a specific object name, character name, race, role, background and alignment
character = create('my_character', 'John Doe', 'Human', 'Fighter', 'Noble', 'Lawful Good')

# Access any of the characters
my_character = character_bank.my_character

# Access any of the characters' attributes
my_character.name # 'John Doe'
my_character.Strength # Str: 17 (+3)
```

## Characters

A character object contains a variety of attributes/methods which tend to differ from character to character.

### Attributes

* name
* _role (e.g my_character.Fighter)
* _race (e.g my_character.Human)
* _background (e.g my_character.Noble)
* _alignment (e.g my_character.LawfulGood)
* age
* Strength
* Dexterity
* Constitution
* Intelligence
* Wisdom
* Charisma
* actions
* armor_class
* character_sheet (e.g print(my_character.character_sheet))
* entity_id
* experience
* hp
* initiative
* inventory
* level
* saving_throws
* skill_points
* skillbook
* speed
* target

### Methods

* attack
* look_around
* move
* pickup
* saving_throw
* end_turn

## Character Bank

The character bank is a collection of all the characters that have been created. It is a dictionary of character objects, with the key being the name of the character. More conveniently, the character bank also allows you to access the characters as attributes. A saving system(using python's pickle) is currently under development. Until then your character's are only saved for the duration of the program.

```python
from CharActor import character_bank, create

# Create a character
character = create('my_character')

# Access the character
my_character = character_bank.my_character
print(my_character.character_sheet)
```


## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License

[MIT](https://choosealicense.com/licenses/mit/)

## Support

If you like this project or are just feeling generous, consider buying me a coffee.

[buymeacoffee](https://www.buymeacoffee.com/primalcoder)
strappa 0.1
A Python bootstrapper to help set up Python projects easily and faster

# Strappa

Strappa is a Python bootstrapper CLI tool to help set up Python projects easily and faster.

## Motivation

I was talking to my friend [Utuk](https://github.com/utukj) about why he prefers to write go more than python and he told me about how he has to put in more effort setting up a python project to enable him write good python code whereas in go, it came right out of the box. I realize this is true as most people do not even know how to set up python projects properly. This simple bootstrapper should help with that.

## Installation

You can install Strappa using pip:

```bash
pip install strappa
```

## Usage

Strappa provides a command-line interface with the following commands:

1. Set up a project in the current directory:

```bash
strappa run
```

This will:

- Set up a virtual environment
- Create a `pyproject.toml` file with pre-configured settings
- Create a `Makefile` with common development commands
- Create a `requirements.txt` file
- Set up a basic project structure (src and tests directories)
- Activate the virtual environment and install requirements

2. Execute a command in the project's virtual environment:

```bash
strappa execute <command>
```

For example:

```bash
strappa execute pip list
strappa execute python -m pytest
```

### Development Commands

This project includes a Makefile with several commands to help you develop, test, and maintain the project. Here's an overview of the available commands:

### Testing and Coverage

- `make test`: Run the project's test suite using pytest.
- `make coverage`: Run tests with coverage analysis.
- `make coverage-report`: Generate an HTML coverage report for detailed inspection.

### Linting and Formatting

- `make ruff`: Run the Ruff linter to check for code style and potential errors.
- `make ruff-fix`: Run Ruff and automatically fix issues where possible.
- `make mypy`: Run the MyPy static type checker on the source code.
- `make format`: Format the code using Ruff's formatting capabilities.
- `make lint`: Run both Ruff and MyPy for comprehensive code checking.

### Comprehensive Checks

- `make all_checks`: Run formatting, linting, and tests in sequence for a full code check.
NOBM 2404.2
Python package that benchmark DFO algorithms mainly OMADS.
Requires Python: >=3.8

# NOBM
Benchmarking suite for non-linear optimization algorithms

---

**Version 1.0.1**

Testing suite aims to benchmark derivative-free optimization (DFO) algorithms mainly 'OMADS.py' and multidisciplinary
design optimization (MDO) algorithms


---
## License & copyright

© Ahmed H. Bayoumy 
---
---
## Installation

```commandline
$ pip install NOBM
```
---
## How to use

After installing the libraries listed in the `requirements.txt`, `NOBM` can be imported in the optimization solver code. 
For benchmarking `OMADS`, the path of the JSON template, which contains the problem setup, should be entered as an 
input argument to the `OMADS.py` call. 

```commandline
python BMDFO.py uncon .\tests
```

```commandline
from NOBM.toy import * 
```
json-db-lite 0.1.2
A simple JSON file database manager
Requires Python: >=3.6

# JsonDbLite

```markdown
`json-db-lite` - это простой Python класс для управления JSON файлом в качестве базы данных. Он позволяет инициализировать, читать, добавлять, обновлять и удалять записи в JSON файле.


```

## Возможности

- **Создание пустого JSON файла при инициализации объекта**
- **Добавление новых записей**
- **Получение всех записей**
- **Очистка базы данных**
- **Удаление записи по ключу**
- **Обновление записи по ключу**

## Installation

Вы можете установить пакет через pip:

```bash
pip install --upgrade json_db_lite
```

## Использование


Пример простого использования класса JSONDatabase:

```python
from json_db_lite import JSONDatabase

db_client = JSONDatabase('small_db.json')


def add_data_to_db():
    # массовое добавление
    db_client.add_records([{"id": 1, "name": "Sara"},
                           {"id": 2, "name": "Mark"},
                           {"id": 3, "name": "Charlie"},
                           {"id": 4, "name": "David"}
                           ])
    # добавление одной записи
    db_client.add_records({"id": 5, "name": "Alex"})


def get_all_data():
    # возвращаем все данные
    return db_client.get_all_records()


def get_data(key='id', value=4):
    # возвращаем данные по ключу
    return db_client.find_records_by_key(key, value)


def update_data():
    # обновляем данные по ключу у одного словаря
    db_client.update_record_by_key(upd_filter={"id": 4}, new_data=[{"name": "Alex"}, {"age": 31}])

    # обновляем данные по ключу у одного словаря
    db_client.update_record_by_key(upd_filter={"name": "Alex"},
                                   new_data=[{"age": 40}, {"job": "python developer"}])


def dell_data():
    # удаляем данные по ключу
    db_client.delete_record_by_key(key="name", value="Alex")


def dell_all_data():
    db_client.clear_database()
```

## License

Этот проект лицензируется по лицензии [MIT](https://choosealicense.com/licenses/mit/).