semvec/pypi-packages huggingface dataset:
eduimporter 1.0.0
Пакет инструментов для импорта данных
Requires Python: >=3.9

# eduimporter

Пакет инструментов для импорта данных.

## Установка

```bash

  $ pip install eduimporter[report]

```

## Тестирование

Для запуска тестов используется tox.

Установка tox:

```bash

$ pip install tox

```

Запуск тестов из директории пакета:

```bash

$ tox

```
py-busline 0.3.0
Agnostic eventbus for Python
Requires Python: >=3.8

# Busline for Python

Agnostic eventbus for Python.

## Local EventBus

### Using Publisher/Subscriber

```python
from src.eventbus.async_local_eventbus import AsyncLocalEventBus
from src.eventbus_client.publisher.local_eventbus_publisher import LocalEventBusPublisher
from src.event.event import Event
from src.eventbus_client.subscriber.local_eventbus_closure_subscriber import LocalEventBusClosureSubscriber


local_eventbus_instance = AsyncLocalEventBus()       # singleton

def callback(topic_name: str, event: Event):
    print(event)

subscriber = LocalEventBusClosureSubscriber(local_eventbus_instance, callback)
publisher = LocalEventBusPublisher(local_eventbus_instance)

await subscriber.subscribe("test-topic")

await publisher.publish("test-topic", Event())      # publish empty event
```

### Using EventBusClient

```python
from src.event.event import Event
from src.eventbus_client.local_eventbus_client import LocalEventBusClient

def callback(topic_name: str, event: Event):
    print(event)

client = LocalEventBusClient(callback)

await client.subscribe("test")

await client.publish("test", Event())
```


## Create Agnostic EventBus

Implement business logic of your `Publisher` and `Subscriber` and... done. Nothing more.

```python
from src.event.event import Event
from src.eventbus_client.publisher.publisher import Publisher

class YourEventBusPublisher(Publisher):

    async def _internal_publish(self, topic_name: str, event: Event, **kwargs):
        pass        # send events to your eventbus (maybe in cloud?)
```

```python
from src.eventbus_client.subscriber.subscriber import Subscriber
from src.event.event import Event

class YourEventBusSubscriber(Subscriber):
    
    async def on_event(self, topic_name: str, event: Event, **kwargs):
        pass        # receive your events
```

You could create a client to allow components to use it instead of become a publisher or subscriber.

```python
from src.eventbus_client.eventbus_client import EventBusClient
from src.event.event import Event

def client_callback(topic_name: str, e: Event):
    print(e)

subscriber = YourEventBusSubscriber(...)
publisher = YourEventBusPublisher(...)

client = EventBusClient(publisher, subscriber, ClosureEventListener(client_callback))
```
nanolab 0.0.27
testing tool using nanomock

##NanoLab

NanoLab is an easy-to-use testing tool designed to run test cases against a local network of nano-nodes. It utilizes [NanoMock](https://github.com/gr0vity-dev/nanomock), a highly customizable tool for creating dockerized nano networks, to facilitate quick and efficient testing of various configurations. Simply provide a config file for the test case and watch NanoLab streamline your testing process.

###Features:

- Run test cases against a local network of nano-nodes
- Leverages NanoMock for dockerized nano network creation
- Simple configuration with JSON
- Compatible with Python 3.8+ and Docker

###How to install:
`pip install nanolab`

###How to use:
|Command| Description
|----|----|
| `nanolab list`| List all available testcases
| `nanolab run -t {testcase}` | execute a testcase 


###How to use with options:

|Command| flag | 
|----|----|
| `-t --test-case`  | Use one of the available testcases (`nanolab list`)
|                   | Can be a `/path/to/config.json` on your disk
| `--gh-user --gh-repo --gh-path` | Default : [gr0vity-dev nanolab-configs default](https://github.com/gr0vity-dev/nanolab-configs/tree/main/default)
|                   | Used in `nanolab list` to show available testcases
|                   | Used in `nanolab run` to download the selected testcase 
| `-i --image`      | List of docker images used per testrun
mt-excel 0.0.4
A package for interacting with excel files
Requires Python: >=3.11

# mt_excel

This is designed to work with MaxTrack.

The package is designed to facilitate interaction with excel files.

It is designed to be used as a module within __MaxTrack__.

[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to figure out how to write more content.