semvec/pypi-packages huggingface dataset:
drata-python-api-client 1.1.4
A client library for accessing Drata's open API
Requires Python: <4.0,>=3.9

# drata-python-api-client
A client library for accessing The Drata public API 

## Usage
First, create a client:

```python
from drata_python_api_client.models import (
    UserResponsePublicDto, ExceptionResponsePublicDto
)
from drata_python_api_client import AuthenticatedClient

drata_client = AuthenticatedClient(region="EU", token="VeryMuchSecureToken")
```

Now call your endpoint and use your models:

```python
from drata_python_api_client.api.users import users_public_controller_get_user_by_email

user: UserResponsePublicDto = users_public_controller_get_user_by_email.sync(
    client=drata_client,
    email="some@email.com",
)
```

Or do the same thing with an async version:

```python
from drata_python_api_client.models import (
    UserResponsePublicDto, ExceptionResponsePublicDto
)
from drata_python_api_client.api.users import users_public_controller_get_user_by_email

async with client as client:
    Union[
        BackgroundCheckResponsePublicDto, 
        ExceptionResponsePublicDto
    ] = await users_public_controller_get_user_by_email.asyncio(client=client, email="some@email.com")
```

## Advanced customizations

There are more settings on the generated `AuthenticatedClient` class which let you control more runtime behavior, check out the docstring on that class for more info. You can also customize the underlying `httpx.Client` or `httpx.AsyncClient` (depending on your use-case):

```python
from drata_python_api_client import AuthenticatedClient

def log_request(request):
    print(f"Request event hook: {request.method} {request.url} - Waiting for response")

def log_response(response):
    request = response.request
    print(f"Response event hook: {request.method} {request.url} - Status {response.status_code}")

client = AuthenticatedClient(
    region="EU",
    httpx_args={"event_hooks": {"request": [log_request], "response": [log_response]}},
)

```

## Building / publishing this package

If you want to install this client into another project without publishing it (e.g. for development) then:
1. If that project **is using Poetry**, you can simply do `poetry add <path-to-this-client>` from that project
1. If that project is not using Poetry:
    1. Build a wheel with `poetry build -f wheel`
    1. Install that wheel from the other project `pip install <path-to-wheel>`
synq-ai 1.0.1
[DEPRECATED] This package has been renamed to 'synqed'. Please use 'synqed' instead: https://pypi.org/project/synqed/
Requires Python: >=3.8
Keywords: deprecated synq synqed


# synq-ai is now synqed

This package has been renamed to **[synqed](https://pypi.org/project/synqed/)**.

## Migration

synq-ai package has been renamed to [synqed](https://pypi.org/project/synqed/).

This package is deprecated. Please install and use 'synqed' instead:

    pip uninstall synq-ai
    pip install synqed

Then update your imports:

    # Old (deprecated)
    import synq_ai
    
    # New (correct)
    import synqed

For more information, visit: https://synqlabs.ai

This package will no longer receive updates. All future development happens in the `synqed` package.
allianceauth-celeryanalytics 0.0.7
Celery Task and Worker Analytics for Alliance Auth
Requires Python: >=3.8
Keywords: allianceauth, eveonline

# celeryanalytics

celery task and worker analytics for [Alliance Auth](https://gitlab.com/allianceauth/allianceauth).

## Installation

With your venv active,

1. Pip install

      `pip install -U allianceauth-celeryanalytics`

2. Add `celeryanalytics` to your `INSTALLED_APPS` in your `local.py`

3. From terminal run migrations

     `python manage.py migrate celeryanalytics`
     `python manage.py collectstatic`

4. **Optional** if you wish to havve the module cealup old tasks its self run 

     `python manage.py ca_setup_task`

## Usage
This module has no permissions. it will start logging all completed and failed tasks on install using the celery signals. To view the UI you need to be superuser, and select `Task Queues` from the side menu

### Task Menu 
Toggle sections of the UI on/off here
![Imgur](https://i.imgur.com/Zc9m0P1.png)

### Workers 
Shows basic info on alll running workers

![Imgur](https://i.imgur.com/O8j4uMw.png)

*NOTE* if you only have a single worker shown, you are probably missing the `-n %(program_name)s_%(process_num)02d` parameter in your the supervisor config commands.

### Active Tasks
Shows tasks that are running in the what workers
![Imgur](https://i.imgur.com/ERE38gE.png)

### Future Tasks
Shows tasks that are held by workers with a future ETA. These may have been retries with a cool down or tasks scheduled to run in the future.

![Imgur](https://i.imgur.com/wPeuTJ7.png)

### Queue Backlog
Shows tasks split by Queue and Priority that are still pending in the queue

![Imgur](https://i.imgur.com/rNxP74P.png)

### Specifics on failed/completed tasks
View the successful/failed tasks in admin of your auth. as below;

![Admin Menu](https://i.imgur.com/g36hJyu.png "Admin Menu")

![Failures](https://i.imgur.com/mTD224f.png "Failures")

![Details](https://i.imgur.com/ang9wXB.png "Details")

## Cleanup 
If you wish to perform a tidy-up of the database you can run the following command from your terminal

`python manage.py ca_run_housekeeping`

## Settings

`CA_HOUSEKEEPING_DB_BACKLOG` defines how long (in days) records should be kept in
your database. Default is 14 days.

`CA_RESULT_MAX_LEN` if you are using a results fed app you may wish to limit the result spam to database.
in your `local.py` add the setting `CA_RESULT_MAX_LEN=1000` set the integer to what ever you want as your max length. Default is `-1` or unlimited.

`CA_LOG_SUCCESS_TO_DB` If you don't want the module to log `Successful Tasks` to database, set this to `False`. Default is `True`

`CA_LOG_FAILURE_TO_DB` If you don't want the module to log `Failed Tasks` to database, set this to `False`. Default is `True`


## Issues

Please remember to report any celeryanalytics related issues using the issues on **this** repository.
Aplicacion-Ventas-EZamora 1.0.0
Aplicacion de ventas con manejo de impuestos y descuentos
Requires Python: >=3.7

# Aplicacion de Ventas
Este Paquete proporciona funcionalidades para gestionar ventas, incluyendo cÃ¡lculos de precios,
impuestos y descuentos

## InstalaciÃ³n

Puedes Instalar el Paquete usando:

'''bash

pip install .
"