semvec/pypi-packages huggingface dataset:
task-barn 0.2.0
Lightweight scheduler and worker for Django using a database backend
License: MIT
Requires Python: >=3.10
Keywords: django, distributed, multiprocessing, task, scheduler

# barn-py

Lightweight scheduler and worker for Django using a database as backend.

The task worker and scheduler use the database as a queue to store and find tasks to process
and you can forget about using `transaction.on_commit`.

**If you need a billion messages per second, please leave.**

### Examples

#### Use generic models

```python
from django.http import HttpRequest, HttpResponse
from django.db import transaction
from barn.decorators import task

@transaction.atomic
def index(request: HttpRequest) -> HttpResponse:
    html = "<html><body>Hello</body></html>"
    # do something with database
    dummy.delay(view="index", code="12")
    return HttpResponse(html)


@task
def dummy(view: str, code: str) -> str:
    # task called inside transaction
    return "ok"
```

#### Use your models (prefered)

You can specify your own model for schedule and task and this approach is preferred.

```python
from django.db import models
from django.core.mail import send_mail
from barn.models import AbstractTask


class EndOfTrialPeriodTask(AbstractTask):
    user = models.ForeignKey('auth.User', models.CASCADE)

    def process(self) -> None:
        # go somewhere and do something...
        self.user.is_active = False
        self.user.save()
        NotifyEndOfTrialPeriodTask.objects.create(user_id=self.user_id)


class NotifyEndOfTrialPeriodTask(AbstractTask):
    user = models.ForeignKey('auth.User', models.CASCADE)

    def process(self) -> None:
        if self.user.email:
            send_mail(
                "End of trial period",
                f"Hello {self.user.get_full_name()}. Your trial period has ended.",
                "from@example.com",
                [self.user.email],
                fail_silently=False,
            )


class EndOfSubscriptionTask(AbstractTask):
    user = models.ForeignKey('auth.User', models.CASCADE)

    def process(self) -> None:
        # go somewhere and do something...
```
pyrustats 0.2.1.2
Basic data structures for statistics
License: MIT
Requires Python: >=3.11.9
Keywords: statistics, distributions

# pyrustats package
A simple package about statistics made by Ruukha  <br />
Currently it can only do Gaussian and Binomial distributions  <br />

# Files
Generaldistribution.py creates the 'Distribution' class for the distribution types to inherit  <br />
Gaussiandistribution.py creates the 'Gaussian' class  <br />
Binomialdistribution.py creates the 'Binomial' class  <br />
Both Gaussian and Binomial class files create functions to calculate the mean, standard deviation, probability density function (pdf), histogram, and a function to plot the normalized histogram of the data and a plot of the pdf along the same range  <br />

# Installation
No special requirements other than matplotlib  <br />

# Changelog
0.2.1: cleaned the code, fixed the package importing with a wrong name.  <br /> 
In Binomialdistribution, if you add a file path as an argument to replace_stats_with_data, it will automatically call read_data_file. Else it will work as previously  
<br />

# License
Copyright 2024 Ruukha

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
cutoop 0.1.0
Common UTilities for Omni6DPose
License: MIT
Requires Python: >=3.7
Keywords: post_estimation

Common UTilities for Omni6DPose
===============================

**cutoop** (pronounced ``/'kʌtup/``) is the official package containing convenient
utilities for data preparation and model evaluation over the Omni6DPose
dataset.

Visit `Omni6DPose <https://jiyao06.github.io/Omni6DPose/cutoop>`_ for details.
v0.1.0
======

- Initial release

MIT License

Copyright (c) 2024 Weiyao Huang

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.