semvec/pypi-packages huggingface dataset:
django-user-status 0.1.3
A Django package to show online/offline status and last seen time.
Requires Python: >=3.8

# Django User Status

A simple Django package to track and display a user's online/offline status and last seen time using Django's caching framework.

## Installation

1. Install the package:
   `pip install django-user-status`

2. Add the middleware to your `settings.py`:
   ```python
   MIDDLEWARE = [
       # ... other middleware
       'django_user_status.middleware.UserStatusMiddleware',
   ]
   ```

redis example in settings.py (if you are using redis)

```
CACHES = {
    "default": {
        "BACKEND": "django_redis.cache.RedisCache",
        "LOCATION": "redis://user:password@localhost:6379",
        "OPTIONS": {

            "CLIENT_CLASS": "django_redis.client.DefaultClient",
        },
    }
}

```

Load the template tags in your templates:

```
{% load user_status_tags %}
```

to use the template tags you need to add "django_user_status" to your INSTALLED_APPS

```
django_user_status
```

Configuration (Optional)
You can customize the package's behavior by adding the following settings to your settings.py file.

- USER_STATUS_CACHE_DURATION: The time in seconds that a user is considered "online" after their last request. Defaults to 300 (5 minutes).
- USER_STATUS_CACHE_KEY_PREFIX: The prefix for the cache key. Useful to avoid key collisions. Defaults to 'last_seen'.
  Example settings.py:

# Set the user to be "online" for 10 minutes

USER_STATUS_CACHE_DURATION = 600

# Use a different cache key prefix

USER_STATUS_CACHE_KEY_PREFIX = 'user_activity'

Usage
In your templates:
To show a user's status:

```
{% get_user_status user %}
```

To show the last seen time:

```
{% get_last_seen user %}
```

What's New in Version 0.1.2

- Bug Fix: Resolved a TypeError related to timezone-aware and naive datetimes. The package now correctly uses timezone-aware datetimes for all cache and status checks, ensuring reliability.

- Added Unit Tests: Comprehensive unit tests have been added to ensure the reliability and correctness of the middleware and template tags.
dtpu 0.2.4
Utilities for text processing tasks with Deep NLP
Requires Python: >=3.8
Keywords: nlp, utilities, text, processing

## Text utilities

This repository contains Python utilities (backed by Rust) used in many Deep 
Learning based NLP applications.

It is mainly designed to be used for whitespace correction, 
spelling correction, language modeling, and similar tasks.

You can install the Python package from PyPI via

> pip install dtpu

Windows (x64) and Linux are currently supported when installing from PyPI.
aspenautokit 0.1.2
A Python package for automating Aspen Plus simulations
Requires Python: >=3.8
Keywords: aspen, simulation, automation, chemical engineering, process simulation

This is a generalized automation methodology developed for Aspen Plus simulations.
[GitHub-flavored Markdown](https://github.com/BaileyLadd01/AspenAutoKit)


Issues and requests can be posed via GitHub in the AspenAutoKit repo.