django-redis
NLTK
| django-redis | NLTK | |
|---|---|---|
| 6 | 64 | |
| 2,800 | 13,035 | |
| 0.7% | 0.8% | |
| 8.6 | 8.1 | |
| 11 days ago | 14 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
django-redis
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Everything You Need to Know About Caching in Django
Redis is an open-source data-structure store that can be used as a database, cache, message broker, etc. To start using Redis in your Django application, you need to first install the django-redis library. The library makes it easier to connect your Django application to Redis.
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Caching Django Applications using Redis
To implement caching in Django application. First, set up your Django project and application. Then install django-redis, a project by Jazzband:
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Konohagakure Search
django-redis
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Django 4.0 will include a built-in Redis cache back end
This isn't such a big deal... There are great third-party packages (i.e https://github.com/jazzband/django-redis) for whoever needs a redis cache backend in a project.
Myself, I just use good ol' memcached for all my caching needs (https://docs.djangoproject.com/en/3.2/topics/cache/#memcache...). It is rock solid and has never failed me till now!
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Multiple Post Requests, data loss
If your example of the counter is accurate for what you want to do, it might be faster using django-redis as your cache backend and using the incr method (which adds one to a given cache key). Repeatedly inserting and deleting database records is much slower than cache operations like that would be. Or is there a way you can avoid deleting database records, and modify existing values?
- Where to load file with a list that will be accessed by almost view and page refresh?
NLTK
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Building a local AI smart Home Assistant
alternatively, could we not simply split by common characters such as newlines and periods, to split it within sentences? it would be fragile with special handling required for numbers with decimal points and probably various other edge cases, though.
there are also Python libraries meant for natural language parsing[0] that could do that task for us. I even see examples on stack overflow[1] that simply split text into sentences.
[0]: https://www.nltk.org/
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Sorry if this is a dumb question but is the main idea behind LLMs to output text based on user input?
Check out https://www.nltk.org/ and work through it, it'll give you a foundational understanding of how all this works, but very basically it's just a fancy auto-complete.
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Best Portfolio Projects for Data Science
NLTK Documentation
- Where to start learning NLP ?
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Is there a programmatic way to check if two strings are paraphrased?
If this is True, then you need also Natural Language Toolkit to process the words.
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[CROSS-POST] What programming language should I learn for corpus linguistics?
In that case, you should definitely have a look at Python's nltk library which stands for Natural Language Toolkit. They have a rich corpus collection for all kinds of specialized things like grammars, taggers, chunkers, etc.
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Transition to ml, starting with LLM
If not, start with Python's Natural Language Toolkit.
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Learning resources for NLP
Try https://www.nltk.org it runs you through the basics. The book is here
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Which programming language should I learn for NLP and computational linguistics?
In terms of programming languages, Python is a great first programming language. the learnpython subreddit has lots of good recommendations for resources to get started. Once you're comfortable with the language, NLTK would be a good place to start, and the docs have heaps of examples. Check it out https://www.nltk.org/
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Python for stock analysis?
The most popular library to do this is NLTK though I believe you can use some of the popular AI API services today as well. Bloomberg launched one.
What are some alternatives?
redis-py - Redis Python client
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
django-cacheops - A slick ORM cache with automatic granular event-driven invalidation.
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Hiredis - Minimalistic C client for Redis >= 1.2
bert - TensorFlow code and pre-trained models for BERT
django-rest-framework - Web APIs for Django. 🎸
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
polyglot - Multilingual text (NLP) processing toolkit
Django - The Web framework for perfectionists with deadlines.
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)