Published in MLearning.ai·2 days agoCross-Validation Techniques for Machine Learning: A Guide to Improve Model PerformanceUnderstand Different Techniques and How to Use Them for Better Model Evaluation — We develop machine-learning models from data. We want these models to be as precise as possible. But the usefulness of a model actually is determined by its performance on future data. Therefore, we must find a way to make the most of the available data useful for future data. The…Python12 min readPython12 min read
Published in FAUN Publication·Jan 19Asynchronous Django ViewsA Simple Guide to Improving Performance — Django supports asynchronous. If you don’t believe me, visit the documentation. In this article, I will talk about Django views that can work asynchronously. We use async views to handle multiple tasks simultaneously using coroutines. Before moving on to the examples, please let me remind you about some basic concepts. Concepts …Django11 min readDjango11 min read
Published in Python in Plain English·Jan 17Send Async Emails In Your Django App With Celery And RedisA Guide to Sending Async Emails with Celery and Redis — In this blog post, we will cover sending mail as an asynchronous task within a Django project. We will utilize Celery and Redis in our project. Celery is an asynchronous task queue/job queue based on distributed message passing. It is often used in Django apps to run tasks in the…Django9 min readDjango9 min read
Published in Towards Dev·Jan 16Django Q: (An Alternative) Asynchronous Task Management in DjangoGetting Started with Django Q for Asynchronous Task Management — The Django web framework (it’s a Python framework after all) normally has a synchronous running cycle. The client sends a request and the server processes it and returns a response to the client. There are several methods we can use in Django to circumvent this constraint and use asynchronous task…Django5 min readDjango5 min read
Published in DevOps.dev·Jan 15Asynchronous Task Processing in Django using Celery and RabbitMQUnlocking the Power of Concurrent Processing and Message Queues in Your Django App — Consider a standard Django application. The client made a request and was waiting for a response from the server. It was on hold for the client during the preparation of the response. Your application processed the request, validated it, connected to the database, then maybe processed that data, etc., and…Django9 min readDjango9 min read
Published in Python in Plain English·Jan 2Introduction to Python Web Scraping Libraries: Selenium, BeautifulSoup, and ScrapyUnleash the Power of Python for Web Scraping with Selenium, BeautifulSoup, and Scrapy — Web scraping is a useful tool for extracting information from websites. There are some libraries for this in Python. This blog post will review the 3 most popular ones: Selenium, Beautifulsoup, and Scrapy. …Python39 min readPython39 min read
Published in AWS Tip·Jan 2Introducing Scrapy: The Powerful Python Library For Efficient Web ScrapingGet started with web scraping using Python and Scrapy — Scrapy is a great tool to scrap web pages. It is a highly popular, fast, efficient, and easy-to-use framework. The official documentation is here. Speed: Scrapy is designed to be fast and efficient, so it can handle large amounts of data without slowing down. Extensibility: It is highly extensible, so…Python12 min readPython12 min read
Published in Towards Dev·Dec 26, 2022Type Hints Can Improve Your Python Code: A Beginner’s GuideMaximizing Code Readability, Maintainability, and Performance with Type Hints — In this post, I will talk about data type hints in Python, how they are used, and while talking about these hints, I will also talk about data types in Python. A type hint in Python is a way to provide information to static type checkers and IDEs about the…Python8 min readPython8 min read
Published in Dev Genius·Dec 26, 2022Time Series with Python: Data OperationsHow to Manipulate Time Series Data in Python? — Time series data is a type of data that is collected over a period of time, typically at regular intervals. It is commonly used in fields such as finance, economics, and meteorology, and is often analyzed to understand trends and patterns over time.Python12 min readPython12 min read
Published in Python in Plain English·Dec 24, 2022Optimization of Pandas Performance on Large DataWays to Speed Up Performance in Pandas Package — Pandas is the most famous data analysis tool in Python. Everyone uses Pandas when dealing with datasets. It is a fast, powerful, and super flexible tool. As data frames increase in size, some ways of performing some operations take longer than others. Therefore, it is important to know and use…Python11 min readPython11 min read
