Date: Oct 1, 2023
Rust is a great language for network programming. Learn how to build a basic HTTP proxy in just 40 lines of code. Also, discover the benefits of using a rotating proxy to avoid IP blocking.
Date: Dec 6, 2023
Learn how to cache API responses in Python to improve performance. Caching reduces API requests, improves speed, and lowers costs.
Date: Feb 3, 2024
Using persistent sessions in Python Requests library improves performance and allows reusing connections for multiple requests.
Date: Nov 4, 2023
Loofah is a Ruby library for parsing and manipulating HTML/XML documents. It provides a simple API for traversing, manipulating, and extracting data from markup. It also offers XSS sanitization and integrates with Rails. Loofah is built on top of Nokogiri, providing speed and Ruby idioms.
Date: Mar 17, 2024
Python's asyncio library and multiprocessing module can be combined for improved resource utilization and cleaner code. Data passing between the two requires caution.
Date: Feb 5, 2024
Choosing the right XML parsing library is crucial for performance. lxml is the fastest option, taking only 0.35 seconds compared to over 2 seconds with xml.etree.ElementTree. It's well worth the extra setup.
Date: Mar 25, 2024
Redis is a popular in-memory data store known for its speed and versatility. By combining Redis with Python's asyncio module, you can build extremely fast and scalable applications.
Date: Feb 20, 2024
Simplifying HTTP requests with PoolManager in Python. PoolManager manages a pool of connections for reusing, improving performance. Customize pool behavior for better resource usage.
Date: Feb 3, 2024
Python's requests library provides a fast and simple interface for making HTTP requests, offering better performance than urllib for most use cases.
Date: Mar 3, 2024
Managing request timeouts in aiohttp is crucial for good performance. Default timeouts may cause resource exhaustion and unresponsive UI. Tuning timeouts based on application load and setting them globally can prevent failures and improve user experience.
Date: Feb 5, 2024
Web scrapers extract data from websites using parser libraries like lxml and BeautifulSoup. lxml is faster and more valid, while BeautifulSoup is more convenient and resilient.
Date: Feb 3, 2024
Python offers options for HTTP requests with http.client and requests. http.client is faster for simple requests, while requests is more feature-rich. Use http.client for speed and requests for complex applications.
Date: Feb 6, 2024
Making HTTP requests in Python is common. urllib's PoolManager helps in reusing connections to each host, boosting performance.
Date: Mar 24, 2024
Python's multithreading capabilities are limited by the Global Interpreter Lock (GIL), but can still provide performance benefits for I/O-bound tasks. Tips include using multiprocessing for CPU-bound tasks and avoiding shared memory between threads.
Date: Mar 17, 2024
Async IO vs Threading in Python: A Practical Comparison. Async IO and threading are two options for concurrency in Python. This article compares their strengths and weaknesses, including performance, scalability, and library compatibility.
Date: Mar 24, 2024
When writing Python programs, developers often wonder if it's better to use threads or processes. Processes are generally faster and more robust, but have higher overhead. Threads require less resources to create, but come with their own challenges.
Date: Jan 9, 2024
Dealing with proxies in Go for web scraping: setup, security, privacy, performance, and troubleshooting. Proxies API offers a solution for developers.
Date: Feb 22, 2024
The Python aiohttp library provides powerful async HTTP client/server functionality. Benchmarking quantifies metrics like requests per second, latency distributions, and resource usage to guide optimization and capacity planning.
Date: Mar 17, 2024
Multithreading improves performance. C++, Java, and Go are fastest. Optimize with thread pools, shared state, and reducing blocking.
Date: Mar 17, 2024
Python provides two major approaches for concurrent and parallel programming: asyncio and thread pools. Choosing the right concurrency tool can impact performance, scalability, and code complexity.
Date: Feb 3, 2024
Rust is a systems programming language focused on performance, reliability, and efficiency. reqwest is a popular HTTP client library for Rust, providing a similar developer experience to Python's requests package.
Date: Mar 17, 2024
Asyncio provides concurrency, not parallelism. It shines for I/O bound work and can achieve high performance. Use multiprocessing for CPU intensive tasks.
Date: Feb 3, 2024
Python Requests library provides simple interface for making HTTP requests. Supports synchronous and asynchronous requests using threads or processes.
Date: Feb 22, 2024
Python developers can choose between Curio and aiohttp for async IO. Curio is great for CPU-bound tasks, while aiohttp is ideal for IO-bound HTTP applications. Both libraries are well-optimized for performance.
Date: Mar 17, 2024
Python developers often need to make their programs concurrent to improve performance. The two main options for concurrency in Python are asyncio and multithreading.
Date: Feb 22, 2024
aiohttp library in Python allows running WSGI apps directly, providing better performance and leveraging aiohttp's features.
Date: Mar 17, 2024
Python's asyncio module enables non-blocking concurrency, improving performance, scalability, and user experience.
Date: Mar 17, 2024
Multithreading in Python can improve performance and responsiveness. Choose the right model based on use case and tradeoffs. Options include threading, multiprocessing, and asyncio.
Date: May 7, 2024
REST and SOAP are two types of APIs with key differences in architecture, data formats, verbs, and performance. REST is faster and more scalable, while SOAP offers more security and robust messaging.
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