As the data volume exploded, the system responded very slowly. We carried out a series of optimizations on the application, and the system’s response time improved by an order of magnitude. Overall, optimizations in file compression and faster network access gave a noticeable boost to frontend performance, while optimizations in stored procedures, caching, and logic code gave a noticeable boost to backend performance.

Compiled from the “Development Tips” series, collecting common problems and solutions in Python and Django development. 1. Sorting Python Iterables Iterable objects fall into 3 main categories: All sequence types, such as list, str, and tuple Some non-sequence types, such as dict and file Objects that contain an __iter__() or

1. Introduction Flask was born in 2010 and is a lightweight Web application framework written in Python. Flask depends on two libraries. Jinja2, a template engine similar to mako Werkzeug, a Python library that follows the WSGI protocol and implements much of what sits underneath a Web framework, such as the request and response objects.

I have been optimizing a project recently. After mapping out the whole chain, I started improving it step by step and found many points that could be improved. What follows are some thoughts on the development model and the deployment approach. I hope they give you some inspiration. 1. Development Background 1.

1. HTTP Header The HTTP protocol is an application-layer specification built on top of TCP/IP, transmitted as ASCII text. The HTTP specification divides an HTTP request into three parts: the status line, the request headers, and the message body. Something like this: 1 2 3 4 5 <method><request-URL><version> <headers> <entity-body> An HTTP header falls into four categories: general headers, request headers, response headers, and entity headers.