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11 tips for speeding up Python programs
11 tips for speeding up Python programs
Python programmers have many options for improving the performance of their apps. Here’s where to start. Credit: Dreamstime
By and large, people use Python because it’s convenient and programmer-friendly, not because it’s fast. The plethora of third-party libraries and the breadth of industry support for Python compensate heavily for its not having the raw performance of Java or C. Speed of development takes precedence over speed of execution.
But in many cases, it doesn’t have to be an either/or proposition. Properly optimised, Python applications can run with surprising speed perhaps not Java or C fast, but fast enough for Web applications, data analysis, management and automation tools, and most other purposes. You might actually forget that you were trading application performance for developer productivity.
6 projects that push Python performance reseller.co.nz - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from reseller.co.nz Daily Mail and Mail on Sunday newspapers.
6 projects that push Python performance
6 projects that push Python performance
Python has never been as speedy as C or Java, but several projects are in the works to get the lead out of the language Credit: Dreamstime
Spiffy and convenient as Python is, most everyone who uses the language knows it’s comparatively creaky orders of magnitude slower than C, Java, or JavaScript for CPU-intensive work. But several projects refuse to ditch all that’s good about Python and instead have decided to boost its performance from the inside out.
If you want to make Python run faster on the same hardware, you have two basic options, each with a drawback: