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 optimized, Python applications can run with surprising speed—perhaps not as fast as Java or C, but fast enough for web applications, data analysis, management and automation tools, and most other purposes. With the right optimizations, you might not even notice the tradeoff between application performance and developer productivity.
