Python 3 Performance

سرفصل های دوره

Python developers love Python's high productivity. Unfortunately, many Python applications suffer from slow performance. This course is about concrete approaches for improving the performance of your Python applications.

1. Course Overview

1. Course Overview

2. Measuring Performance

1. Understanding Performance

2. Strategy to Improve Performance

3. Basic Ways to Measure Performance

4. Why Profile

5. More Profilers

6. Visualizing Profiling Data

3. Using the Right Data Structures

1. Which Data Structure Is Faster

2. Comparing Lists and Arrays

3. Comparing Sets and Tuples

4. Comparing Queues and Deques

5. Using Dictionaries

6. Comparing Dataclass, Dictionary, and NamedTuple

4. Optimizing Python Code

1. Caching

2. For vs. List Comprehension

3. Efficient Iterations with Generators

4. Fast Concatenation of Strings

5. Permission or Forgiveness

6. Faster Functions

7. Optimizing Numerical Calculations

8. Interpreter-based Optimizations

9. Risky Optimizations

5. Using More Threads

1. What Are Threads

2. Challenges of Working with Threads

3. When to Use Multithreading

6. Using Asynchronous Code

1. Asynchronous Code

2. Challenges of Working with asyncio

3. When to Use asyncio

7. Using More Processes

1. Process-based Parallelism

2. Processes Communication

3. When to Use More Processes

4. Scaling from One to More Machines

5. Summary

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تولید کننده: PluralSight