#425: Memray: The endgame Python memory profiler

1

Introduction

00:00 • 2min

2

Memory Profiling in Python

02:26 • 4min

3

What Is Memray and How Does It Work?

06:24 • 3min

4

The Advantages of Tracing Profilers in Python

09:13 • 2min

5

The Advantages of Profiling for Python

11:30 • 2min

6

The Importance of Tracing Profilers in Python

13:50 • 5min

7

PyCharm: A Powerful Development Environment for Data Scientists and Web Developers

18:22 • 2min

8

How to Care About Unwind

20:31 • 3min

9

Python Memory: A Different Focus Than C Profile

23:06 • 3min

10

The Funny Thing About Memory

25:40 • 4min

11

InfluxDB: A Database for Real-Time Analytics

29:58 • 2min

12

The Python Allocator and the C Library

32:16 • 3min

13

Python Memory and Performance

35:01 • 2min

14

Memory Profiler for Python

37:09 • 6min

15

The Advantages of Memory Over Sampled Profilers

42:49 • 6min

16

How to Use a Flame Graph Report to Analyze Memory Usage

48:47 • 5min

17

Python Memory Leaks

53:27 • 4min

18

The Importance of Temporary Allocations

57:47 • 2min

19

How to Allocate Memory in a List

59:28 • 4min

20

The Benefits of Tracing Profilers

01:03:14 • 2min

21

Does Memory Support Python 3.12 Yet?

01:04:45 • 2min

22

How to Analyze 312 Applications

01:06:22 • 2min

23

Talk Python: How to Stay Productive While Writing Python Code

01:07:53 • 2min