PySnooper

You can install PySnooper using Pip, Conda, or system package managers depending on your environment.

$ pip install pysnooper

To trace the execution of an entire function, apply the @pysnooper.snoop() decorator to the function definition. This will log which lines are executed and when local variables change to stderr by default.

import pysnooper

@pysnooper.snoop()
def number_to_bits(number):
    if number:
        bits = []
        while number:
            number, remainder = divmod(number, 2)
            bits.insert(0, remainder)
        return bits
    else:
        return [0]

number_to_bits(6)

If you do not want to trace an entire function, you can use pysnooper.snoop() as a context manager with a with block to trace only the relevant section of code.

import pysnooper
import random

def foo():
    lst = []
    for i in range(10):
        lst.append(random.randrange(1, 1000))

    with pysnooper.snoop():
        lower = min(lst)
        upper = max(lst)
        mid = (lower + upper) / 2
        print(lower, mid, upper)

foo()

The @pysnooper.snoop() decorator accepts several arguments to customize the debugging output:

• Output Redirection: Pass a file path as the first argument to redirect logs to a file instead of stderr. You can also pass a stream or a callable.
• watch: A tuple of strings representing expressions (e.g., attributes or dictionary keys) that you want to monitor even if they aren't local variables.
• depth: An integer specifying how many levels of function calls to trace. Setting depth=2 will show snoop lines for functions called by your decorated function.

# Redirect output to a file
@pysnooper.snoop('/my/log/file.log')

# Watch specific expressions
@pysnooper.snoop(watch=('foo.bar', 'self.x["whatever"]'))

# Trace nested function calls
@pysnooper.snoop(depth=2)