How PySnooper Can Replace Print Statements for Smarter Python Debugging

Limitations of print‑based debugging

Using print statements to trace program execution requires inserting many statements, manually removing them after debugging, and clutters the source code. This approach is error‑prone and inefficient, especially when many variables or code paths need inspection.

PySnooper overview

PySnooper is an open‑source Python library that provides a decorator @pysnooper.snoop(). When applied to a function, it automatically logs each executed line, timestamps, and the values of local variables, eliminating the need for manual print statements.

Traditional print‑debug example

def removeDuplicates(nums):
    """
    :type nums: List[int]
    :rtype: int
    """
    flag = 0
    i = 1
    while i < len(nums):
        if nums[i] == nums[i - 1]:
            flag += 1
            i += 1
            print("flag=", flag)
            print("i=", i)
            if flag >= 2:
                del nums[i - 1]
                i -= 1
                print("i=", i)
                print("nums=", nums)
        else:
            print("else")
            i += 1
            flag = 0
    return len(nums)

nums = [1, 1, 1, 2]
print(removeDuplicates(nums))

This code prints intermediate values to the console, but the output is plain text and the statements must be removed after debugging.

Using PySnooper

import pysnooper
@pysnooper.snoop()
def removeDuplicates(nums):
    flag = 0
    i = 1
    while i < len(nums):
        if nums[i] == nums[i - 1]:
            flag += 1
            i += 1
            if flag >= 2:
                del nums[i - 1]
                i -= 1
        else:
            i += 1
            flag = 0
    return len(nums)

nums = [1, 1, 1, 2]
print(removeDuplicates(nums))

Running this version produces a colored log where:

Red frames highlight the line currently being executed.

Blue, green, and yellow frames show the values of variables at that point.

Redirecting output to a file

If writing to standard error is inconvenient, the log can be saved to a file:

import pysnooper
@pysnooper.snoop('file.log')
def removeDuplicates(nums):
    # function body identical to the example above
    ...

The generated file.log contains the same detailed line‑by‑line execution information.

Installation

pip install pysnooper

If the default PyPI source is slow, a mirror can be used:

pip install pysnooper -i https://pypi.douban.com/simple

Repository

Source code, documentation, and additional examples are available at https://github.com/cool-RR/PySnooper.