Debug Python Code Without Print Statements Using PySnooper

When Python code does not behave as expected, developers usually resort to a full‑featured debugger or sprinkle print statements to see which lines run and what local variables contain. The article introduces a minimalist alternative called PySnooper , which works by adding a single decorator to any function.

To start, import the library with import pysnooper. Adding @pysnooper.snoop() above a function definition automatically creates a detailed execution log without any additional setup. The log records each line number, timestamps, variable assignments, and the values before and after each statement.

The author provides a concrete example: a function number_to_bits(number) that converts an integer to a list of binary bits. By decorating the function with @pysnooper.snoop() and calling number_to_bits(6), the generated log shows the initial variable number = 6, the creation of bits = [], each iteration of the while loop, the divmod operation, and how bits evolves to [1, 1, 0]. The full log output is reproduced verbatim in a ... block, illustrating the exact format PySnooper uses.

Beyond the basic usage, the article lists several useful features. By passing a file path as the first argument, e.g. @pysnooper.snoop('/my/log/file.log'), the log can be written to a specific file instead of stderr. The variables parameter lets users monitor non‑local variables, such as foo.bar or self.whatever. The depth argument (e.g., depth=2) controls how many levels of nested function calls are displayed in the log.

An image of the log output is included to visualise the line‑by‑line trace. The article concludes that PySnooper provides a quick, zero‑configuration way to gain insight into Python code execution, making it especially handy for small scripts or when a full debugger feels heavyweight.