Python is a well-known programming language in many fields, including building websites, technical computing, machine learning and data analysis. However, Python does have faults that may prevent it from operating as intended. Defects must be found and fixed for Python code to function at its best. This essay offers a comparative examination of several Python code bug-finding methods. This study aims to assess these approaches' efficacy and efficiency in locating defects at the level of specific code lines. The relevance of bug identification and its effect on Python programs are briefly discussed in the first section of the article. Then it examines several methods for finding bugs, like testing procedures, static analysis and dynamic analysis. There is a detailed discussion of each approach's benefits, constraints and use cases.