Important Modules in Python

Beyond the core language itself, a handful of built-in modules come up again and again in real-world Python programming. Getting comfortable with these early saves significant time later.

Frequently Used Modules

• os - interacting with the operating system, such as file paths and directories
• datetime - working with dates, times, and time differences
• random - generating random numbers and making random selections
• json - reading and writing data in JSON format, common in web APIs
• re - working with regular expressions for advanced text pattern matching
• math - mathematical functions like square roots, logarithms, and trigonometry

import os
import json

print(os.getcwd())   # prints the current working directory

data = {"name": "Abhay", "course": "Data Science"}
json_text = json.dumps(data)
print(json_text)   # {"name": "Abhay", "course": "Data Science"}

Why These Matter for Data Science

Even before reaching specialized libraries like Pandas and NumPy, these standard modules handle essential groundwork - reading file paths, parsing timestamps, working with API responses in JSON, and cleaning messy text using regular expressions.

Coming Up Next

To close out this module, the final topic takes a closer look at the sys module - used for interacting directly with the Python interpreter itself.