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import

The import statement brings code from another module or package into the current file, letting you reuse functions, classes, and variables defined elsewhere - whether from Python's standard library, a third-party package, or your own project files. Python offers several import styles: importing an entire module, importing specific names directly, and renaming imports with 'as' to avoid naming conflicts or shorten long module names.

Syntax

import module\nfrom module import name

Examples

Basic Import

Importing an entire module and accessing its contents with dot notation.

import math

print(math.sqrt(16))   # 4.0
print(math.pi)          # 3.141592653589793

Importing Specific Names

Importing only the specific functions or classes you need, used without the module prefix.

from math import sqrt, pi

print(sqrt(25))  # 5.0
print(pi)         # 3.141592653589793

Import with an Alias

Renaming an import with 'as', commonly used for long module names or established conventions.

import numpy as np
import pandas as pd

# Common in data science code:
# arr = np.array([1, 2, 3])
# df = pd.DataFrame({"a": [1, 2, 3]})

from datetime import datetime as dt
now = dt.now()
print(now)

Importing from Your Own Files

Importing functions or classes defined in another file within your own project.

# In a file called helpers.py:
# def greet(name):
#     return f"Hello, {name}!"

# In your main file:
from helpers import greet

print(greet("John"))

Best practices

  • Use 'import module' when you use many things from that module, and 'from module import x' when you only need a couple of specific names
  • Avoid 'from module import *' - it pollutes your namespace and makes it unclear where a name actually came from
  • Follow standard aliasing conventions when they exist (numpy as np, pandas as pd) so your code is instantly familiar to other Python developers
  • Group imports at the top of the file: standard library imports first, then third-party packages, then your own local modules

Runtime & versions

Python interpreter. Feature availability depends on the language and runtime version used by your project; consult the official reference below.

Python language reference

Specifications & further reading