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Python Modules

Vishal

In Python, modules refer to the Python file, which contains Python code like Python statements, classes, functions, variables, etc. A file with Python code is defined with extension.py

For example: In Test.py, where the test is the module name.

In Python, large code is divided into small modules. The benefit of modules is, it provides a way to share reusable functions.

Types of modules

In Python, there are two types of modules.

  1. Built-in Modules
  2. User-defined Modules

Built-in modules

Built-in modules come with default Python installation. One of Python’s most significant advantages is its rich library support that contains lots of built-in modules. Hence, it provides a lot of reusable code.

Some commonly used Python built-in modules are datetime, os, math, sys, random, etc.

User-defined modules

The modules which the user defines or create are called a user-defined module. We can create our own module, which contains classes, functions, variables, etc., as per our requirements.

How to import modules?

In Python, the import statement is used to import the whole module. Also, we can import specific classes and functions from a module.

For example, import module name.

When the interpreter finds an import statement, it imports the module presented in a search path. The module is loaded only once, even we import multiple times.

To import modules in Python, we use the Python import keyword. With the help of the import keyword, both the built-in and user-defined modules are imported. Let’s see an example of importing a math module.

Import multiple modules

If we want to use more than one module, then we can import multiple modules. This is the simplest form of import statement that we already used in the above example.

Syntax of import statement:

import module1[,module2[,.. moduleN]Code language: Python (python)

Example

Output

120
18

Import only specific classes or functions from a module

To import particular classes or functions, we can use the from...import statement. It is an alternate way to import. Using this way, we can import individual attributes and methods directly into the program.

In this way, we are not required to use the module name. See the following example.

Syntax of from...import statement:

from <module_name> import <name(s)>Code language: Python (python)

Example

Output

120

Import with renaming a module

If we want to use the module with a different name, we can use from..import…as statement.

It is also possible to import a particular method and use that method with a different name. It is called aliasing. Afterward, we can use that name in the entire program.

Syntax of from..import ..as keyword:

from <module_name> import <name> as <alternative_name>Code language: Python (python)

Example 1: Import a module by renaming it

Output

16

Example 2: import a method by renaming it

Output

32

Import all names

If we need to import all functions and attributes of a specific module, then instead of writing all function names and attribute names, we can import all using an asterisk *.

Syntax of import * statement:

import *Code language: Python (python)

Example

Output

16.0
120
9.42477796076938
10.0

Create Module

In Python, to create a module, write Python code in the file, and save that file with the.py extension. Here our module is created.

Example

Output

Learn Python with PYnative

Variables in Module

In Python, the module contains Python code like classes, functions, methods, but it also has variables. A variable can list, tuple, dict, etc.

Let’s see this with an example:

First, create a Python module with the name test_module.py and write the below code in that file.

Example

cities_list = ['Mumbai', 'Delhi', 'Bangalore', 'Karnataka', 'Hyderabad']Code language: Python (python)

Now, create a Python file with the name test_file.py, write the below code and import the above module test_module.py in that file. See the following code.

When we execute this test_file.py, the variable of test_module.py is accessible using the dot(.)operator.

Output

Accessing 1st city: Delhi
Accessing All cities : ['Mumbai', 'Delhi', 'Bangalore', 'Karnataka', 'Hyderabad']

Python Module Search Path

When we import any program module, the interpreter first searches for a specified name for a built-in module. If the name is not found, the interpreter searches in a list of directories given by the variable sys.path which initialized from the environment variable PYTHONPATH.

PYTHONPATH have the same syntax as the Unix shell variable PATH, list of the colon(:)-separated directory names. When a PYTHONPATH is not set, or the file is not found there, the search continues in an installation-dependent default path. It is usually /usr/local/lib/python.

Reloading a module

In Python, when we import a module in our program using the import statement, the module is loaded. By default, the module loaded only once, even if we import it multiple times.

Sometimes we update the loaded module with new changes, then an updated version of the module is not available to our program. In that case, we can use the reload() function to reload a module again.

First, create a Python module with the name test_module.py and write the below code in that file.

print("Welcome to PYnative")Code language: Python (python)

Now, create a Python file with the name, test_file.py and write the below code in it and import the module test_module.py. See the following code.

Output

Welcome to PYnative
Welcome to PYnative
Welcome to PYnative
This is test file..

The dir() function

In Python, dir() is a built-in function. This function is used to list all members of the current module. When we use this function with any object (an object can be sequence like list, tuple, set, dict or can be class, function, module, etc. ), it returns properties, attributes, and method.

For Class Objects, it returns a list of names of all the valid attributes and base attributes.

Syntax of dir() function:

dir([object])Code language: Python (python)

Example

Output

['__doc__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh', 'asin',  'asinh', 'atan', 'atan2', 'atanh', 'ceil', 'copysign', 'cos', 'cosh', 'degrees', 'e', 'erf',  'erfc', 'exp', 'expm1', 'fabs', 'factorial', 'floor', 'fmod', 'frexp', 'fsum', 'gamma',  'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf', 'isnan', 'ldexp', 'lgamma', 'log',  'log10', 'log1p', 'log2', 'modf', 'nan', 'pi', 'pow', 'radians', 'remainder', 'sin', 'sinh',  'sqrt', 'tan', 'tanh', 'tau', 'trunc']

Return value from dir()

  • When we use dir() with an object, it returns the list of the object’s attributes.
  • When we use the __dir__() The object’s method, if that object has this method, it returns all attributes of that object. And if that object does not has __dir__() method, it returns all information about that object.
  • If we do not pass an object to dir() it returns a list of currently available functions, methods, properties, attributes, names in the local scope.