Skip to main content

Python Importing Modules

In Python, importing modules is a fundamental way to extend the functionality of your code by incorporating libraries and modules written by others. Here's a guide on how to import modules in Python:

Basic Import

To import a module, you use the import statement followed by the module name.

import math

Using Imported Functions

After importing, you can use the functions and variables defined in the module.

import math result = math.sqrt(16) # Use the sqrt function from the math module print(result) # Output: 4.0


Importing Specific Items

You can import specific functions, classes, or variables from a module using the from ... import ... syntax.

from math import sqrt, pi result = sqrt(16) print(result) # Output: 4.0 print(pi) # Output: 3.141592653589793



Renaming Modules

To avoid name conflicts or for convenience, you can rename modules using the as keyword.

import math as m result = m.sqrt(16) print(result) # Output: 4.0


Importing All Items

To import all functions and variables from a module, use the from ... import * syntax. However, this is generally discouraged because it can lead to unclear code and potential name conflicts.

from math import * result = sqrt(16) print(result) # Output: 4.0


Importing Submodules

Some modules have submodules which you can import separately.

import os.path path = os.path.join("folder", "file.txt") print(path) # Output: folder/file.txt


Checking Installed Modules

To see a list of installed modules, you can use the following:

help("modules")


Installing Modules

If you need to install a third-party module, you can use pip (Python's package installer).

pip install requests


Importing Installed Modules

Once installed, you can import third-party modules just like built-in ones.

import requests response = requests.get("https://www.example.com") print(response.text)


-----------

-----------

By understanding these basics, you can effectively manage and utilize modules in your Python projects.


Comments

Popular posts from this blog

Power BI tenant settings and admin portal

As of my last update, Power BI offers a dedicated admin portal for managing settings and configurations at the tenant level. Here's an overview of Power BI tenant settings and the admin portal: 1. Power BI Admin Portal: Access : The Power BI admin portal is accessible to users with admin privileges in the Power BI service. URL : You can access the admin portal at https://app.powerbi.com/admin-portal . 2. Tenant Settings: General Settings : Configure general settings such as tenant name, regional settings, and language settings. Tenant Administration : Manage user licenses, permissions, and access rights for Power BI within the organization. Usage Metrics : View usage metrics and reports to understand how Power BI is being used across the organization. Service Health : Monitor the health status of the Power BI service and receive notifications about service incidents and outages. Audit Logs : Access audit logs to track user activities, access requests, and administrative actions wit...

Performance Optimization

Performance optimization in SQL is crucial for ensuring that your database queries run efficiently, especially as the size and complexity of your data grow. Here are several strategies and techniques to optimize SQL performance: Indexing Create Indexes : Primary Key and Unique Indexes : These are automatically indexed. Ensure that your tables have primary keys and unique constraints where applicable. Foreign Keys : Index foreign key columns to speed up join operations. Composite Indexes : Use these when queries filter on multiple columns. The order of columns in the index should match the order in the query conditions. Avoid Over-Indexing:  Too many indexes can slow down write operations (INSERT, UPDATE, DELETE). Only index columns that are frequently used in WHERE clauses, JOIN conditions, and as sorting keys. Query Optimization Use SELECT Statements Efficiently : SELECT Only Necessary Columns : Avoid using SELECT * ; specify only ...

DAX UPPER Function

The DAX UPPER function in Power BI is used to convert all characters in a text string to uppercase. This function is useful for standardizing text data, ensuring consistency in text values, and performing case-insensitive comparisons. Syntax: UPPER(<text>) <text>: The text string that you want to convert to uppercase. Purpose: The UPPER function helps ensure that text data is consistently formatted in uppercase. This can be essential for tasks like data cleaning, preparing text for comparisons, and ensuring uniformity in text-based fields. E xample: Suppose you have a table named "Customers" with a column "Name" that contains names in mixed case. You want to create a new column that shows all names in uppercase. UppercaseName = UPPER(Customers[Name]) Example Scenario: Assume you have the following "Customers" table: You can use the UPPER function as follows: Using the UPPER function, you can convert all names to uppercase: UppercaseName = ...