Python has evolved amazingly in the developer’s ecosystem. Today, it is one of the most powerful languages used to build a wide variety of applications. There are various reasons to use Python, but the primary reason to use Python is that it is one of the most flexible, robust and simple languages with huge code libraries and frameworks available in the market today.

In this article, we are going to list out some interesting functionalities that you can do with Python. Have a look.

Don't forget to check out our practical agile series of posts.

Interesting things you can do with Python

1: Automating your daily routine tasks

Python can be used to automate the routine, tedious tasks that consume your time on a daily basis. With Python, you can make your everyday life easier.

Tasks that can be automated with Python:

  • Searching files in the database or text in files
  • Updating, creating, and renaming the folders and files according to your requirements.
  • Searching the web and creating dictionaries
  • Sending message notifications and reminder emails
  • Tracking and sorting invoices

    Automating these tasks only requires you to write a few lines of code. Python is a simple and easy language that doesn’t require you to do a lot of coding.

2. Automatically detects what’s in the image

Detecting faces from a huge loop of images comes under Artificial Intelligence (AI) and machine learning (ML) technology. Before delving into how Python automatically detects the image, let’s understand why Python is popular among AI and ML scientists.

Python is a popular language for artificial intelligence and machine learning. AI and ML areas involve the gathering, analyzing, and processing of a huge amount of data on a daily basis. Most AI and ML professionals look for a language that can be easy to learn and understand, as any complex programming language can increase the learning curve for AI and ML scientists, leading to a delay in project development. So, they mostly prefer the Python language. Python syntax resembles the everyday English language, meaning AI and ML scientists can work with complex systems easily.

Other features that make Python a perfect choice for AI and ML projects are:

  • It offers flexibility
  • It has a huge community support (a bunch of resources and documentation are available that enable you to build amazing products)
  • It is platform-independent, meaning it can run on any platform, including Windows, Linus, macOS, Unix and many more.

How can you make your device recognize images using Python?

Python offers you the best and open-source face recognition library for free, known as face-recognition 1.2.3. You can use this library in your Python script and make your device recognize faces in images. With this, you can easily find the pictures of a particular person from a huge number of images. All this coding with Python can be done in just a few hours. Python makes the implementation of AI and ML easy.

Example to show how easy it is to detect a face in photographs by using the Python library

Code snippet: 

import face_recognition 1.2.3
image = face_recognition.load_image_file("your_file.jpg")
face_locations = face_recognition.face_locations(image)

3. Data analysis, manipulation and visualization

It is said that humans can perceive things better looking at visual data. Data scientists have the capability to gather a huge amount of unstructured data to analyze and synthesize it into structured visual content. This helps the companies to get actionable insights into their businesses.

Data scientists using Python libraries to make visualization charts

With Python, it is easy for data scientists to create visualization of their data. Python contains powerful libraries for visualization, including:

  • Matplotlib: It is an amazing Python library embedded with a full 2D support but limited 3-D graphic support. It enables data scientists to create data bars, charts, plots, power spectra, histograms, etc., within a few lines of code.
  • Seaborn: It is a Python library that can be used to create informative and visually appealing statistical graphical data. It provides various features including, color palettes, built-in themes, tools and functions that enable data scientists to extract, analyze, synthesize and format the complex data into simple and easily understandable visualizations.

Panda: Python library for data manipulation and analysis

Panda is the most powerful and popular library for data manipulation and data analysis. Its source code is highly optimized, providing accurate results to data scientists while performing data manipulation and analysis.

Example to show how easy it is to create data visualization using Python

Let's consider the following data set (created in Excel) to create a visualization in the form of the line chart:

how how easy it is to create data visualization using Python

To convert this data set into a line chart, data scientists need to:

  • Import Python libraries (Matplotlib and Panda)
  • Then, they have to assign the data integers, variables, parameters, etc., along with afew lines of Python code.
Have a look at the code snippet:
  1. Importing data with Python libraries:
import matplotlib.pyplot as plt
import pandas as pd
df=pd.read_excel("E:/First.xlsx", "Sheet1")

Note: In the code snippet, E:/First.xlsx, “sheet1” is the path of the file name ‘First.xlsx’, which is created in sheet1 of the excel file First.xlsx. This file is located in the ‘E drive’ of the computer.

2. Defining parameters for Line chart:

var = df.groupby('BMI').Sales.sum()
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
ax1.set_xlabel('BMI')
ax1.set_ylabel('Sum of Sales')
ax1.set_title("BMI wise Sum of Sales")
var.plot(kind='line')

Here is the output:

Here is the output

(image source: analyticsvidhya.com)

4. Create games with Python

With Python, you can create a variety of adventure games, arcade games, and puzzle games. You can develop classics games on Python including ping-pong, tic-tac-toe, hangman and more. Pygame is a most popular Python library for game development. Pygame includes various modules with several functionalities for playing sound, drawing graphics, handling mouse input and more.

Some key points about Pygame (Python’s library)

  • It is an open-source library that is available for free to build games in Python.
  • It is highly portable and can be run on any operating system, including Windows, macOS, etc.
  • It is one of the most powerful Python libraries that contains almost everything you need to get started with building your own games.
  • It contains a wide range of modules that can be used to add interactive features or functionalities to your existing application.

We know that every language has certain advantages and limitations. Now the question is: is Python good enough for developing every type of game?

Is Python suitable for developing every type of game applications?

There are many programming languages, including Python, Java, etc., that are suitable for developing game applications. However, Python is not good for developing performance-intensive games, meaning the games that require extremely fast action. Also, Python can be used to build powerful 2D games, but building 3D games in Python will not give the expected high performance and output. For building 3D games, there are other programming languages available on the market, like: C, C#, C++, Java, etc.

However, game developers can use Python for building tools to simplify routine tasks related to games, such as level designing. Python is good for number crunching and string manipulations, it also has an extensive library. This, in turn, makes it suitable for building tool kits for games in order to automate repetitive tasks.

5. Building robotics applications

According to the Global Market Insights report, “The worldwide industrial robotics market size is set to exceed $80 billion by 2024.” And, a huge portion of the robotics growth is contributed by artificial intelligence. Artificial intelligence is a field of robotics that is used to control robots. We have already discussed why Python is the most popular programming language in the field of AI. Now, let's understand why Python is the most suitable language for robotics:

Why Python for robotics?

  • Robotics operating systems are compatible with Python.
  • It has a ton of computational libraries that are required for robotics.
  • It is a simple language that even non-programmers (with deep knowledge in robotics technology) can learn, understand and use effectively while building robotics applications.

Python and Raspberry Pi

Python programming language is used to build Raspberry Pi. Raspberry Pi is a small-sized computer that can be plugged into TVs or computer monitors. You can also use Raspberry Pi to build and control robots.

Some key points about Raspberry Pi

  • Its latest model is Raspberry Pi 4 Model B.
  • It comes with a Raspberry official beginners’ guide, with which you can learn how to set up, configure and use the Raspberry Pi computer.

Need help building amazing applications, partner with a python development company to help? Contact us today! At Zibtek, we use cutting edge technologies to help our customers maintain a competitive edge in this digital marketplace.