5 Tasks To Automate With Python

Python has incredibly evolved over the years in the developer’s ecosystem. Developers today find Python as one of the most sturdy and flexible open-source languages to build a wide range of applications.

You can use Python in all layers of the application stack across the technology industry. Right from data manipulation processing real-time data feeds to serverless applications processing commands from your voice assistant to being a robust, general-purpose language for traditional applications.

Developers prefer Python for various reasons, including flexibility, robustness, and simplicity. Moreover, Python has immense code libraries and frameworks available in the market today. Thus, Python stands tall as an excellent tool because of its extensive library of plugins and breadth of capabilities.

With Python, one can build from simple maintenance scripts to complex machine learning applications. Python has always been Google’s favorite as Python is one of its main server-side languages. Instagram prefers Python for its simplicity, whereas Spotify likes the language for its ease of use.

There are tonnes of things you can automate with Python. Let me see some of the most exciting functionalities that you can achieve with this developer-friendly language.

1. Automate Your Repetitive Tasks

You can rely on Python to automate the stereotypical, monotonous, and repetitive daily jobs that consume most of your time. Thus, you can concentrate on other crucial tasks that are essential for your business. With Python, you can improve the productivity of you and your workforce by automating mundane tasks.

Here are a few of the tasks that you can automate with Python:

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

With very few lines of code, Python allows you to automate the above-said tasks. That is why Python is popularly known as a developer-friendly language, as it does not demand you to do a lot of coding.

2. Automatic Image Detection

Recognizing and detecting faces from a huge loop of images comes under Artificial Intelligence(AI) and Machine Learning (ML) technology. Before learning how Python automatically detects the visuals, let us understand why AI and ML scientists prefer Python.

Python is gaining its popularity in Artificial Intelligence (AI) and Machine Learning (ML) industry. Both AI and ML involve gathering, analyzing, and processing massive data regularly.

AI and ML professionals prefer Python language as it is easy to learn, understand and execute. Leveraging other complex programming languages will only increase their learning curve, leading to a delay in the project development.

As Python syntax resembles our everyday English language, it is easy for AI and ML scientists to work with complex systems effortlessly.

Python is a perfect choice for AI and ML projects because,

• It is flexible.
• It has massive community support, including numerous resources and documentation that can help you build excellent products.
• It is platform-independent. That means it can run on any platform like Windows, Linus, macOS, Unix, etc.

Python can help your device to recognize images. learn how:

Python provides you the best and open-source face recognition library. It is known as face-recognition 1.2.3. You can leverage this library in your Python script and make your device recognize faces in images.

Coding is made easy with Python, making it ideal for AI and ML implementation.

3. Building Games With Python

Pygame is the most reliable Python library for game development. Using that, you can create a wide variety of adventure games, arcade games, and puzzle games. You can also develop classic games on Python, including ping-pong, tic-tac-toe, hangman, and more.

Pygame includes several modules with numerous functionalities to play sound, drawing graphics, handling mouse input and more.

What is Pygame(Python’s library)?

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

Game developers can use Python for constructing tools to simplify routine tasks related to games, like level designing. Python is ideal for number crunching and string manipulations. Moreover, Python has an extensive library. That, in turn, makes it suitable for building tool kits for games, automating repetitive tasks.

4. Constructing Robotic Applications

A recent report from Global Market Insights reveals that the worldwide industrial robotics market size will exceed $80 billion by 2024. Artificial Intelligence (AI) contributes to robotics growth to a great extent.

Artificial Intelligence (AI) is a branch of robotics that scientists use to control robots. As we have seen earlier, Python is a well-known programming language in the AI field. And, now, let us understand why Python is an ideal language for robotics.

How Python supports Robotics?

• Robotics operating systems are compatible with Python.
• It is a simple language that enables even non-programmers(scientists with deep knowledge in robotics technology) to learn, understand and effectively use it to build robotics applications.
• It has vast computational libraries that can contribute to the robotics field.

Python and Raspberry Pi:

Raspberry Pi is a small-sized computer that you can plug into TVs or computer monitors. Python is the programming language behind the construction of Raspberry Pi. One can use Raspberry Pi to build and control robots.

Some Key Points about Raspberry Pi:

• The recent model is Raspberry Pi 4 Model B.
• It comes with a Raspberry official beginner’s guide. With the guide, users can learn how to set up, configure and use the Raspberry Pi computer.

5. Data Analysis, Manipulation, and Visualization

In general, humans find it easy to interpret visuals rather than text posts. Thus, businesses invest time and money in creating visual content for their brands for faster reach among the customers.

Data scientists gather a large amount of unstructured data to analyze and synthesize it into structured visual content. Python libraries help these data scientists to make visualization charts effortlessly.

Python has some robust libraries for visualization like:

Matplotlib: It is an excellent Python library embedded with full 2D support but limited 3D graphic support. It allows data scientists to create data bars, charts, plots, power spectra, histograms, etc, within a few lines of code.

Seaborn: It is an outstanding Python library that one can leverage to create educative, engaging, and visually appealing statistical or graphical data. It comes with several features, including color palettes, built-in themes, tools, and functions that enable data scientists to extract, analyze, synthesize and format complex data into simplified and easily interpretable visualizations.

Python has the most popular library for data manipulation and data analysis, namely Panda.

Panda: Its highly optimized source code provides accurate results to data scientists while performing data manipulation and analysis.

Final Thoughts

Python is a popular, advanced, and interactive tool that you can leverage to automate tasks. Python is highly readable and often uses English keywords. Plus, it has fewer syntactic constructions than the other scripting languages. So, it is easy for anyone to get started with Python, even for beginners.

Developers worldwide prefer Python for their web development, game development, data visualization, and machine learning projects. Hopefully, this blog would have given you an idea of creating exciting Python projects while automating tedious processes.