This blog sums up the features, functions and use cases that make Python popular. It is the fuel behind emerging apps with AI + IoT + Microcontrollers = MicroPython, CircuitPython, ArduPy!
In a nutshell, Python is open source, easy to code and understand, syntax is clear and precise, dynamically typed and is used for developing video games, machine learning (IoT) - Robotics projects like robots, automated sensor alarms, night lamp, safety vaults, thief detecting systems, desktop and web applications, data analysis and visualization.
Python’s standard library has modules that cover a range of common programming tasks like (1) I/O data manipulation, (2) network communication, (3) mathematical operations, etc, and does not require third-party packages.
Python includes basic data structures (lists, dictionaries), string manipulation, date and time handling, web scraping, and system interactions for various tasks. Developers import modules from the standard library which works consistently across different operating systems. These are required if the project requires specific domain expertise for complex data analysis, machine learning, or graphical user interfaces. Sometimes, third-party libraries offer better performance than standard library equivalents.
High level languages have readable syntax, made by humans, and are easy to understand and use. Low level languages are machine language, probably in 0,1 format, which can be read by machines, and not by humans. Python's syntax abstracts away many of the complexities of programming, allowing developers to focus on solving problems. It executes on any platform - Windows, Mac, Linux, and Raspberry Pi.
These days a Python Development Company offers web development to data science, automation, game development, networking, desktop applications, and the Internet of Things app development. Its frameworks, such as Django and Flask, streamline web app creation, while libraries like Pandas and TensorFlow facilitate data analysis and machine learning. Python's clear syntax supports automation tasks, and its Pygame library aids in game development. Additionally, it offers tools for network programming (Netmiko, Paramiko, NAPALM, and Nornir which enable efficient network automation by providing functionalities like SSH connections, multi-vendor device interaction, configuration management, and streamlined task orchestration across different network devices) and the creation of user-friendly desktop applications.
Python code is executable across microcontrollers - used for embedded systems as it works across Windows, Mac, Linux, and Raspberry Pi. MicroPython may require platform specific documentation to make the most of its limited RAM and flash memory storage. The pyboard (official MicroPython microcontroller board) comes with a variety of hardware features including microUSB connector, micro SD card slot and I/O pins.
Pygame is used to make video games. Pandas and Matplotlib are used for presenting data in various graphical formats - line charts, bar graphs, scatter plots and histograms, making complex data patterns easier to understand and interpret.
Conclusive
Python has often ranked on GitHub, making developers looking to upskill making Python a top choice for learning. Developers looking to upskill often mention Python as their top choice for learning, making Python development services increasingly sought after for both innovative next-gen projects.
Python desegregates with data science libraries for visualization alongside machine learning modeling. It experiments with different models for quick iteration and optimization. Python can handle large datasets making it suitable for production-level applications (data science projects, smart contract development, distributed ledger development, network monitoring, threat detection, security automation, data collection, device communication, and control systems).
In short,
- A Python script written on Windows server can easily run without modification on a Linux server.
- Python syntax is very easy to understand. A simple hello world program in Python requires just one line: print("Hello, World!").
- Libraries and frameworks speed up the development process.
- Stack Overflow or Python-specific communities on Reddit are being used to post development queries.
- A data scientist uses Python with libraries like NumPy and Matplotlib to analyze and visualize data trends.
- A startup uses Django, a Python web framework, to build a scalable web application quickly. These points highlight Python’s versatility, ease of use, and growing relevance in tech fields like data science and web development.
