Python is one of the best coding languages to comprehend to boost your career. Many of the biggest websites in the world use Python, and there are ample of jobs you can get with Python skills. All new Python students should know these points before getting started.
Python is an interpreted language
Learn the distinction between front-end and back-end
In distinction to the front-end code, the back-end code is what goes on behind the scenes. It’s what you don’t see. Back-end code tells websites what to do, and it also questions data from the database in order to display it to the website user. A few examples of back-end coding languages are Python, Ruby, PHP, C, and Java.
Python is object-oriented, but not exclusively
If you come from an object-oriented background, particularly Java where everything is an object, the hello.py, example may look a little strange. The single-line script not only doesn’t define any classes, but it isn’t even inside of a method declaration.
Python supports object-oriented programming, but you aren’t locked into it. You can add functions directly to a script when there isn’t a necessity for the overhead and complication of defining a class.
Understand what you can do with Python
Python is considerable for building the back-end of websites, data analysis, accessing API data, machine learning, and automating repetitive tasks.
Instagram uses Python’s Django framework to manage their CMS, while Instacart uses Python for need forecasting to run projections for the upcoming weeks.
Whitespace matters in Python
It may appear odd to highlight something as seemingly trivial as whitespace, but it's such a crucial aspect of Python's syntax that it warrants mentioning.
Python uses incision to indicate scope, freeing it from the arguments about curly brace placement that other languages encounter. Generally speaking, a code block is defined by statements that share the same indentation level.
Python 2 vs. Python 3 — Know the difference
Python 2 is still used by numerous companies for one reason: they created their sites with Python 2 years ago, and they haven’t upgraded to Python 3.
Python 3 was a big upgrade to the language with substantial changes that make transitioning a lot of work, so many of corporations built on Python 2 chose to stick with what works. It was either that or rebuild the whole site.
New websites are almost always built with Python 3. Over the next few years, once unwilling companies stuck on Python 2 will be making the switch to Python 3. Because everyone is moving to Python 3, we approve prioritizing it if you’re learning Python for the first time.
Use virtual environments to prevent dependency conflicts
In many cases, you'll already have a Python interpreter installed on your system. For development, however, you'll likely want to create a virtual environment, which is effectively a copy of the interpreter that is scoped specifically to that environment.
The reason for using virtual environments largely revolves around installing dependencies. Without using a virtual environment, any dependencies that are established for your project (such as the Django, Flask, pandas, or numpy libraries) are installed to the global interpreter. Having such dependencies installed system-wide is a risk for an abundance of reasons, encompassing1 version compatibility issues.
Instead, creating a virtual environment for your project provides an individually scoped interpreter to use. Any dependencies installed to the virtual environment only exist for that environment, allowing you to easily formulate on multiple projects without fear of system-wide implications or conflicts.
There are a number of ways to manage Python virtual environments, including the built-in venv command, as well as the (arguably more user-friendly) utility packages pyenv and virtualenv
You can be a Python developer without knowing “everything” about Python
Here’s something a lot of non-developers might not know: to “know” a language, you don’t have to learn the entire language. In fact, virtually no developers will know the fullness of a programming language. You only have to understand the section of the language that you need to do what you’re trying to accomplish.
So if you just want to build a data scraper in Python, you can learn the foundations of Python and the data scraping library BeautifulSoup, but you don’t need to know everything.