Python Programming Skills

How do I improve my python Programming skills as beginner?

Do you want to improve the python programming skill? Python is an amazingly multipurpose programming language. You can use it to build websites, machine learning algorithms, and mobile apps.

If you are a beginner and you want to improve your Python programming skills. Then read this article carefully, it will be very helpful for you. But one thing is for sure that you will have to practice a lot to become a good python programmer.  Programming is lots of fun and extraordinarily useful. It allows you to be creative and also opens up a wide range of new careers for you.

What is Python Programming Language?

Python is a commonly interpreted, interactive, high-level and object-oriented programming language. It was built by Guido van Rossum during 1985-1990. Like Perl, Python source code is also available under a GNU General Public License (GPL) and maintains similar properties to PERL.

Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It has a large and comprehensive standard library. The syntax of the language is clean and length of the code is relatively short.

Python supports the use of modules and packages, which mean that programs can be designed in a modular style and code, can be reused across a variety of projects. Once you’ve developed a module or package you need, it can be scaled for use in other projects, and it’s easy to import or export these modules.

Follow these effective tips; it will help you to improve your python programming skills.

Analyze the problem clearly

Firstly you need to analyze your problem very clearly. You should think twice about how to solve that problem. Surely, you find the solution about that problem.

Collect complete requirements

You should take the time to write down what goals the end product needs to achieve. It will save your time to find the solution.

Create a  plan or diagram

•    For a small project, you need to create a basic flowchart or a simple plan.

•    For larger projects, it helps to break the job into modules, and to consider the following:

•    What task each module must perform

•    How data gets passed between modules

•    How the data will be used within each module

•    Although gathering and planning requirements can be tedious and much less fun than diving straight into coding, it is even more tedious to spend hours debugging. Take the time to design the flow and structure of your program correctly up front, and you may even spot more efficient ways of accomplishing your goals before you write the first line of code!

Comment your code liberally

If you think that your code might need explanation, comment it. Each function should be preceded by 1-2 lines describing the arguments and what it returns. Comments should tell you why you are using these lines. Remember to update the comments when you update your code!

Use consistent naming conventions for variables

It will help you keep track of each type of variable, and the purpose of the variable. This means more typing than simply x = a + b * c, but it will make your code much easier to debug and maintain. One popular convention is Hungarian notation, where the variable name is prefixed with its type. For example, for integer variables you might use intRowCounter; strings might use strUserName. It doesn’t matter what your naming convention is, but be sure that it is consistent and that your variable names are descriptive.

Organize your code

Use visual structures to indicate code structure. For example, indent a code block that sits within a conditional (if, else,…) or a loop (for, while,…) Also try putting spaces between a variable name and an operator such as addition, subtraction, multiplication, division, and even the equal sign (myVariable = 2 + 2). As well as making the code more visually elegant, it makes it much easier to see the program flow at a glance.

Test everything

Start by testing each module on its own, using inputs and values that you would typically expect. Then try inputs that are possible but less common. This will flush out any hidden bugs. There is an art to testing, and you will gradually build up your skills with practice. Write your tests to include the following cases:

•    Extremes: Zero and beyond the expected maximum for positive numeric values, empty string for text values, and null for every parameter.

•    Meaningless values. Even if you don’t believe your end user would input gibberish, test your software against it anyway.

•    Incorrect values. Use zero for a value that will be used in division, or a negative number when positive is expected or when a square root will be calculated. Something that is not a number when the input type is a string, and it will be parsed for a numeric value.

Practice

Practice is the best option for learning the Python programming skill. There’s always something new to learn, and – perhaps more importantly – always something old to relearn.

Be prepared for change

Sometimes, you need to change in your coding. You should be prepared for your any kind of modification. Sometimes the changes take less time. But another side some change need the more time. So, always you should ready for any changes.

Start simple and work towards complexity.

When programming something complex, it helps to get the simpler building blocks in place and working properly first. For example, let’s say you want to create an evolving shape on the screen that follows the mouse direction and changes shape depending on mouse speed.

•    Start by displaying a square and getting it to follow the mouse; i.e., solve movement tracking alone, first.

•    Next, make the size of the square relate to mouse speed; i.e., solve speed-to-shape tracking on its own.

•    Finally, create the actual shapes you want to work with and put the three components together.

•    This approach naturally lends itself to modular code writing, where each component is in its own self-contained block. This is very useful for code reuse (e.g. you want to just use the mouse tracking in a new project), and makes for much easier debugging and maintenance.

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