“10 Python tips for beginners” will act as a soft landing for beginners to the most highly-demanded programming languages out there. See our Introduction to Python post for more understanding of python programming language. This tutorial discusses 10 helpful Python tips and tricks every beginner should know. If you want to make your Python programming process more efficient, don’t miss these tips/tricks!
Python Tip 1: Using list comprehension for more efficient coding
List comprehension in Python is a quick way of creating new lists from existing ones. It provides a shorter syntax to make new lists from existing lists and their values.
List comprehension syntax:
list2 = [expression for item in iterable if condition == True]The resultant value will be a new list. The old list will remain unchanged.
For instance, we have a list of fruit names, and you want to create a new list that will hold only the fruits with the letter “a” in their name.
Without list comprehension, we’ll have to write a for statement with a conditional test inside:
fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
newlist = []
for x in fruits:
if "a" in x:
newlist.append(x)
print(newlist)
With list comprehension, we can accomplish all of the above with one line of code:
newlist = [x for x in fruits if "a" in x]List comprehension is an intelligent way to define and create lists based on existing lists, and it is more compact and faster than normal functions and loops for making lists. However, we should avoid writing long list comprehensions in one line to ensure user-friendly code.
Remember, every list comprehension can be written in a for-loop, but not every for-loop can be written as a list comprehension.
Python Tip 2: Utilizing the power of lambda functions
Lambda Functions in Python are anonymous, meaning the function is without a name. As we already know, the def keyword defines a standard Python function. Similarly, the lambda keyword defines an anonymous Python function.
Note:
- These functions can contain any amount of arguments but just one expression, which is evaluated and returned.
- It is free to use lambda functions wherever functions are required.
- You must know that lambda functions are restricted to a single expression.
Lambda Syntax:
lambda arguments : expressionThe code below will show a lambda example that takes any number as an argument, then adds 5 to x and returns the result:
add_five = lambda x : x + 5
print(add_five(5))Result:
10The following example multiplies argument x with argument y and return the result:
mult = lambda x, y : x * y
print(mult(5,10))Result:
50We use lambda functions when we require an anonymous function for a short time.
Python Tip 3: Using the ‘enumerate’ function for iterating over lists
enumerate() is a built-in function in Python that adds a counter to an iterable object and returns it as an enumerated object. This enumerated object can then be used directly for loops or converted into a list of tuples using the list() function.
Syntax:
enumerate(iterable, start)Parameters:
- Iterable: any object that can be iterated trough
- Start: the index value from which the counter is to start, and the default value is 0
Example:
newlist = ["eat", "sleep", "repeat"]
obj = enumerate(newlist)
print (obj)Result:
[(0, 'eat'), (1, 'sleep'), (2, 'repeat')]Python Tip 4: Using the ‘zip’ function for iterating over multiple lists
The zip() function takes multiple iterable object arguments and returns a zip object containing mapped values from all the objects. It maps multiple similar containers to other containers with a matching index to be used as a single entity.
Syntax of zip() function:
name = ["Fred", "Miriam", "Joy", "Mike"]
no = [ 4, 1, 3, 2 ]
mapped = zip(name, no)
print(list(mapped))Result:
[('Fred', 4), ('Miriam', 1), ('Joy', 3), ('Mike', 2)]In the above code snippet, “Fred” has an index of 0, so they are mapped; the same goes for the others.
The zip() function is used to quickly and consistently manipulate and perform operations on multiple iterable.
Python Tip 5: Using the ‘ternary operator’ for writing concise if-else statements
Ternary operators are conditional statements in Python that are on a single line of code. The name ternary suggests that this operator is made up of three operands.
The ternary operator can be considered a shortened, one-line version of the if-else statement to test a condition.
Syntax:
value_if_true if condition else value_if_falseExample:
a, b = 9, 21
min = a if a < b else b
print(min)The above example prints the lesser variable, which contains the lowest of a and b.
The ternary operator is widely used as it is helpful to make your code compact and preserve all the necessary conditions.
Python Tip 6: Using the ‘try-except’ block to handle exceptions
The try-except statement can handle errors or exceptions, as we call them. Exceptions are errors that arise during the execution of a program. Python will not tell you about errors like syntax errors. Instead, it will unexpectedly halt the execution.
An unexpected exit is terrible for both the end user and the developer.
Instead of an emergency halt, you can use a try-except statement to deal with the problem correctly. An emergency halt will occur if you do not properly handle exceptions.
Syntax:
try:
<do something>
except exception:
<handle the error>The try block lets you test a code block for errors.
The except block lets you handle any resulting error.
The else block allows you to execute code when there is no error.
The finally block allows you to run code, regardless of the result of the try and except blocks.
Example:
try:
print(x)
except NameError:
print("Variable x is not defined")The error here is the “NameError” which is why we have it after the except keyword.
In a nutshell, try-except blocks handle expected but sometimes unavoidable errors in your code.
We will create more in-depth discussions on this topic and the others in this post in our future content.
Python Tip 7: Using the ‘with’ statement to work with files and resources.
In Python, the “with” statement is an exception handler like a try-finally block with a straightforward shorthand. More importantly, it guarantees the closing of resources right after using them. A typical example of utilizing the with statement is reading or writing to a file. A function or class that supports the “with” is called a context manager. A context manager allows you to open and close resources right when you want to. For instance, the open() function is a context manager. When called, the open() function using the “with” statement, the file closes after processing the file.
The with statement replaces the commonly used try-finally error-handling statements. A typical instance of using the with statement is opening a file.
Example 1: Opening a file using try-finally
file = open('file_path', 'w')
file.write('hello world !')
file.close()
file = open('file_path', 'w')
try:
file.write('hello world')
finally:
file.close()
Example 2: Opening a file using with
with open('file_path', 'w') as file:
file.write('hello world !') Unlike the try-finally, the “with” statement makes the code cleaner and more readable. It streamlines the management of shared resources like file streams.
Python Tip 8: Use Virtual Environments
A Virtual Environment is a python environment that is isolated and explicitly created for a project without interfering with other projects. It is a tool that allows numerous installations of Python, one for each project.
You can create and manage virtual environments using tools like Anaconda (conda environments), virtualenv, pipenv.
We will discuss this extensively in a dedicated post. For now, read more here.
Python Tip 9: Using of IDEs
In theory, you can utilize any text editor for writing Python codes. However, your productivity can be increased if you use a suitable IDE for your projects. Therefore, you should know at least one IDE of your choice. It’s not essential to work with numerous IDEs since many modern IDEs (e.g., VSC, PyCharm) are well-developed to ease our coding work.
With these IDEs, you can explore their supportive tools, like plugins, which provide additional features on top of the standard features. For example, you can incorporate version-control tools (e.g., git) into your projects. For another instance, using plugins or built-ins, your IDEs can help inspect whether your code observes the PEP 8-based style rules. Most IDEs deliver efficient auto-completion tips, which help you write code more conveniently.
Python Tip 10: Practice! Practice! Practice!
This should be the most important Python Tip because sticking to a routine is crucial for learning a new language. It’s advisable to set a daily coding goal. Muscle memory is vital in programming, and daily coding helps you build it. Start with a manageable time, such as 25 minutes daily, and gradually increase it.
This tutorial is merely an introduction to the topics stated above; tutorials dedicated to tips respectively will be created in the nearest future.
Thank you for reading through this blog. We hope you found the information informative and helpful. We will continue to keep you updated with the latest developments and insights on Python Programming. Stay tuned for more exciting content from us. We value your feedback, so feel free to reach out with any comments or suggestions. Let’s continue learning together!