What's New In Python 3.8? Python 3.8 New Features

What's New In Python 3.8? Python 3.8 New Features

In this video 'What's New Features in Python 3.8?' covers the new features in Python 3.8 added to the new release of Python. What's New In Python 3.8? Python 3.8 New Features, Python 3.8 Tutorial

This video on 'What's New In Python 3.8?' covers the new features in python 3.8 added to the new release of Python and other language changes. Following are the topics discussed:
0:52 - New Features
08:33 - New Modules
09:05 - Other Language Changes

Dictionaries in Python - Learn how to work with Python Dictionaries

Dictionaries in Python - Learn how to work with Python Dictionaries

In this Python Dictionaries tutorial, you will learn how to work with Python Dictionaries, an incredibly helpful built-in data type that you will definitely use during your projects. In this Python dictionaries tutorial you'll cover the basic characteristics and learn how to access and manage dictionary data. Learn everything about Python dictionary; how they are created, accessing, adding and removing elements from them and, various built-in methods.

Welcome

In this article, you will learn how to work with Python Dictionaries, an incredibly helpful built-in data type that you will definitely use during your projects.

In particular, you will learn:

  • What dictionaries are used for and their main characteristics.
  • Why they are important for your programming projects.
  • The "anatomy" of a dictionary: keys, values, and key-value pairs.
  • The specific rules that determine if a value can be a key.
  • How to access, add, modify, and delete key-value pairs.
  • How to check if a key is in a dictionary.
  • What the length of a dictionary represents.
  • How to iterate over dictionaries using for loops.
  • What built-in dictionary methods you can use to leverage the power of this data type.

At the end of this article, we will dive into a simple project to apply your knowledge: we will write a function that creates and returns a dictionary with a particular purpose.

Let's begin! 🔅

🔸 Dictionaries in Context

Let's start by discussing the importance of dictionaries. To illustrate this, let me do a quick comparison with another data type that you are probably familiar with: lists.

When you work with lists in Python, you can access an element using a index, an integer that describes the position of the element in the list. Indices start from zero for the first element and increase by one for every subsequent element in the list. You can see an example right here:

But what if we need to store two related values and keep this "connection" in our code? Right now, we only have single, independent values stored in a list.

Let's say that we want to store names of students and "connect" each name with the grades of each particular student. We want to keep the "connection" between them. How would you do that in Python?

If you use nested lists, things would get very complex and inefficient after adding only a few items because you would need to use two or more indices two access each value, depending on the final list. This is where Python Dictionaries come to the rescue.

Meet Dictionaries

A Python dictionary looks like this (see below). With a dictionary, you can "connect" a value to another value to represent the relationship between them in your code. In this example,"Gino" is "connected" to the integer 15 and the string "Nora" is "connected" to the integer 30.

Let's see the different elements that make a dictionary.

🔹 The "Anatomy" of a Python Dictionary

Since a dictionary "connects" two values, it has two types of elements:

  • Keys: a key is a value used to access another value. Keys are the equivalent of "indices" in strings, lists, and tuples. In dictionaries, to access a value, you use the key, which is a value itself.
  • Values: these are the values that you can access with their corresponding key.

These two elements form what is called a key-value pair (a key with its corresponding value).

Syntax

This is an example of a Python Dictionary mapping the string "Gino" to the number 15 and the string "Nora" to the number 30:

>>> {"Gino": 15, "Nora": 30}

  • To create a dictionary, we use curly brackets { } .
  • Between these curly brackets, we write key-value pairs separated by a comma.
  • For the key-value pairs, we write the key followed by a colon, a space, and the value that corresponds to the key.

💡 Tips:

  • For readability and style purposes, it is recommended to add a space after each comma to separate the key-value pairs.
  • You can create an empty dictionary with an empty pair of curly brackets {}.

Important Rules for Keys

Not every value can be a key in a Python dictionary. Keys have to follow a set of rules:

According to the Python Documentation:

  • Keys have to be unique within one dictionary.

It is best to think of a dictionary as a set of key: value pairs, with the requirement that the keys are unique (within one dictionary).

  • Keys have to be immutable.

Unlike sequences, which are indexed by a range of numbers, dictionaries are indexed by keys, which can be any immutable type; strings and numbers can always be keys.

  • If the key is a tuple, it can only contain strings, numbers or tuples.

Tuples can be used as keys if they contain only strings, numbers, or tuples; if a tuple contains any mutable object either directly or indirectly, it cannot be used as a key.

  • Lists cannot be keys because they are mutable. This is a consequence of the previous rule.

You can’t use lists as keys, since lists can be modified in place using index assignments, slice assignments, or methods like append() and extend().

💡 Note: Values have no specific rules, they can be either mutable or immutable values.

🔸 Dictionaries in Action

Now let's see how we can work with dictionaries in Python. We are going to access, add, modify, and delete key-value pairs.

We will start working with this dictionary, assigned to the ages variable:

>>> ages = {"Gino": 15, "Nora": 30}

Access Values using Keys

If we need to access the value associated with a specific key, we write the name of the variable that references the dictionary followed by square brackets [] and, within square brackets, the key that corresponds to the value:

<variable>[<key>]

This is an example of how we can access the value that corresponds to the string "Gino":

>>> ages = {"Gino": 15, "Nora": 30}
>>> ages["Gino"]
15

Notice that the syntax is very similar to indexing a string, tuple, or list, but now we are using the key as the index instead of an integer.

If we want to access the value that corresponds to "Nora", we would do this:

>>> ages = {"Gino": 15, "Nora": 30}
>>> ages["Nora"]
30

💡 Tip: If you try to access a key that does not exist in the dictionary, you will get a KeyError:

>>> ages = {"Gino": 15, "Nora": 30}
>>> ages["Talina"]
Traceback (most recent call last):
  File "<pyshell#10>", line 1, in <module>
    ages["Talina"]
KeyError: 'Talina'

Add Key-Value Pairs

If a key-value pair doesn't exist in the dictionary, we can add it. To do this, we write the variable that references the dictionary followed by the key within square brackets, an equal sign, and the new value:

This is an example in IDLE:

>>> ages = {"Gino": 15, "Nora": 30}

# Add the key-value pair "Talina": 24
>>> ages["Talina"] = 24

# The dictionary now has this key-value pair
>>> ages
{'Gino': 15, 'Nora': 30, 'Talina': 24}

Modify a Key-Value Pair

To modify the value associated to a specific key, we use the same syntax that we use to add a new key-value pair, but now we will be assigning the new value to an existing key:

>>> ages = {"Gino": 15, "Nora": 30}

# The key "Gino" already exists in the dictionary, so its associated value
# will be updated to 45.
>>> ages["Gino"] = 45

# The value was updated to 45.
>>> ages
{'Gino': 45, 'Nora': 30}

Deleting a Key-Value Pair

To delete a key-value pair, you would use the del keyword followed by the name of the variable that references the dictionary and, within square brackets [], the key of the key-value pair:

This is an example in IDLE:

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}

# Delete the key-value pair "Gino": 15.
>>> del ages["Gino"]

# The key-value pair was deleted.
>>> ages
{'Nora': 30, 'Talina': 45}
🔹 Check if a Key is in a Dictionary

Sometimes, it can be very helpful to check if a key already exists in a dictionary (remember that keys have to be unique).

According to the Python Documentation:

To check whether a single key is in the dictionary, use the in keyword.

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> "Talina" in ages
True
>>> "Gino" in ages
True
>>> "Lulu" in ages
False

The in operator checks the keys, not the values. If we write this:

>>> 15 in ages
False

We are checking if the key 15 is in the dictionary, not the value. This is why the expression evaluates to False.

💡 Tip: You can use the in operator to check if a value is in a dictionary with .values().

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> 30 in ages.values()
True
>>> 10 in ages.values()
False
🔸 Length of a Python Dictionary

The length of a dictionary is the number of key-value pairs it contains. You can check the length of a dictionary with the len() function that we commonly use, just like we check the length of lists, tuples, and strings:

# Two key-value pairs. Length 2.
>>> ages = {"Gino": 15, "Nora": 30}
>>> len(ages)
2

# Three key-value pairs. Length 3.
>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> len(ages)
3
🔹 Iterating over Dictionaries in Python

You can iterate over dictionaries using a for loop. There are various approaches to do this and they are all equally relevant. You should choose the approach that works best for you, depending on what you are trying to accomplish.

First Option - Iterate over the Keys

We can iterate over the keys of a dictionary like this:

for <key> in <dictionary>:
	# Do this

For example:

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> for student in ages:
	print(student)

Gino
Nora
Talina

Second Option - Iterate over the Key-Value Pairs

To do this, we need to use the built-in method .items(), which allows us to iterate over the key-value pairs as tuples of this format (key, value).

for <key-value-pair-as-tuple> in <dictionary>.items():
	# Do this

For example:

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}

>>> for pair in ages.items():
	print(pair)

('Gino', 15)
('Nora', 30)
('Talina', 45)

Third Option - Assign Keys and Values to Individual Variables

With .items() and for loops, you can use the power of a tuple assignment to directly assign the keys and values to individual variables that you can use within the loop:

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}

# Tuple assignment to assign the key to the variable key 
# and the value to the variable value.
>>> for key, value in ages.items():
	print("Key:", key, "; Value:", value)

Key: Gino ; Value: 15
Key: Nora ; Value: 30
Key: Talina ; Value: 45

Fourth Option - Iterate over the Values

You can iterate over the values of a dictionary using the .values() method.

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> for age in ages.values():
	print(age)

15
30
45
🔸 Dictionary Methods

Dictionaries include very helpful built-in methods that can save you time and work to perform common functionality:

.clear()

This method removes all the key-value pairs from the dictionary.

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> ages.clear()
>>> ages
{}

.get(, )

This method returns the value associated with the key. Otherwise, it returns the default value that was provided as the second argument (this second argument is optional).

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> ages.get("Nora")
30
>>> ages.get("Nor", "Not Found")
'Not Found'

If you don't add a second argument, this is equivalent to the previous syntax with square brackets []that you learned:

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> ages["Nora"]
30
>>> ages.get("Nora")
30

.pop(, )

This method removes the key-value pair from the dictionary and returns the value.

>>> ages = {"Gino": 15, "Nora": 30, "Talina": 45}
>>> ages.pop("Talina")
45
>>> ages
{'Gino': 15, 'Nora': 30}

.update()

This method replaces the values of a dictionary with the values of another dictionary only for those keys that exist in both dictionaries.

An example of this would be a dictionary with the original grades of three students (see code below). We only want to replace the grades of the students who took the make-up exam (in this case, only one student took the make-up exam, so the other grades should remain unchanged).

>>> grades = {"Gino": 0, "Nora": 98, "Talina": 99}
>>> new_grades = {"Gino": 67}
>>> grades.update(new_grades)
>>> grades
{'Gino': 67, 'Nora': 98, 'Talina': 99}

By using the .update() method, we could update the value associated with the string "Gino" in the original dictionary since this is the only common key in both dictionaries.

The original value would be replaced by the value associated with this key in the dictionary that was passed as argument to .update().

💡 Tips: To learn more about dictionary methods, I recommend reading this article in the Python Documentation.

🔹 Mini Project - A Frequencies Dictionary

Now you will apply your knowledge by writing a function freq_dict that creates and returns a dictionary with the frequency of each element of a list, string, or tuple (the number of times the element appears). The elements will be the keys and the frequencies will be the values.

Code

We will be writing the function step-by-step to see the logic behind each line of code.

  • Step 1: The first thing that we need to do is to write the function header. Notice that this function only takes one argument, the list, string or tuple, which we call data.
def freq_dict(data):
  • Step 2: Then, we need to create an empty dictionary that will map each element of the list, string, or tuple to its corresponding frequency.
def freq_dict(data):
	freq = {}
  • Step 3: Then, we need to iterate over the list, string, or tuple to determine what to do with each element.
def freq_dict(data):
	freq = {}
	for elem in data: 
  • Step 4: If the element has already been included in the dictionary, then the element appears more than once and we need to add 1 to its current frequency. Else, if the element is not in the dictionary already, it's the first time it appears and its initial value should be 1.
def freq_dict(data):
	freq = {}
	for elem in data:
		if elem in freq:
			freq[elem] += 1
		else:
			freq[elem] = 1
  • Step 5: Finally, we need to return the dictionary.
def freq_dict(data):
	freq = {}
	for elem in data:
		if elem in freq:
			freq[elem] += 1
		else:
			freq[elem] = 1
	return freq

🔔 Important: Since we are assigning the elements as the keys of the dictionary, they have to be of an immutable data type.

Examples

Here we have an example of the use of this function. Notice how the dictionary maps each character of the string to how many times it occurs.

>>> def freq_dict(data):
	freq = {}
	for elem in data:
		if elem in freq:
			freq[elem] += 1
		else:
			freq[elem] = 1
	return freq

>>> freq_dict("Hello, how are you?")
{'H': 1, 'e': 2, 'l': 2, 'o': 3, ',': 1, ' ': 3, 'h': 1, 'w': 1, 'a': 1, 'r': 1, 'y': 1, 'u': 1, '?': 1}

This is another example applied to a list of integers:

>>> def freq_dict(data):
	freq = {}
	for elem in data:
		if elem in freq:
			freq[elem] += 1
		else:
			freq[elem] = 1
	return freq

>>> freq_dict([5, 2, 6, 2, 6, 5, 2, 2, 2])
{5: 2, 2: 5, 6: 2}

Great Work! Now we have the final function.

🎓 In Summary
  • Dictionary are built-in data types in Python that associate (map) keys to values, forming key-value pairs.
  • You can access a value with its corresponding key.
  • Keys have to be of an immutable data type.
  • You can access, add, modify, and delete key-value pairs.
  • Dictionaries offer a wide variety of methods that can help you perform common functionality.

Originally published by Estefania Cassingena Navone at https://www.freecodecamp.org

Learn Python from Zero - Full Fundamental Course for Beginners

Learn Python from Zero - Full Fundamental Course for Beginners

Learn Python from Zero - Full Fundamental Course for Beginners: This course will provides you a full introduction into all of the core concepts in python like data types, reserved words etc. View this Python tutorial for beginners to learn Python programming from zero. Every topic explained in detail to make this best Python tutorial for beginners.

Learn Python from Zero - Full Fundamental Course for Beginners

This course will provides you a full introduction into all of the core concepts in python like data types, reserved words etc. Follow along with the videos and you will become a python programmer in less time and you will entered into Python world.
View this Python tutorial for beginners to learn Python programming from zero. Every topic explained in detail to make this best Python tutorial for beginners.

Contents:

  1. (00:00:00) What is Python and Father of Python
  2. (00:19:30) Easiness of Python when compared with Other Languages
  3. (00:45:35) Why the name 'Python'
  4. (00:53:29) Python as All Rounder
  5. (01:04:28) Where we can use Python
  6. (01:11:26) Features of Python: Part-1
  7. (01:25:30) Features of Python: Part-2
  8. (01:44:47) Features of Python: Part-3
  9. (01:58:48) Features of Python: Part-4
  10. (02:11:58) Features of Python Summary
  11. (02:19:08) Limitations and Flavors of Python
  12. (02:37:13) Python Versions
  13. (02:51:05) Python Identifiers
  14. (03:13:26) Python Reserved Words
  15. (03:26:56) Data Types Introduction
  16. (03:42:00) Data Types: int data type
  17. (04:04:16) Data Types: Base Conversion Functions
  18. (04:12:59) Data Types: float data type
  19. (04:25:22) Data Types: complex data type
  20. (04:38:47) Data Types: bool data type
  21. (04:46:55) str data type representations by using single,double and triple quotes
  22. (05:07:02) Data Types: str data type - positive and negative index
  23. (05:14:16) Data Types: str data type - Slice Operator
  24. (05:30:45) Data Types: str data type - Slice Operator Applications
  25. (05:43:26) Data Types: + and * operators for str data type
  26. (05:56:29) Type Casting: introduction and int() function
  27. (06:10:00) Type Casting: float() and complex() functions
  28. (06:32:34) Type Casting: bool() and str() functions
  29. (06:44:57) Type Casting: Summary
  30. (06:53:39) Fundamental Data Types vs Immutability : Meaning Of Immutability
  31. (07:08:21) Fundamental Data Types vs Immutability : Need Of Immutability
  32. (07:29:06) Immutability vs Mutability
  33. (07:49:26) Python Data Types: List data type
  34. (08:14:00) Python Data Types: Tuple data type
  35. (08:35:53) Python Data Types: Set data type
  36. (08:56:58) Python Data Types: FrozenSet
  37. (09:07:39) Python Data Types: Dict
  38. (09:24:18) Python Data Types: range
  39. (09:48:35) Python Data Types: bytes and bytearray
  40. (10:05:25) Python Data Types Summary
  41. (10:25:13)None Data Type
  42. (10:37:46)Escape Characters,Comments and Constants

5 Python Online Courses for Beginners

5 Python Online Courses for Beginners

If you are thinking to learn a new programming language then also Python is a good choice, particularly if you are looking to move towards a lucrative career path of Data Science and Machine learning which has lots of opportunities. In this article, I am going to share some of the best online courses to learn Python in 2020...

Python is an object-oriented, high-level programming language with integrated dynamic semantics primarily for web and app development. It is extremely attractive in the field of Rapid Application Development because it offers dynamic typing and dynamic binding options.

Python is relatively simple, so it's easy to learn since it requires a unique syntax that focuses on readability. Developers can read and translate Python code much easier than other languages. In turn, this reduces the cost of program maintenance and development because it allows teams to work collaboratively without significant language and experience barriers.

Additionally, Python supports the use of modules and packages, which means 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.

In recent years, Python has also become a default language for Data Science and Machine learning Projects and that's another reason why many experienced programmers are learning Python .

If you are thinking to learn a new programming language then also Python is a good choice, particularly if you are looking to move towards a lucrative career path of Data Science and Machine learning which has lots of opportunities. In this article, you will find free online courses in python programming, but not only will you find one, but you will also find 5 more courses on Python! I am going to share some of the best online courses to learn Python in 2020

They are high quality courses with more than 4 star rating (from 0 to 5 stars), that means if you are starting your career with the python programming language, these are the best courses that will take you step-by-step , to start and learn from scratch the fundamentals about this language that so professional and useful has been in recent years.

Top 5 Courses to Learn Python in 2020

1. Complete Python Bootcamp: Go from zero to hero in Python

This is one of the most popular course to learn Python on Udemy and more than 250,000 students have enrolled in it. That speaks volumes for the quality of the course.

This is a comprehensive but straight-forward course to learn the Python programming language on Udemy! and useful for all levels of programmers.

In this course, you will learn Python 3 in a practical manner. You will start by downloading and setting up Python on your machine and then slowly move on to different topics.

It's also a practical course where an instructor will show you live coding and explain what he does.

The course also comes with quizzes, notes and homework assignments as well as 3 major projects to create a Python project portfolio! which complements your learning.

2. 30 Days of Python | Unlock your Python Potential

In early 2016, Python passed Java as the #1 beginners language in the world. Why? It's because it's simple enough for beginners yet advanced enough for the pros.

You can not only write simple scripts to automate stuff but also create a complex program to handle trades. You can even use Python for it for IOT, Web Development, Big Data, Data Science, Machine learning and more.

This is a very practical course and useful not just for beginners but also for programmers who know other programming languages e.g. Java, C++ and want to learn Python.

In 30 days this course will teach you to write complex Python applications to scrape Data from nearly any website and Build your own Python applications for all types of automation. It's perfect for busy developers who learn by doing serious stuff.

3. Python for Beginners with Examples


This online Python course is taught by Ardit Sulce ,This Python course has everything you need to know to start coding in Python and not even that, by the end of the course you will know how to build complete programs and also build graphical user interfaces for your programs so you can impress your employer or your friends. This course will guide you step by step starting from the basics and always assuming you don't have previous programming experience or a computer science degree. In fact, most people who learn Python come from a vast variety of careers.

This course has all you need to get you started. After you take it you will be ready to go to the next level of specializing in any of the Python paths such as data science or web development. Python is one of the most needed skills nowadays. Sign up today!

4. Learn Python Programming Masterclass


This is another fantastic course to learn Python on Udemy. This course is taught by Tim Buchalka,I am a big fan of Tim Buchalka and have attended a couple of his courses.

This course is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python.

The fact is, Python is one of the most popular programming languages in the world – Huge companies like Google use it in mission critical applications like Google Search.

And Python is the number one language choice for machine learning, data science and artificial intelligence. To get those high paying jobs you need an expert knowledge of Python, and that’s what you will get from this course.

By the end of the course you’ll be able to apply in confidence for Python programming jobs. And yes, this applies even if you have never programmed before. With the right skills which you will learn in this course, you can become employable and valuable in the eyes of future employers.

5. The Python Bible™ | Everything You Need to Program in Python

This course was developed by Ziyad Yehia , a renowned instructor on Udemy. Currently, This course has nearly 78,000 students and excellent star ratings.

This is a project-based course and you will build 11 Projects int this Python Course.

If you enjoy hands-on learning while working on the project rather than learning individual concept then this course is for you.

This is a comprehensive, in-depth and meticulously prepared course and teaches you everything you need to know to program in Python. It delivers what is promised in the title, A-Z, it's all here!

Conclusion

That's all about the best courses to learn Python in depth. you can begin with these courses, don't need to buy all of them, just choose the one where you can connect with instructor.

These courses will give you a solid foundation and confidence to use Python in your project.

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Thanks for reading