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How To Write Beautiful Python Code With PEP 8

It gets difficult to understand a messed up handwriting, similarly an unreadable and unstructured code is not accepted by all. However, you can benefit as a programmer only when you can express better with your code. This is where PEP comes to the rescue. Python Enhancement Proposal or PEP is a design document which provides information to the Python community and also describes new features and document aspects, such as style and design for Python.Python is a multi-paradigm programming language which is easy to learn and has gained popularity in the fields of Data Science and Web Development over a few years and PEP 8 is called the style code of Python. It was written by Guido van Rossum, Barry Warsaw, and Nick Coghlan in the year 2001. It focuses on enhancing Python’s code readability and consistency. Join the certification course on Python Programming and gain skills and knowledge about various features of Python along with tips and tricks.A Foolish Consistency is the Hobgoblin of Little Minds‘A great person does not have to think consistently from one day to the next’ — this is what the statement means.Consistency is what matters. It is considered as the style guide. You should maintain consistency within a project and mostly within a function or module.However, there will be situations where you need to make use of your own judgement, where consistency isn’t considered an option. You must know when you need to be inconsistent like for example when applying the guideline would make the code less readable or when the code needs to comply with the earlier versions of Python which the style guide doesn’t recommend. In simple terms, you cannot break the backward compatibility to follow with PEP.The Zen of PythonIt is a collection of 19 ‘guiding principles’ which was originally written by Tim Peters in the year 1999. It guides the design of the Python Programming Language.Python was developed with some goals in mind. You can see those when you type the following code and run it:>>> import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those!The Need for PEP 8Readability is the key to good code. Writing good code is like an art form which acts as a subjective topic for different developers.Readability is important in the sense that once you write a code, you need to remember what the code does and why you have written it. You might never write that code again, but you’ll have to read that piece of code again and again while working in a project. PEP 8 adds a logical meaning to your code by making sure your variables are named well, sufficient whitespaces are there or not and also by commenting well. If you’re a beginner to the language, PEP 8 would make your coding experience more pleasant.Following PEP 8 would also make your task easier if you’re working as a professional developer. People who are unknown to you and have never seen how you style your code will be able to easily read and understand your code only if you follow and recognize a particular guideline where readability is your de facto.And as Guido van Rossum said— “Code is read much more than it is often written”.The Code LayoutYour code layout has a huge impact on the readability of your code.IndentationThe indentation level of line is computed by the leading spaces and tabs at the beginning of a line of logic. It influences the grouping of statements. The rules of PEP 8 says to use 4 spaces per indentation level and also spaces should be preferred over tabs.An example of code to show indentation:x = 5 if x < 10:   print('x is less than 10') Tabs or Spaces?Here the print statement is indented which informs Python to execute the statement only if the if statement is true. Indentation also helps Python to know what code it will execute during function calls and also when using classes.PEP 8 recommends using 4 spaces to show indentation and tabs should only be used to maintain consistency in the code.Python 3 forbids the mixing of spaces and tabs for indentation. You can either use tabs or spaces and you should maintain consistency while using Python 3. The errors are automatically displayed:python hello.py  File "hello.py", line 3       print(i, j)                 ^TabError: inconsistent use of tabs and spaces in indentationHowever, if you’re working in Python 2, you can check the consistency by using a -t flag in your code which will display the warnings of inconsistencies with the use of spaces and tabs.You can also use the -tt flag which will show the errors instead of warnings and also the location of inconsistencies in your code. Maximum Line Length and Line BreakingThe Python Library is conservative and 79 characters are the maximum required line limit as suggested by PEP 8. This helps to avoid line wrapping.Since maintaining the limit to 79 characters isn’t always possible, so PEP 8 allows wrapping lines using Python’s implied line continuation with parentheses, brackets, and braces:def function(argument_1, argument_2,             argument_3, argument_4):     return argument_1Or by using backslashes to break lines:with open('/path/to/some/file/you/want/to/read') as example_1, \     open('/path/to/some/file/being/written', 'w') as example_2:     file_2.write(file_1.read())When it comes to binary operators, PEP 8 encourages to break lines before the binary operators. This accounts for more readable code.Let us understand this by comparing two examples:# Example 1 # Do total = ( variable_1 + variable_2 - variable_3 ) # Example 2 # Don't total = ( variable_1 + variable_2 - variable_3 )In the first example, it is easily understood which variable is added or subtracted, since the operator is just next to the variable to which it is operated. However, in the second example, it is a little difficult to understand which variable is added or subtracted.Indentation with Line BreaksIndentation allows a user to differentiate between multiple lines of code and a single line of code that spans multiple lines. It enhances readability too.The first style of indentation is to adjust the indented block with the delimiter:def function(argument_one, argument_two,               argument_three, argument_four):         return argument_oneYou can also improve readability by adding comments:x = 10 if (x > 5 and     x < 20):     # If Both conditions are satisfied     print(x)Or by adding extra indentation:x = 10 if (x > 5 and       x < 20):     print(x)Another type of indentation is the hanging indentation by which you can symbolize a continuation of a line of code visually:foo = long_function_name(       variable_one, variable_two,       variable_three, variable_four)You can choose any of the methods of indentation, following line breaks, in situations where the 79 character line limit forces you to add line breaks in your code, which will ultimately improve the readability.Closing Braces in Line ContinuationsClosing the braces after line breaks can be easily forgotten, so it is important to put it somewhere where it makes good sense or it can be confusing for a reader.One way provided by PEP 8 is to put the closing braces with the first white-space character of the last line:my_list_of_numbers = [     1, 2, 3,     4, 5, 6,     7, 8, 9     ]Or lining up under the first character of line that initiates the multi-line construct:my_list_of_numbers = [     1, 2, 3,     4, 5, 6,     7, 8, 9 ]Remember, you can use any of the two options keeping in mind the consistency of the code.Blank LinesBlank lines are also called vertical whitespaces. It is a logical line consisting of spaces, tabs, formfeeds or comments that are basically ignored.Using blank lines in top-level-functions and classes:class my_first_class:     pass class my_second_class:     pass def top_level_function():     return NoneAdding two blank lines between the top-level-functions and classes will have a clear separation and will add more sensibility to the code.Using blank lines in defining methods inside classes:class my_class:     def method_1(self):         return None     def method_2(self):         return NoneHere, a single vertical space is enough for a readable code.You can also use blank spaces inside multi-step functions. It helps the reader to gather the logic of your function and understand it efficiently. A single blank line will work in such case.An example to illustrate such:def calculate_average(number_list):     sum_list = 0     for number in number_list:         sum_list = sum_list + number         average = 0     average = sum_list / len(number_list)    return averageAbove is a function to calculate the average. There is a blank line between each step and also before the return statement.The use of blank lines can greatly improve the readability of your code and it also allows the reader to understand the separation of the sections of code and the relation between them.Naming ConventionsChoosing names which are sensible and can be easily understandable, while coding in Python, is very crucial. This will save time and energy of a reader. Inappropriate names might lead to difficulties when debugging.Naming StylesNaming variables, functions, classes or methods must be done very carefully. Here’s a list of the type, naming conventions and examples on how to use them:TypeNaming ConventionsExamplesVariableUsing short names with CapWords.T, AnyString, My_First_VariableFunctionUsing a lowercase word or words with underscores to improve readability.function, my_first_functionClassUsing CapWords and do not use underscores between words.Student, MyFirstClassMethodUsing lowercase words separated by underscores.Student_method, methodConstantsUsing all capital letters with underscores separating wordsTOTAL, MY_CONSTANT, MAX_FLOWExceptionsUsing CapWords without underscores.IndexError, NameErrorModuleUsing short lower-case letters using underscores.module.py, my_first_module.pyPackageUsing short lowercase words and underscores are discouraged.package, my_first_packageChoosing namesTo have readability in your code, choose names which are descriptive and give a clearer sense of what the object represents. A more real-life approach to naming is necessary for a reader to understand the code.Consider a situation where you want to store the name of a person as a string:>>> name = 'John William' >>> first_name, last_name = name.split() >>> print(first_name, last_name, sep='/ ') John/ WilliamHere, you can see, we have chosen variable names like first_name and last_name which are clearer to understand and can be easily remembered. We could have used short names like x, y or z but it is not recommended by PEP 8 since it is difficult to keep track of such short names.Consider another situation where you want to double a single argument. We can choose an abbreviation like db for the function name:# Don't def db(x):     return x * 2However, abbreviations might be difficult in situations where you want to return back to the same code after a couple of days and still be able to read and understand. In such cases, it’s better to use a concise name like double_a_variable:# Do def double_a_value(x):     return x * 2Ultimately, what matters is the readability of your code.CommentsA comment is a piece of code written in simple English which improves the readability of code without changing the outcome of a program. You can understand the aim of the code much faster just by reading the comments instead of the actual code. It is important in analyzing codes, debugging or making a change in logic. Block CommentsBlock comments are used while importing data from files or changing a database entry where multiples lines of code are written to focus on a single action. They help in interpreting the aim and functionality of a given block of code.They start with a hash(#) and a single space and always indent to the same level as the code:for i in range(0, 10):     # Loop iterates 10 times and then prints i     # Newline character     print(i, '\n')You can also use multiple paragraphs in a block comment while working on a more technical program. Block comments are the most suitable type of comments and you can use it anywhere you like.Inline CommentsInline comments are the comments which are placed on the same line as the statement. They are helpful in explaining why a certain line of code is essential.Example of inline comments:x = 10  # An inline comment y = 'JK Rowling' # Author NameInline comments are more specific in nature and can easily be used which might lead to clutter. So, PEP 8 basically recommends using block comments for general-purpose coding.Document StringsDocument strings or docstrings start at the first line of any function, class, file, module or method. These type of comments are enclosed between single quotations ( ''') or double quotations ( """ ).An example of docstring:def quadratic_formula(x, y, z, t):     """Using the quadratic formula"""     t_1 = (- b+(b**2-4*a*c)**(1/2)) / (2*a)     t_2 = (- b-(b**2-4*a*c)**(1/2)) / (2*a)     return t_1, t_2Whitespaces in Expressions and StatementsIn computing, whitespace is any character or sequence of characters which are used for spacing and have an ‘empty’ representation. It is helpful in improving the readability of expressions and statements if used properly.Whitespace around Binary OperatorsWhen you’re using assignment operators ( =, +=, -=,and so forth ) or comparisons ( ==, !=, >, <. >=, <= ) or booleans ( and, not, or ), it is suggested to use a single whitespace on the either side.Example of adding whitespace when there is more than one operator in a statement:# Don't b = a ** 2 + 10 c = (a + b) * (a - b) # Do b = a**2 + 10 c = (a+b) * (a-b)In such mathematical computations, you should add whitespace around the operators with the least priority since adding spaces around each operator might be confusing for a reader.Example of adding whitespaces in an if statement with many conditions:# Don't if a < 10 and a % 5 == 0:     print('a is smaller than 10 and is divisible by 5!') # Do if a<10 and a%5==0:     print('a is smaller than 10 and is divisible by 5!')Here, the and operator has the least priority, so whitespaces have been added around it.Colons act as binary operators in slices:ham[3:4]ham[x+1 : x+2]ham[3:4:5]ham[x+1 : x+2 : x+3]ham[x+1 : x+2 :]Since colons act as a binary operator, whitespaces are added on either side of the operator with the lowest priority. Colons must have the same amount of spacing in case of an extended slice. An exception is when the slice parameter is omitted, space is also omitted.Avoiding WhitespacesTrailing whitespaces are whitespaces placed at the end of a line. These are the most important to avoid. You should avoid whitespaces in the following cases—Inside a parentheses, brackets, or braces:# Do list = [1, 2, 3] # Don't list = [ 1, 2, 3, ]Before a comma, a semicolon, or a colon:x = 2 y = 3 # Do print(x, y) # Don't print(x , y)Before open parenthesis that initiates the argument list of a function call:def multiply_by_2(a):       return a * 2 # Do multiply_by_2(3) # Don't multiply_by_2 (3)Before an open bracket that begins an index or a slice:# Do ham[5] # Don't ham [5]Between a trailing comma and a closing parenthesis:# Do spam = (1,) # Don't spam = (1, )To adjust assignment operators:# Do variable_1 = 5 variable_2 = 6 my_long_var = 7 # Don't variable_1    = 5 variable_2    = 6 my_long_var  = 7Programming RecommendationsPEP 8 guidelines suggest different ways to maintain consistency among multiple implementations of Python like PyPy, Jython or Cython.An example of comparing boolean values:# Don't bool_value = 5 > 4 if bool_value == True: return '4 is smaller than 5' # Do if bool_value: return '4 is smaller than 5'Since bool can only accept values True or False, it is useless to use the equivalence operator == in these type of if executions. PEP 8 recommends the second example which will require lesser and simpler coding. An example to check whether a list is empty or not:# Don't list_value = [] if not len(list_value):     print('LIST IS EMPTY') # Do list_value = [] if not list_value:     print('LIST IS EMPTY')Any empty list or string in Python is falsy. So you can write a code to check an empty string without checking the length of the list. The second example is more simple, so PEP encourages to write an if statement in this way.The expression is not and not ... is are identical in functionality. But the former is more preferable due to its nature of readability:# Do if x is not None:     return 'x has a value' # Don't if not x is None:     return 'x has a value'String slicing is a type of indexing syntax that extracts substrings from a string. Whenever you want to check if a string is prefixed or suffixed, PEP recommends using .startswith() and .endswith() instead of list slicing. This is because they are cleaner and have lesser chances of error:# Do if foo.startswith('cat'): # Don't if foo[:3] == 'cat':An example using .endswith():# Don't if file_jpg[-3:] == 'jpg':     print('It is a JPEG image file') # Do if file_jpg.endswith('jpg'):     print('It is a JPEG image file')Though there exists multiple ways to execute a particular action, the main agenda of the guidelines laid by PEP 8 is simplicity and readability.When to Ignore PEP 8You should never ignore PEP 8. If the guidelines related to PEP8 are followed, you can be confident of writing readable and professional codes. This will also make the lives of your  colleagues and other members working on the same project much easier. There are some exclusive instances when you may ignore a particular guideline:After following the guidelines, the code becomes less readable, even for a programmer who is comfortable with reading codes that follow PEP 8.If the surrounding code is inconsistent with PEP.Compatible of code with older version of Python is the priority.Checking PEP 8 Compliant CodeYou can check whether your code actually complies with the rules and regulations of PEP 8 or not. Linters and Autoformatters are two classes of tools used to implement and check PEP 8 compliance.LintersIt is a program that analyzes your code and detects program errors, syntax errors, bugs and structural problems. They also provide suggestions to correct the errors.Some of the best linters used for Python code:pycodestyle is a tool to verify the PEP 8 style conventions in your Python code.You can run the following from the command line to install pycodestyle using pip:pip install pycodestyleTo display the errors of a program, run pycodestyle in this manner:pycodestyle my_code.pymy_code.py:1:11: E231 missing whitespace after '{'my_code.py:3:19: E231 missing whitespace after ')'my_code.py:4:31: E302 expected 2 blank lines, found 1flake8 is a Python wrapper that verifies PEP 8, pyflakes, and circular complexity.Type the command to install flake8 using pip:pip install flake8Run flake8 from the terminal using the command:flake8 calc.py calc.py:24:3: E111 indentation is not a multiple of twocalc.py:25:3: E111 indentation is not a multiple of twocalc.py:45:9: E225 missing whitespace around operatorYou can also use some other good linters like pylint, pyflakes, pychecker and mypy.AutoformattersAn autoformatter is a tool which will format your code to adapt with PEP 8 automatically.One of the most commonly used autoformatter is black.To install black using pip, type:pip install blackRemember, you need to have Python 3.6 or above to install black.An example of code that doesn’t follow PEP 8:def add(a, b): return a+b def multiply(a, b):       return \         a   * bNow run black following the filename from the terminal:black my_code.pyreformatted my_code.pyAll done! The reformatted code will look like:def add(a, b):     return a + b def multiply(a, b):     return a * bSome other autoformatters include autopep8 and yapf. Their work is similar to black.ConclusionSince you have now learnt to write a good-quality and readable Python code using PEP 8, you’ll consider it a bliss while working in a project. Though it might be too precise in its nature, it will be useful to everyone working in a particular project by making the code more understandable and making changes and debugging easier.Let us sum up what we’ve learnt so far:What is PEP 8 and what is its importance.Multiple guidelines for writing PEP 8 compliant code.How to check code against PEP 8 using linters and autoformatters.If you intend to know more about PEP 8 and its book of guidelines, you can refer to pep8.org or simply enroll for the Python certification course offered by KnowledgeHut.

How To Write Beautiful Python Code With PEP 8

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How To Write Beautiful Python Code With PEP 8

It gets difficult to understand a messed up handwriting, similarly an unreadable and unstructured code is not accepted by all. However, you can benefit as a programmer only when you can express better with your code. This is where PEP comes to the rescue. 

Python Enhancement Proposal or PEP is a design document which provides information to the Python community and also describes new features and document aspects, such as style and design for Python.

Python is a multi-paradigm programming language which is easy to learn and has gained popularity in the fields of Data Science and Web Development over a few years and PEP 8 is called the style code of Python. It was written by Guido van Rossum, Barry Warsaw, and Nick Coghlan in the year 2001. It focuses on enhancing Python’s code readability and consistency. Join the certification course on Python Programming and gain skills and knowledge about various features of Python along with tips and tricks.

A Foolish Consistency is the Hobgoblin of Little Minds

‘A great person does not have to think consistently from one day to the next’ — this is what the statement means.

Consistency is what matters. It is considered as the style guide. You should maintain consistency within a project and mostly within a function or module.

However, there will be situations where you need to make use of your own judgement, where consistency isn’t considered an option. You must know when you need to be inconsistent like for example when applying the guideline would make the code less readable or when the code needs to comply with the earlier versions of Python which the style guide doesn’t recommend. 

In simple terms, you cannot break the backward compatibility to follow with PEP.

The Zen of Python

It is a collection of 19 ‘guiding principles’ which was originally written by Tim Peters in the year 1999. It guides the design of the Python Programming Language.

Python was developed with some goals in mind. You can see those when you type the following code and run it:

>>> import this
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

The Need for PEP 8

Readability is the key to good code. Writing good code is like an art form which acts as a subjective topic for different developers.

Readability is important in the sense that once you write a code, you need to remember what the code does and why you have written it. You might never write that code again, but you’ll have to read that piece of code again and again while working in a project. 

PEP 8 adds a logical meaning to your code by making sure your variables are named well, sufficient whitespaces are there or not and also by commenting well. If you’re a beginner to the language, PEP 8 would make your coding experience more pleasant.

Following PEP 8 would also make your task easier if you’re working as a professional developer. People who are unknown to you and have never seen how you style your code will be able to easily read and understand your code only if you follow and recognize a particular guideline where readability is your de facto.

And as Guido van Rossum said— “Code is read much more than it is often written”.

The Code Layout

Your code layout has a huge impact on the readability of your code.

Indentation

The indentation level of line is computed by the leading spaces and tabs at the beginning of a line of logic. It influences the grouping of statements. 

The rules of PEP 8 says to use 4 spaces per indentation level and also spaces should be preferred over tabs.

An example of code to show indentation:

x = 5
if x < 10:
  print('x is less than 10') 

Tabs or Spaces?

Here the print statement is indented which informs Python to execute the statement only if the if statement is true. Indentation also helps Python to know what code it will execute during function calls and also when using classes.

PEP 8 recommends using 4 spaces to show indentation and tabs should only be used to maintain consistency in the code.

Python 3 forbids the mixing of spaces and tabs for indentation. You can either use tabs or spaces and you should maintain consistency while using Python 3. The errors are automatically displayed:

python hello.py
  File "hello.py", line 3
      print(i, j)
                ^

TabError: inconsistent use of tabs and spaces in indentation

However, if you’re working in Python 2, you can check the consistency by using a -t flag in your code which will display the warnings of inconsistencies with the use of spaces and tabs.

You can also use the -tt flag which will show the errors instead of warnings and also the location of inconsistencies in your code. 

Maximum Line Length and Line Breaking

The Python Library is conservative and 79 characters are the maximum required line limit as suggested by PEP 8. This helps to avoid line wrapping.

Since maintaining the limit to 79 characters isn’t always possible, so PEP 8 allows wrapping lines using Python’s implied line continuation with parentheses, brackets, and braces:

def function(argument_1, argument_2,
            argument_3, argument_4):
    return argument_1

Or by using backslashes to break lines:

with open('/path/to/some/file/you/want/to/read') as example_1, \
    open('/path/to/some/file/being/written', 'w') as example_2:
    file_2.write(file_1.read())

When it comes to binary operators, PEP 8 encourages to break lines before the binary operators. This accounts for more readable code.

Let us understand this by comparing two examples:

# Example 1
# Do
total = ( variable_1 + variable_2 - variable_3 )
# Example 2
# Don't
total = ( variable_1 + variable_2 - variable_3 )

In the first example, it is easily understood which variable is added or subtracted, since the operator is just next to the variable to which it is operated. However, in the second example, it is a little difficult to understand which variable is added or subtracted.

Indentation with Line Breaks

Indentation allows a user to differentiate between multiple lines of code and a single line of code that spans multiple lines. It enhances readability too.

The first style of indentation is to adjust the indented block with the delimiter:

def function(argument_one, argument_two,
              argument_three, argument_four):
        return argument_one

You can also improve readability by adding comments:

x = 10
if (x > 5 and
    x < 20):
    # If Both conditions are satisfied
    print(x)

Or by adding extra indentation:

x = 10
if (x > 5 and
      x < 20):
    print(x)

Another type of indentation is the hanging indentation by which you can symbolize a continuation of a line of code visually:

foo = long_function_name(
      variable_one, variable_two,
      variable_three, variable_four)

You can choose any of the methods of indentation, following line breaks, in situations where the 79 character line limit forces you to add line breaks in your code, which will ultimately improve the readability.

Closing Braces in Line Continuations

Closing the braces after line breaks can be easily forgotten, so it is important to put it somewhere where it makes good sense or it can be confusing for a reader.

One way provided by PEP 8 is to put the closing braces with the first white-space character of the last line:

my_list_of_numbers = [
    1, 2, 3,
    4, 5, 6,
    7, 8, 9
    ]

Or lining up under the first character of line that initiates the multi-line construct:

my_list_of_numbers = [
    1, 2, 3,
    4, 5, 6,
    7, 8, 9
]

Remember, you can use any of the two options keeping in mind the consistency of the code.

Blank Lines

Blank lines are also called vertical whitespaces. It is a logical line consisting of spaces, tabs, formfeeds or comments that are basically ignored.

Using blank lines in top-level-functions and classes:

class my_first_class:
    pass
class my_second_class:
    pass
def top_level_function():
    return None

Adding two blank lines between the top-level-functions and classes will have a clear separation and will add more sensibility to the code.

Using blank lines in defining methods inside classes:

class my_class:
    def method_1(self):
        return None

    def method_2(self):
        return None

Here, a single vertical space is enough for a readable code.

You can also use blank spaces inside multi-step functions. It helps the reader to gather the logic of your function and understand it efficiently. A single blank line will work in such case.

An example to illustrate such:

def calculate_average(number_list):
    sum_list = 0
    for number in number_list:
        sum_list = sum_list + number
   
    average = 0
    average = sum_list / len(number_list)

   return average

Above is a function to calculate the average. There is a blank line between each step and also before the return statement.

The use of blank lines can greatly improve the readability of your code and it also allows the reader to understand the separation of the sections of code and the relation between them.

Naming Conventions

Choosing names which are sensible and can be easily understandable, while coding in Python, is very crucial. This will save time and energy of a reader. Inappropriate names might lead to difficulties when debugging.

Naming Styles

Naming variables, functions, classes or methods must be done very carefully. Here’s a list of the type, naming conventions and examples on how to use them:

TypeNaming ConventionsExamples
VariableUsing short names with CapWords.T, AnyString, My_First_Variable
FunctionUsing a lowercase word or words with underscores to improve readability.function, my_first_function
ClassUsing CapWords and do not use underscores between words.Student, MyFirstClass
MethodUsing lowercase words separated by underscores.Student_method, method
ConstantsUsing all capital letters with underscores separating wordsTOTAL, MY_CONSTANT, MAX_FLOW
ExceptionsUsing CapWords without underscores.IndexError, NameError
ModuleUsing short lower-case letters using underscores.module.py, my_first_module.py
PackageUsing short lowercase words and underscores are discouraged.package, my_first_package

Choosing names

To have readability in your code, choose names which are descriptive and give a clearer sense of what the object represents. A more real-life approach to naming is necessary for a reader to understand the code.

Consider a situation where you want to store the name of a person as a string:

>>> name = 'John William'
>>> first_name, last_name = name.split()
>>> print(first_name, last_name, sep='/ ')
John/ William

Here, you can see, we have chosen variable names like first_name and last_name which are clearer to understand and can be easily remembered. We could have used short names like x, y or z but it is not recommended by PEP 8 since it is difficult to keep track of such short names.

Consider another situation where you want to double a single argument. We can choose an abbreviation like db for the function name:

# Don't
def db(x):
    return x * 2

However, abbreviations might be difficult in situations where you want to return back to the same code after a couple of days and still be able to read and understand. In such cases, it’s better to use a concise name like double_a_variable:

# Do
def double_a_value(x):
    return x * 2

Ultimately, what matters is the readability of your code.

Comments

A comment is a piece of code written in simple English which improves the readability of code without changing the outcome of a program. You can understand the aim of the code much faster just by reading the comments instead of the actual code. It is important in analyzing codes, debugging or making a change in logic. 

Block Comments

Block comments are used while importing data from files or changing a database entry where multiples lines of code are written to focus on a single action. They help in interpreting the aim and functionality of a given block of code.

They start with a hash(#) and a single space and always indent to the same level as the code:

for i in range(0, 10):
    # Loop iterates 10 times and then prints i
    # Newline character
    print(i, '\n')

You can also use multiple paragraphs in a block comment while working on a more technical program. 

Block comments are the most suitable type of comments and you can use it anywhere you like.

Inline Comments

Inline comments are the comments which are placed on the same line as the statement. They are helpful in explaining why a certain line of code is essential.

Example of inline comments:

x = 10  # An inline comment
y = 'JK Rowling' # Author Name

Inline comments are more specific in nature and can easily be used which might lead to clutter. So, PEP 8 basically recommends using block comments for general-purpose coding.

Document Strings

Document strings or docstrings start at the first line of any function, class, file, module or method. These type of comments are enclosed between single quotations ( ''') or double quotations ( """ ).

An example of docstring:

def quadratic_formula(x, y, z, t):
    """Using the quadratic formula"""
    t_1 = (- b+(b**2-4*a*c)**(1/2)) / (2*a)
    t_2 = (- b-(b**2-4*a*c)**(1/2)) / (2*a)

    return t_1, t_2

Whitespaces in Expressions and Statements

In computing, whitespace is any character or sequence of characters which are used for spacing and have an ‘empty’ representation. It is helpful in improving the readability of expressions and statements if used properly.

Whitespace around Binary Operators

When you’re using assignment operators ( =, +=, -=,and so forth ) or comparisons ( ==, !=, >, <. >=, <= ) or booleans ( and, not, or ), it is suggested to use a single whitespace on the either side.

Example of adding whitespace when there is more than one operator in a statement:

# Don't
b = a ** 2 + 10
c = (a + b) * (a - b)

# Do
b = a**2 + 10
c = (a+b) * (a-b)

In such mathematical computations, you should add whitespace around the operators with the least priority since adding spaces around each operator might be confusing for a reader.

Example of adding whitespaces in an if statement with many conditions:

# Don't
if a < 10 and a % 5 == 0:
    print('a is smaller than 10 and is divisible by 5!')

# Do
if a<10 and a%5==0:
    print('a is smaller than 10 and is divisible by 5!')

Here, the and operator has the least priority, so whitespaces have been added around it.

Colons act as binary operators in slices:

ham[3:4]

ham[x+1 : x+2]

ham[3:4:5]

ham[x+1 : x+2 : x+3]

ham[x+1 : x+2 :]

Since colons act as a binary operator, whitespaces are added on either side of the operator with the lowest priority. Colons must have the same amount of spacing in case of an extended slice. An exception is when the slice parameter is omitted, space is also omitted.

Avoiding Whitespaces

Trailing whitespaces are whitespaces placed at the end of a line. These are the most important to avoid. 

You should avoid whitespaces in the following cases—

Inside a parentheses, brackets, or braces:

# Do
list = [1, 2, 3]

# Don't
list = [ 1, 2, 3, ]

Before a comma, a semicolon, or a colon:

x = 2
y = 3

# Do
print(x, y)

# Don't
print(x , y)

Before open parenthesis that initiates the argument list of a function call:

def multiply_by_2(a):
      return a * 2

# Do
multiply_by_2(3)

# Don't
multiply_by_2 (3)

Before an open bracket that begins an index or a slice:

# Do
ham[5]

# Don't
ham [5]

Between a trailing comma and a closing parenthesis:

# Do
spam = (1,)

# Don't
spam = (1, )

To adjust assignment operators:

# Do
variable_1 = 5
variable_2 = 6
my_long_var = 7

# Don't
variable_1    = 5
variable_2    = 6
my_long_var  = 7

Programming Recommendations

PEP 8 guidelines suggest different ways to maintain consistency among multiple implementations of Python like PyPy, Jython or Cython.

An example of comparing boolean values:

# Don't
bool_value = 5 > 4
if bool_value == True:
return '4 is smaller than 5'

# Do
if bool_value:
return '4 is smaller than 5'

Since bool can only accept values True or False, it is useless to use the equivalence operator == in these type of if executions. PEP 8 recommends the second example which will require lesser and simpler coding. 

An example to check whether a list is empty or not:

# Don't
list_value = []
if not len(list_value):
    print('LIST IS EMPTY')

# Do
list_value = []
if not list_value:
    print('LIST IS EMPTY')

Any empty list or string in Python is falsy. So you can write a code to check an empty string without checking the length of the list. The second example is more simple, so PEP encourages to write an if statement in this way.

The expression is not and not ... is are identical in functionality. But the former is more preferable due to its nature of readability:

# Do
if x is not None:
    return 'x has a value'

# Don't
if not x is None:
    return 'x has a value'

String slicing is a type of indexing syntax that extracts substrings from a string. Whenever you want to check if a string is prefixed or suffixed, PEP recommends using .startswith() and .endswith() instead of list slicing. This is because they are cleaner and have lesser chances of error:

# Do
if foo.startswith('cat'):

# Don't
if foo[:3] == 'cat':

An example using .endswith():

# Don't
if file_jpg[-3:] == 'jpg':
    print('It is a JPEG image file')

# Do
if file_jpg.endswith('jpg'):
    print('It is a JPEG image file')

Though there exists multiple ways to execute a particular action, the main agenda of the guidelines laid by PEP 8 is simplicity and readability.

When to Ignore PEP 8

You should never ignore PEP 8. If the guidelines related to PEP8 are followed, you can be confident of writing readable and professional codes. This will also make the lives of your  colleagues and other members working on the same project much easier. 

There are some exclusive instances when you may ignore a particular guideline:

  • After following the guidelines, the code becomes less readable, even for a programmer who is comfortable with reading codes that follow PEP 8.
  • If the surrounding code is inconsistent with PEP.
  • Compatible of code with older version of Python is the priority.

Checking PEP 8 Compliant Code

You can check whether your code actually complies with the rules and regulations of PEP 8 or not. Linters and Autoformatters are two classes of tools used to implement and check PEP 8 compliance.

Linters

It is a program that analyzes your code and detects program errors, syntax errors, bugs and structural problems. They also provide suggestions to correct the errors.

Some of the best linters used for Python code:

  • pycodestyle is a tool to verify the PEP 8 style conventions in your Python code.

You can run the following from the command line to install pycodestyle using pip:

pip install pycodestyle

To display the errors of a program, run pycodestyle in this manner:

pycodestyle my_code.py

my_code.py:1:11: E231 missing whitespace after '{'

my_code.py:3:19: E231 missing whitespace after ')'

my_code.py:4:31: E302 expected 2 blank lines, found 1

  • flake8 is a Python wrapper that verifies PEP 8, pyflakes, and circular complexity.

Type the command to install flake8 using pip:

pip install flake8

Run flake8 from the terminal using the command:

flake8 calc.py 

calc.py:24:3: E111 indentation is not a multiple of two

calc.py:25:3: E111 indentation is not a multiple of two

calc.py:45:9: E225 missing whitespace around operator

You can also use some other good linters like pylintpyflakes, pychecker and mypy.

Autoformatters

An autoformatter is a tool which will format your code to adapt with PEP 8 automatically.One of the most commonly used autoformatter is black.

To install black using pip, type:

pip install black

Remember, you need to have Python 3.6 or above to install black.

An example of code that doesn’t follow PEP 8:

def add(a, b): return a+b

def multiply(a, b):
      return \
        a   * b

Now run black following the filename from the terminal:

black my_code.py

reformatted my_code.py

All done! 

The reformatted code will look like:

def add(a, b):
    return a + b

def multiply(a, b):
    return a * b

Some other autoformatters include autopep8 and yapf. Their work is similar to black.

Conclusion

Since you have now learnt to write a good-quality and readable Python code using PEP 8, you’ll consider it a bliss while working in a project. Though it might be too precise in its nature, it will be useful to everyone working in a particular project by making the code more understandable and making changes and debugging easier.

Let us sum up what we’ve learnt so far:

  • What is PEP 8 and what is its importance.
  • Multiple guidelines for writing PEP 8 compliant code.
  • How to check code against PEP 8 using linters and autoformatters.

If you intend to know more about PEP 8 and its book of guidelines, you can refer to pep8.org or simply enroll for the Python certification course offered by KnowledgeHut.

Priyankur

Priyankur Sarkar

Data Science Enthusiast

Priyankur Sarkar loves to play with data and get insightful results out of it, then turn those data insights and results in business growth. He is an electronics engineer with a versatile experience as an individual contributor and leading teams, and has actively worked towards building Machine Learning capabilities for organizations.

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1 comments

Ramya 16 Aug 2019

NIce article.

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A certification from a reputed accreditation body will validate your skills and make you stand out among your peers.Having an extra certification apart from your UG or PG degree makes you a better fit for the job role in which you have an interest. But before you opt for any certification, you need to understand which programming language will take you where; and the potential benefits of pursuing a certification course of that particular programming language.In this article, you will get to know about the top programming certifications of 2021 and how to achieve them.What are Programming certifications?Programming certifications are exam-oriented, and verify your skill and expertise in that field. Different organizations provide different programming certification exams that define your level, skills, and abilities vis `a vis that programming language. Having a programming certification will give you an edge over other peers and will highlight your coding skills.Most Popular Programming CertificationsC & C++ CertificationsOracle Certified Associate Java Programmer OCAJPCertified Associate in Python Programming (PCAP)MongoDB Certified Developer Associate ExamR Programming CertificationOracle MySQL Database Administration Training and Certification (CMDBA)CCA Spark and Hadoop Developer1. C & C++ CertificationsRegardless of your specialization in your UG or PG courses, clearing a developer-rated certification will not only make your resume stand out from others but also enhance your skills and boost your confidence. We have curated the top-most and popularly available certifications with descriptions that can help you decide which one is appropriate for your career path.C & C++ Certifications: C and C++ are often called the mother of Procedure-oriented and Object-oriented programming languages, which is absolutely true. 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Passing this certification course gives you a logo and a license to authenticate your CCA status.It comprises of topics likeLoad data from HDFS for use in Spark applicationsWrite the results back into HDFS using SparkRead and write files in a variety of file formatsPerform standard extract, transform, load (ETL) processes on data using the Spark APIUse metastore tables as an input source or an output sink for Spark applicationsUnderstand the fundamentals of querying datasets in SparkFilter data using SparkWrite queries that calculate aggregate statisticsJoin disparate datasets using SparkProduce ranked or sorted dataSupply command-line options to change your application configuration, such as increasing available memoryDemand and Benefits: Passing the CCA Spark and Hadoop Developer Exam (CCA175) by Cloudera verifies that you have all the essential skills required to get a job as a Hadoop developer and handle Big data projects. The average salary of a certified CCA Spark and Hadoop Developer with this certification is $ 74,200 per annum.Top companies and industries hiring Certified Spark and Hadoop Developers are Primus Global, IBM, Collabera, CorroHealth, Genpact, Xerox, Accenture, and more.Where to take Training for Certification: KnowledgeHut has extensive courses for those who want to become Big Data experts and want to work as Hadoop developers. It has different courses on Big Data Analytics, Apache Storm, Hadoop Administration, Apache Spark & Scala, Big Data with Hadoop, and more.Who should take the Training (roles) for Certification: Any Big Data developer, graduate & post graduate students, Hadoop developer or computer science aspirant - who wants to make a career in Big data development or start his/her career as a Big Data or Hadoop project developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification: $ 295Application fee for certification: $ 295Exam fee for certification: $ 295Retake fee for certification: Within 30 to 60 minutes of exam completion, Cloudera will send a scorecard mail with a pass or fail status. If the candidate fails the exam, then they have to wait for 30 days for another try.  Cloudera gives additional discounts on retakes.ConclusionWhether you are starting your career as a coder or are an experienced programmer looking to grow in the industry, having a certification and proper knowledge of any popular programming language is one of the most proven ways to elevate your programming career.  We trust that this article will help you to understand your area of interest. Choose the programming language you wish to make a career in, wisely. This would also depend on your pre-existing knowledge. If you aren't sure which resource will be more informative for doing your certification as per your area of interest, KnowledgeHut (https://www.knowledgehut.com/) has all the support and expert trainers who can guide you, from start to finish—that is in clearing the exam and helping you gain sound knowledge of your preferred subject.Receiving a programming certification is an added bonus which will make you stand out from the rest. Proper training from an institute such as KnowledgeHut will help you gain skills that are relevant and in demand in the industry.
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Top-Paying Programming Certifications for 2021

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Top IT Certifications for Java Developers in 2021

Programming languages are at the heart of computer science and software development. They help developers write efficient code for developing digital solutions through applications and websites. Programming helps in automating, maintaining, assembling, and measuring the processed data.  Java is one such popular programming language. It is a robust, high-level, general-purpose, pure object-oriented programming language developed by Sun Microsystems (now part of Oracle). James Gosling is the creator of Java which was earlier named Oak. Java ranks high in the top programming languages list and is one of the most extensively used software development platforms. It is well suited to developing software solutions and other innovative projects and simulations.  Since Oracle acquired Sun Microsystems in January 2010, they have been responsible for the further development of the Java platform. All the mentioned top Java certifications verify a specific expertise level and knowledge of the Java platform highlighting particular domains. Without further due, let us now dig into the top 5 Java certifications and their details. About Oracle’s Java CertificationsOrganizations and industries consider certifications as proof of knowledge, especially when the certifications are from a recognized body or firm. Aspirants and professionals looking for possibilities in the Java development domain can avail of a plethora of benefits through the certifications mentioned in this article. There are six levels of Oracle Java Certification based on job roles, skills, and responsibilities: Oracle Certified Junior Associate (OCJA) Oracle Certified Associate (OCA) Oracle Certified Professional (OCP) Oracle Certified Specialist (OCS) Oracle Certified Expert (OCE) Oracle Certified Master (OCM) Among them, the top five Java certifications that are in demand for the year 2021 are – 1. Oracle Certified Associate Java Programmer OCAJPIt is the preliminary and most basic certification provided by Oracle for Java. It helps you gain fundamental understanding of Java programming and build a foundation in Java and other general programming concepts. There are two subcategories in this certification – OCAJP Java Standard Edition 8 (OCAJP 8) and  OCAJP Java Standard Edition 11 (OCAJP 11) OCAJP8 comprises of topics like  Creating and Using Arrays Handling Exceptions Java Basics Using Loop Constructs Using Operators and Decision Constructs Working with Inheritance Working with Java Data Types Working with Methods and Encapsulation Working with Selected classes from the Java API OCAJP11 comprises of topics like Applying Encapsulation Creating and Using Methods Creating Simple Java Programs Describing and Using Objects and Classes Handling Exceptions Java Technology and the Java Development Environment Programming Abstractly Through Interfaces Reusing Implementations Through Inheritance Understanding Modules Using Operators and Decision Constructs Working with Java Arrays Working with Java Primitive Data Types and String APIs Demand and Benefits: Having an OCAJP certification verifies that the programmer or the aspirant has all the necessary and essential skills to become an expert Java developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The entry-level salary of a junior Java developer with this certification is $ 3670 per annum; when the candidate gathers two to three years of experience, the average salary hikes to $ 5430 annually.   (Source: Glassdoor) Top companies and industries hiring Oracle Certified Associate Java Programmers are Smart Monitor Pvt. Ltd., Fiserv, Micron Semiconductor Asia Pvt. Ltd., and more. Where to take Training for Certification: KnowledgeHut has a fascinating course, designed for beginners in Java programming. It offers hands-on learning with 40 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to be a Java developer or start his/her career as a Java programmer can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 2) Oracle Certified Professional Java Programmer OCPJPIt is a professional-level certification program provided by Oracle for Java developers. It verifies the candidates' knowledge and professional expertise. Using this certification, aspirants and other hard-core Java programmers can distinguish themselves from those Java professionals who are not certified. It comes in the second level of Oracle's Java Certification list. There are two subcategories of this certification – OCPJP Java Standard Edition 8 (OCPJP 8) and  OCPJP Java Standard Edition 11 (OCPJP 11) This certification is preferable if someone has professional experience with Java or has already worked for some years in Java technology.  OCPJP8 comprises of topics like: Advanced Class Design Building Database Applications with JDBC Concurrency Exceptions and Assertions Generics and Collections Java Class Design Java File I/O (NIO.2) Java I/O Fundamentals Java Stream API Lambda Built-in Functional Interfaces Localization Use Java SE 8 Date/Time API OCPJP11 comprises of topics like: Annotations Built-in Functional Interfaces Concurrency Database Applications with JDBC Exception Handling and Assertions Functional Interface and Lambda Expressions Generics and Collections I/O (Fundamentals and NIO.2) Java Fundamentals Java Interfaces Java Stream API Lambda Operations on Streams Localization Migration to a Modular Application Parallel Systems Secure Coding in Java SE Application Services in a Modular ApplicationDemand and Benefits: Once you are a certified Professional Java Programmer (OCPJP), you can switch to better salary slabs and organizations that hire senior Java developers. This certification also helps in getting internal promotions as Java developers in different organizations and firms. The average salary of a certified professional Java developer is $ 5300 - $ 8610 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, Morgan Stanley, Chetu, Mphasis, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java developers and professionals for learning intermediate Java topics. It has hands-on learning with 32 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any Java programmer who wants to apply for a senior Java developer's role or start his/her career as a Java programmer can opt for this professional certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.3. Oracle Certified Expert - Web Component Developer OCEWCDIt is an intermediate-level course offered by Oracle for Java web developers. The Oracle Certified Expert Web Component Developer is for web developers who want to write web applications using Java. Through this course, they can prove their expertise in developing web apps using JSP and Servlet technologies. It verifies your expertise in Servlet 3.0 and helps in creating dynamic Web content and Web services.  It comprises of topics like Understanding Java EE Architecture Managing Persistence using JPA entities and Bean Validation Implementing business logic using EJBs Using Java Message Service API Implement SOAP Services using JAX-WS and JAXB APIs Creating Java Web Applications using Servlets and JSPs Implementing REST Services using JAX-RS API Creating Java Applications using WebSockets Developing Web Applications using JSFs Securing Java EE 7 Applications Using CDI Beans Demand and Benefits: You can opt for this course once you are a certified Professional Java Programmer (OCPJP) or certified associated Java programmer. This certification course will help you get a job in organizations having rigorous work in Servlet, Java Server Page, JSF, and web microservices. The average salary of a certified professional Java developer is $ 8,850 - $ 11,930 per annum. Top companies and industries hiring Oracle Certified Web Component Developers are Amdocs, IBM, Oracle, Capgemini, SAP, Shine, Byjus, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java web developers (. It has hands-on learning with instructor-led online lectures and live projects. Apart from this, you can get online training from Oracle University as wellWho should take the Training (roles) for Certification: Any programmer or computer science aspirant who wants to settle as a Java web developer or start his/her career as a Java web content and web service developer can opt for this certification course. As a prerequisite, you have to pass the OCPJP to opt for this certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 4. Oracle Certified Professional Java Application Developer (OCPJAD)It is an advanced-level course offered by Oracle for Java application developers. The Oracle Certified Professional Java Application Developer (OCPJAD) is for software developers who want to write different applications and automation tools using Java. Through this course, developers can prove their expertise and abilities to develop and deploy applications through Java Enterprise Edition 7. OCPJAD is ideal for desktop application developers, frontend + backend app developers, software engineers, and application architects. It comprises of topics like Creating Batch API Developing CDI Beans Concepts of Concurrency Creating Java Applications with Web-Sockets Creating Java Web Applications with JSPs Developing Java Web Applications with Servlets Developing Web Applications with JSFs Implementing Business Logic with EJBs Performing REST Services with JAX-RS API Implementing SOAP Services with JAX-WS and JAXB APIs Java EE 7 system architecture Java EE 7 Security Techniques Java Message Service API Managing Persistence with JPA Entities and Bean-ValidationDemand and Benefits: Once you pass the Certified Professional Java Application Developer (OCPJAD), you can seek employment in organizations that work on critical application development and command higher salaries. This professional certification will give you exposure to develop APIs, implementing business logic using EJBs, create message services, and apply security systems. The average salary of a certified professional application developer is $ 9,800 - $ 13,910 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, NetSuite Inc., SAP, Cognizant, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity with hands-on learning exposure and live projects. Apart from this, you can get online training from Oracle University as well. Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to become a certified Java application developer or move to the specialized sector of API development using REST, security architect or software engineer can opt for this certification course. As a prerequisite, you should have passed the OCAJP certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.5. Oracle Certified Master Java Enterprise Architect (OCMJEA)Large-scale development and service firms have different critical applications and systems to develop, manage, and maintain. Such systems require full-stack developers and specialized professionals with proven skills. Such organizations and MNCs hire only highly experienced professionals and specialists who can supervise the extensive operation, architect the defects, and define & develop systems as per requirements. The Oracle Certified Master Java Enterprise Architect (OCMJEA) is one of the most prestigious Java certifications a Java developer can achieve.  It comprises of topics like Architect Enterprise Applications through Java EE Developing Applications for the Java EE 6 Developing Applications for the Java EE 7 Developing Applications with Java EE 6 on WebLogic Server 12c Java Design Patterns Java EE 6: Develop Business Components with JMS & EJBs Java EE 6: Develop Database Applications with JPA Java EE 6: Develop Web Services with JAX-WS & JAX-RS Java EE 7: New Features Java SE 7: Develop Rich Client Applications Java SE 8: Programming Java SE 8 Fundamentals Object-Oriented Analysis and Design Using UML, etc. Demand and Benefits: Once you pass the Certified Master Java Enterprise Architect course, you get the essential skills and understanding of how to execute application development on an enterprise level. Such an experienced professional gains full-stack Java development skills. They get hired with the responsibility of undertaking Java projects from the very start to their final delivery. Many Certified Master Java Enterprise Architects work as managers or senior managerial roles in industries and firms. The average salary of a certified professional application developer is $ 14,000 - $ 19,210 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are IBM, Oracle, Microsoft, HCL, Capgemini, NetSuite Inc., SAP, Cognizant, Atlassian, etc. Where to take Training for Certification: KnowledgeHut has a fascinating Java course  with hands-on learning exposure and a live project. Apart from that, a professional can train himself through ILT (Instructor-Led-in-Class), Learning Subscription, TOD (Training on Demand), LVC (Live Virtual Class), or classes delivered by Oracle Authorized Education Center . Other Oracle Authorized Partner Oracle Academy, Oracle University Training Center, or Oracle Workforce Development Program can also benefit and train you in this course.  Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to move to a senior role in the enterprise-level or want to become a manager or team lead can opt for this certification course. As a prerequisite, you need to have passed the OCPJP certification.  Course fees for Certification:  $248 Application fee for certification: $ 248 Exam fee for certification: $ 248 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. Java is an evergreen programming language and is here to stay, at least for the next couple of decades. A vast community of professionals and entry-level aspirants enjoy the benefit of this pure object-oriented, class-based, multi-paradigm, high-level programming language. Java Certification requires proper training.KnowledgeHut has the required infrastructure and quality education faculty, both online and offline, to train aspirants for these Oracle Certifications. It caters to well-structured, industry-oriented Java certification training, explicitly designed to serve the candidates according to the latest industry needs. Getting proper training from KnowledgeHut will help aspirants master core knowledge of Java plus equip themselves with the industry standards to manage large projects. 
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Top IT Certifications for Java Developers in 2021

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Best Python Certifications of 2021

Programming is always at the core of computer science and Information Technology. Every year millions of programmers graduate with a degree and look for opportunities in the job market. The demand for programmers is growing exponentially, and this demand is not going anytime soon. Python was released by Python Software Foundation in 1991, and in just a few years, has become the most popular and widely used programming language in various disciplines.Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, AI, robotics, drone systems, developing cyber-security tools, mathematics, system scripting, etc.According to TIOBE index, Python ranks second among all other programming languages. KnowledgeHut has some fascinating advanced-level courses on Python, such as Machine Learning using Python and Artificial Intelligence using Python.Once you gain expertise in writing Python programs, candidates can start learning advanced-level Python libraries and modules such as Pandas, SciPy, NumPy, Matplotlib, etc. There are different options one can explore after learning Python. These are data analysis, machine learning, cybersecurity, automation, web scraping, etc.Top Python Certifications of 2021Certified Entry-Level Python Programmer (PCEP) Certified Associate in Python Programmer (PCAP) Introduction to Programming Using Python by Microsoft Certified Professional in Python Programming 1 & 2 (PCPP 1 & 2) Certified Expert in Python Programming (PEPP) During the course of your Python certification training and exam preparation, you will develop different real-world projects and get familiar with case studies. Also, there will be hands-on lab experiences in Python programming. In this article, you will get to know the top five Python certifications of 2021 that can give you the launchpad you need to embark on a successful career.   1. Certified Entry-Level Python Programmer (PCEP): The PCEP is an entry-level Python certification. To enroll in this course, you need to have a basic understanding of how procedural programming works. Also, some knowledge of flowcharts and algorithm creation will benefit you. Through this certification, an aspirant can gain the core and fundamental understanding of Python. This certification from the Python Institute will make you proficient in Python programming and help you become a Python certified professional. Aspirants and professionals can choose Python as a career option/path and climb the Python Institute’s certification ladder from associate to professional.PCEP comprises of topics like Basic formatting and outputting methods Handling Boolean values Compilation vs. interpretation Constants, Variables and Variable naming conventions Defining user-defined functions Fundamentals of computer programming Inputting and converting Data Logical vs. bitwise operations in Python Looping and control statements Lists New data aggregates: Tuples and Dictionaries The assignment operator Primary kinds of data and numerical operators Rules governing the building of expressions Working with multi-dimensional arrays Different slicing operations Demand and Benefits: Having a PCEP certification verifies that the programmer or the aspirant has knowledge of all the necessary and fundamental Python concepts. The course also covers all the syntax and semantics of different Python constructs & data types offered by the language. This course brings crisp knowledge on general coding techniques using standard language infrastructure and basic programming skills using Python. The average entry-level salary of a Python programmer with this certification will be $ 5660 per annum. Top companies and industries hiring PCEP are Philips, Cataleya Pvt. Ltd., Deloitte, Zynga, Mphasis, VMware, etc.Where to take Training for Certification: Python Institute has all the study resources you need to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut  that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to learn Python or start an internship or entry-level job as Python programmer can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 295 Application fee for certification: $ 295 Exam fee for certification: $ 295 Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit on the number of times a candidate may retake the exam.2. Certified Associate in Python Programmer (PCAP):PCAP is another important second-level or associate-level certification exam for Python. This course and certification will give you the confidence to measure your skill and complete the Python-based coding tasks. It also facilitates competing for competitive coding sessions. This course also comprises the essential notions and concepts related to object-oriented programming. With this associated-level certification, you can stand unique in the competitive job market. PCAP comprises of topics like Basic formatting and outputting methods Python basics Using Boolean values Compilation vs. interpretation Variables and variable naming conventions Defining and using functions Fundamentals of computer programming Fundamentals of OOP  How to use OOPs in the Python programming language Generators and closures Inputting and converting of data Logical vs. bitwise operations Looping and control statements File processing for Python developers Name scope issues New data aggregates: tuples and dictionaries Primary kinds of data and numerical operators Python modules Inheritance in Python Rules for creating expressions Working with multi-dimensional arrays Strings, lists, and other Python data structures The assignment operator The concept of exceptions and implementation Demand and Benefits: Having a PCAP certification verifies that the programmer or the aspirant has all the necessary and essential concepts of intermediate-level Python programming. The course also covers all the fundamental concepts of different Python constructs & fundamentals of OOP. This course brings crisp knowledge on general coding techniques using standard language infrastructure and basic programming skills using Python. The approximate salary of a Python programmer with this certification will be $7000 to $11,262 per annum. Top companies and industries hiring PCAP are CareCentrix, Accenture, Deutsche Bank, Collabera, NetApp, Capgemini, Tech Mahindra, Myntra, etc. Where to take Training for Certification: Python Institute (https://pythoninstitute.org/free-python-courses/) has all the study resources you need to prepare for this examination. You can also get a comprehensive training by enrolling for the Python course offered by KnowledgeHut (https://www.knowledgehut.com/programming/python-programming-certification-training) that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to build a career in Python or pursue an associate-level job as a Python programmer or developer, can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 295 Application fee for certification: $ 295 Exam fee for certification: $ 295 Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam. 3. Introduction to Programming Using Python by MicrosoftIt is another popular entry-level Python certification by Microsoft (https://docs.microsoft.com/en-us/learn/certifications/exams/98-381). This certification covers all the syntax, data types, and basic understanding of Python. It also teaches how to logically solve any problem using Python constructs. Candidates wanting to enroll for this course are expected to have had some instruction or hands-on experience of approximately 100 hours with the Python programming language, including debugging skills, logic development, understanding conditional & decision-making statements, and maintaining well-formed well documented Python code. Microsoft’s Introduction to Programming Using Python comprises of topics like Basics of Python Using Boolean values Fundamentals of computer programming Interpretations Variables and variable naming conventions Defining and using functions Indexing and slicing operations Type conversions Basic formatting and outputting Data Types and Operators Control Flow with Decisions and Loops Construct Data structures Jump Statements Perform Input and Output Operations Document and Structure Code Comments and white-spaces Perform Operations Using Modules and Tools Demand and Benefits: Having a Microsoft certification verifies that the Python programmer or the aspirant has all the necessary and fundamental Python concepts. The course also covers all the syntax and semantics of different Python constructs & data types offered by the language. Anyone with this certification will have a better understanding of core Python, and the candidate can stand out in the competitive exams from the rest. The average entry-level salary of a Python programmer with this certification will be $ 5660 per annum. Top companies and industries hiring Python professionals with this credential are Cataleya Pvt. Ltd., Zynga, VMware, Mphasis, Deloitte, Capgemini, etc. Where to take Training for Certification: Microsoft has a paid five-day instructor-led course to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to learn Python or start an internship or entry-level job as Python programmer, can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 127 Application fee for certification: $ 127 Exam fee for certification: $ 127 Retake fee for certification: Exam retake is free. If the candidate fails to achieve a passing score on the first attempt, he/she must wait 24 hours before retaking the exam. 4. Certified Professional in Python Programming 1 & 2 (PCPP 1 & 2):Once you sound knowledge of the core concepts of Python or have 3 to 5 years of experience in Python programming, you may prepare for professional Python certification. Certified Professional in Python Programming 1 certifications will reflect your experience and programming skills in the following areas: Text File Handling GUI-based Programming Encapsulation Inheritance Advanced Object-Oriented Programming PEP conventions Metaprogramming Communicating with a program's environment Using Libraries and Modules Importing math, science, and engineering modules Having this globally recognized credential will make you stand out in a competitive job market. Many recruiting agencies and firms are looking for professional Python programmers who can develop and deploy applications. Certified Professional in Python Programming 2 (PCPP2) is another advanced-level professional certification course offering proficiency in Python-MySQL database handling. Certified Professional in Python Programming 2 certification will reflect your experience and programming skills in the following areas: Basic directory structure CRUD operations Design patterns Observer and Proxy Singleton and State Design Template Method Model-View-Controller using Python Multiprocessing, threading, subprocess, and multiprocessor synchronization Relational database management using Python MySQL and SQL commands Sharing, storing and installing packages Network programming in Python Application testing techniques and principles Demand and Benefits: Having a PCPP certification verifies that the Python developer has all the necessary and essential skills of a professional Python programmer. The course covers all the advanced object-oriented programming concepts, GUI programming, etc. This course brings crisp knowledge for experienced professionals to make them stand out in the software development industry. The approximate salary of a Python programmer with this certification will be $ 12,053 to $ 14,700 per annum. Top companies and industries hiring PCPP certified professionals are Dell, Accenture, SG Analytics, HCL, Oracle, Capgemini, Tech Mahindra, Flipkart, etc. Where to take Training for Certification: Python Institute has all the study resources you need to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut that has 32 hours of instructor-led training covering the advanced programming concepts like database handling, OOPs, logical layout, data visualization, etc. Who should take the Training (roles) for Certification: Any professional, programmer, or experienced Python developer - who wants to settle as a senior Python developer or pursue an experienced-level job as a Python programmer or developer can opt for this certification course. The candidate should have the Certified Associate in Python Programmer (PCAP) certification or few years of work experience in Python. Course fees for Certification: $ 195 Application fee for certification: $ 195 Exam fee for certification: $ 195  Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam. 5. Certified Expert in Python Programming (CEPP):This Python certification tag is for experts who complete all the OpenEDG Python Institute's Programming certification program (PCAP-31-xx, PCPP-32-1-xx, and PCPP-32-2-xx exams). It is the most advanced credential a Python developer can achieve from the Python Institute. Having this globally recognized credential will verify your expertise in Python programming. It highlights expertise in the universal concepts of Python programming. Also, this certification showcases the skills in resolving typical implementation challenges on different verticals of Python. Demand and Benefits: Having a CEPP certification verifies that the Python developer has industry level expertise in Python. This certification designates that the candidate has covered all the topics from basics to advance object-oriented programming concepts, GUI programming, etc. Using this certification, one can apply for a senior software development role, Python developer’s role, team lead, agile project management lead, and other senior job roles. Many professionals switch their careers to Big Data, Data Analytics, Machine learning, and deep learning after completing this certification. The approximate salary of a Python programmer with this certification will be $ 17,350 to $ 39,945 per annum. Top companies and industries hiring CEPPs are Amazon, Tesla, HSBC, Google, HCL, Oracle, Capgemini, Qualcomm, 6sense, Vitrana, and other top service-based companies. Where to take Training for Certification: Python Institute has all the study resources you need to prepare for PCAP-31-xx, PCPP-32-1-xx, and PCPP-32-2-xx examination. Once a candidate has passed all the certifications, he/she becomes recognized as an Open EDG Python Institute Certified Expert in Python Programming (CEPP). Who should take the Training (roles) for Certification: Any professional, Python expert, or senior Python developer, who wants to settle as a team lead or pursue an experienced-level job profile can opt for these certifications to reach at this level.  Course fees for Certification: $ 295 + $ 295 + $ 195 Application fee for certification: $ 295 + $ 295 + $ 195 Exam fee for certification: $ 295 + $ 295 + $ 195  Retake fee for certification: There is no retake fee Conclusion We trust this article gave you a better insight into different Python certifications! Whether you are starting out as a coder, or are an experienced Python programmer looking at making a splash in the industry, having a Python certification and proper knowledge of Python will elevate your programming career. Python is one of the top programming languages that can help you land different jobs in web development, app development, data science, cybersecurity, networking, web scraping, robotics, IoT, etc. If you aren't sure which online resource will be more informative for your Python certification, KnowledgeHut (https://www.knowledgehut.com/) has all the study materials and expert trainers who will help you reach the pinnacle of Python expertise. Receiving a Python certification, apart from academics and degrees, will make you stand out from the rest. So, start preparing for one today! 
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Best Python Certifications of 2021

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