Differences Between an Interpreter and a Compiler

Some advantages of Python

Python is simple to use, but it is a real programming language, offering much more structure and support for large programs than shell scripts or batch files can offer. On the other hand, Python also offers much more error checking than C, and, being a very-high-level language, it has high-level data types built in, such as flexible arrays and dictionaries. Because of its more general data types Python is applicable to a much larger problem domain than Awk or even Perl, yet many things are at least as easy in Python as in those languages.

Python allows you to split your program into modules that can be reused in other Python programs. It comes with a large collection of standard modules that you can use as the basis of your programs — or as examples to start learning to program in Python. Some of these modules provide things like file I/O, system calls, sockets, and even interfaces to graphical user interface toolkits like Tk.

Python is an interpreted language, which can save you considerable time during program development because no compilation and linking is necessary. The interpreter can be used interactively, which makes it easy to experiment with features of the language, to write throw-away programs, or to test functions during bottom-up program development. It is also a handy desk calculator.

Python enables programs to be written compactly and readably. Programs written in Python are typically much shorter than equivalent C, C++, or Java programs, for several reasons:

• the high-level data types allow you to express complex operations in a single statement;

• statement grouping is done by indentation instead of beginning and ending brackets;

• no variable or argument declarations are necessary.

Python is extensible: if you know how to program in C it is easy to add a new built-in function or module to the interpreter, either to perform critical operations at maximum speed, or to link Python programs to libraries that may only be available in binary form (such as a vendor-specific graphics library). Once you are really hooked, you can link the Python interpreter into an application written in C and use it as an extension or command language for that application.

Programming-Language features of Python

• A variety of basic data types are available: numbers (floating point, complex, and unlimited-length long integers), strings (both ASCII and Unicode), lists, and dictionaries.
• Python supports object-oriented programming with classes and multiple inheritance.
• Code can be grouped into modules and packages.
• The language supports raising and catching exceptions, resulting in cleaner error handling.
• Data types are strongly and dynamically typed. Mixing incompatible types (e.g. attempting to add a string and a number) causes an exception to be raised, so errors are caught sooner.
• Python contains advanced programming features such as generators and list comprehensions.
• Python's automatic memory management frees you from having to manually allocate and free memory in your code.

Then, run the file by typing the following command: 

(For Linux and Mac) 

python3 hello_world.py 

(For Windows)

python3 hello_world.py 

This line instructs your Python interpreter to execute the command you just wrote. You should see the correct output

Using the Python Interpreter

The Python interpreter is usually installed as /usr/local/bin/python3.11 on those machines where it is available; putting /usr/local/bin in your Unix shell’s search path makes it possible to start it by typing the command: python3 to the shell.

On Windows machines where you have installed Python from the Microsoft Store, the python3.11 command will be available. If you have the py.exe launcher installed, you can use the py command.

Typing an end-of-file character (Control-D on Unix, Control-Z on Windows) at the primary prompt causes the interpreter to exit with a zero exit status. If that doesn’t work, you can exit the interpreter by typing the following command: quit().

Interactive Mode

When commands are read from a tty, the interpreter is said to be in interactive mode. In this mode it prompts for the next command with the primary prompt, usually three greater-than signs (>>>); for continuation lines it prompts with the secondary prompt, by default three dots (...). The interpreter prints a welcome message stating its version number and a copyright notice before printing the first prompt:

python3.11
Python 3.11 (default, April 4 2021, 09:25:04)
[GCC 10.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>

Declaration of Variables

Python Literals

Literals are representations of fixed values in a program. They can be numbers, characters, or strings, etc. For example, 'Hello, World!', 12, 23.0, 'C', etc.

Literals are often used to assign values to variables or constants. For example,

site_name = 'santechz.com'

In the above expression, site_name is a variable, and 'santechz.com' is a literal.

Python Numeric Literals

Numeric Literals are immutable (unchangeable). Numeric literals can belong to 3 different numerical types: Integer, Float, and Complex.

Python Boolean Literals

There are two boolean literals: True and False.

For example,

result1 = True  

Here, True is a boolean literal assigned to result1.

String and Character Literals in Python

Character literals are unicode characters enclosed in a quote. For example,

some_character = 'S'

Here, S is a character literal assigned to some_character.

Similarly, String literals are sequences of Characters enclosed in quotation marks.

For example,

some_string = 'Python is fun' 

Here, 'Python is fun' is a string literal assigned to some_string.

Special Literal in Python

Python contains one special literal None. We use it to specify a null variable. For example,

value = None

print(value)

# Output: None

Here, we get None as an output as the value variable has no value assigned to it.

Comments

Comments are lines that exist in computer programs that are ignored by compilers and interpreters. Including comments in programs makes code more readable for humans as it provides some information or explanation about what each part of a program is doing.

Depending on the purpose of your program, comments can serve as notes to yourself or reminders, or they can be written with the intention of other programmers being able to understand what your code is doing.

Comments in Python begin with a hash mark (#) and whitespace character and continue to the end of the line.

A Python multiline comment consists of a group of text enclosed in a delimiter (""") at each end. To avoid syntax errors, make sure to indent the first """ correctly. These are used when the comment content fits into multiple lines.

Example:

# Print Python to console
print("Python")

"""
This is a multiline comment
This is the next line.
"""
print("Language")

Indenting Code

A block is a group of statements in a program or script. Usually it consists of at least one statement and of declarations for the block, depending on the programming or scripting language. A language which allows grouping with blocks, is called a block structured language.

Python programs get structured through indentation, i.e. code blocks are defined by their indentation.

This principle makes it easier to read and understand other people's Python code. 

All statements with the same distance to the right belong to the same block of code, i.e. the statements within a block line up vertically. The block ends at a line less indented or the end of the file. If a block has to be more deeply nested, it is simply indented further to the right. 

Various Operators in Python

Comparison Operators

Bitwise Operators

Python Type Conversion

In programming, type conversion is the process of converting data of one type to another. For example: converting int data to str.

There are two types of type conversion in Python.

• Implicit Conversion - automatic type conversion
• Explicit Conversion - manual type conversion

Python Implicit Type Conversion

In certain situations, Python automatically converts one data type to another. This is known as implicit type conversion.

Example 1: Converting integer to float

Let's see an example where Python promotes the conversion of the lower data type (integer) to the higher data type (float) to avoid data loss.

integer_number = 123
float_number = 1.23

new_number = integer_number + float_number

# display new value and resulting data type
print("Value:",new_number)
print("Data Type:",type(new_number))

Value: 124.23
Data Type: <class 'float'>

In the above example, we have created two variables: integer_number and float_numberof int and float type respectively.

Then we added these two variables and stored the result in new_number.

As we can see new_number has value 124.23 and is of the float data type.

It is because Python always converts smaller data types to larger data types to avoid the loss of data.

Explicit Type Conversion

In Explicit Type Conversion, users convert the data type of an object to required data type.

We use the built-in functions like int(), float(), str(), etc to perform explicit type conversion.

This type of conversion is also called typecasting because the user casts (changes) the data type of the objects.

Example 2: Addition of string and integer Using Explicit Conversion

num_string = '12'
num_integer = 23

print("Data type of num_string before Type Casting:",type(num_string))

# explicit type conversion
num_string = int(num_string)

print("Data type of num_string after Type Casting:",type(num_string))

num_sum = num_integer + num_string

print("Sum:",num_sum)
print("Data type of num_sum:",type(num_sum))

Output:

Data type of num_string before Type Casting: <class 'str'>
Data type of num_string after Type Casting: <class 'int'>
Sum: 35
Data type of num_sum: <class 'int'>

In the above example, we have created two variables: num_string and num_integer with str and int type values respectively. Notice the code,

num_string = int(num_string)

Here, we have used int() to perform explicit type conversion of num_string to integer type.

After converting num_string to an integer value, Python is able to add these two variables.

Finally, we got the num_sum value i.e 35 and data type to be int.