Cheat Sheet Python



Python is a high level, general purpose, and multi-paradigm programming language. Python is interpreted instead of compiled. Python was designed by Guido Van Rossum, a Dutch Programmer. It first appeared in the year 1990. The file extensions of Python can be .py, .pyc, .pyo, .pyd, .pyw, .pyz etc. Python is imperative, object-oriented, procedural, functional and reflective. Python has automatic memory management and dynamic typing system features. Python supports interpretation in multiple or cross-platform operating systems. Python is open source software and has a large community for its significant development.

Python is licensed by the Python Software Foundation License. Python was influenced by languages such as Ruby, JavaScript, CoffeeScript, Groovy, Swift etc. Python version 2.0 was first released in the year 2000 which includes some major feature improvements such as garbage collector (cyclic detection), Unicode character support. Python version 3.0 was released in the year 2008. Python supports different functional programming features such as filter( ), reduce( ) and map() methods to perform some streaming and parallel operations in a shorter time. Python is easily readable, well formatted and easier to write the code which is having less punctual syntaxes and English like keywords.

Commands and Content on Cheat sheet Python

Python has an extensive library, scalable, extendable, interactive and contains many inbuilt methods to compute common operations. Below are the Cheat sheet Python commands mentioned which perform different kinds of operations:

-oTo generate optimized bytecode
-cTo add the current directory to execute the python code
-sTo exclude imports while starting up the python code execution
-dTo show the output in debugging mode
-xTo disable built-in class-based exception (deprecated since 1.6)
fileTo run a python script from the given file
-mTo execute the python file contents as the main module
-iTo enter into interactive mode after script or command execution
-ITo enter into an isolated mode
-OTo remove assert statements
-OOTo discard doc strings
-RTo turn on hash randomization
-uTo force standard output and error streams to be unbuffered
-WTo give warning control message
-JReserved for use in Jython

Identifiers:- It is used to identify any function, class, variable, object or module etc., The valid identifier in python starts with any of a-z, A-Z, 0-9 or (_).

Reserved keywords: – and, exec, not, assert, finally, or, break, for, pass, class, form, print, continue, global, raise, def, if, return, del, import, try, elif, in, while, else, is, with, except, lambda and yield.

Operators: – The different types of operators in Python are Arithmetic Operators, Comparison (Relational) Operators, Assignment Operators, Logical Operators, Bitwise Operators, Membership Operators, and Identity Operators. The different types of numerical operators are int (signed and unsigned), long, float and complex numbers.

Loops: – The looping operators in Python are while, for and nested. The nested loops are while, for, do…while etc. The different loop control statements are break, continue and past statements.

Mathematical Functions: – The different functions available in python’s math module are

fabs(Arg)Returns absolute value of arg
ceil(Arg)Returns smaller integer > or = to arg
copysign(arg1, arg2)Returns arg1 with the sign of arg2
floor(Arg)Returns largest number < or = arg
modf(Arg)Returns integer and fractional parts of arg
trunk(Arg)Returns truncated value of arg
exp(Arg)Returns an exponential value of arg
log10(Arg)Returns logarithmic value to base 10
sqrt(Arg)Returns square root value of arg
cos(Arg)Returns the cosine value of arg
sin(Arg)Returns the sine value of arg
tan(Arg)Returns the tangent value of arg
sinh(Arg)Returns the hyperbolic sine value of arg
tanh(Arg)Returns the hyperbolic tangent value of arg
cosh(Arg)Returns the hyperbolic cosine value of arg
erf(Arg)Returns the error function of arg
isfinite(Arg)Returns true if finite else returns false
isinf(Arg)Returns true if infinity else returns false
isnan(Arg)Returns true if not a number else returns false
gcd(arg1, arg2)Returns Greatest Common Divisor of arg1 and arg2 values

 Free Tips and Tricks of using Cheat Sheet Python Commands:-

  1. The python scripts can be run using command line window and running the command as python <>
  2. The cheat sheet Python programs can be interpreted by running python in the command window and entering the commands one after the other.
  3. The conditional expressions can be used to write the conditional statements to execute the required computations.
  4. Lambda functions can be used to parallelize or streamline the complex processing list operations or a large number of multiple or concurrent operations.
  5. Decorators are the latest feature to wrap the functions around a function where the function can be passed as an argument to another function which returns a value and that will be passed as an argument to the function.
  6. In cheat sheet python, Boolean will be taken as an integer.
  7. In a few cases, the IDE can’t be used for the purpose of debugging where the cheat sheet python commands line window can be used to debug the python code. In such cases, the pdb module can be used which is in built-in python library.
  8. A shell command can be run from a python program or python file by using system() function in os class by calling command os.system(arg) where arg is the command which is defined as String.
  9. The filter function in the python creates the list for the elements which return only true.
  10. The map function will be applied to all of the items of an input list.
  11. The reduce function is used to apply some computation on a list and returns a value.

Conclusion – Cheat Sheet Python

Python is easy to use and its syntax is easier to remember and code the programs easily. Python can be used in web development technologies by using different frameworks and technologies which support python. Django web application framework is built on top of Python which follows MVT architectural pattern.

Python will be used in terms of achieving a speed of execution for some computations in a few modern computing applications to achieve far better results compared to the other programming languages to achieve performance and high-end results.

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