Python Intermediate Summary

Summary of Python Intermediate Fundamentals

This page covers all main points throughout the Python intermediate fundamentals.

Python Speed Performance (more)

• code performance is vital in larger projects
• background processes impact code execution
• processing time is the CPU performance measurement
• four built-in packages: time, datetime, timeit, and cProfile

Python Intermediate (more)

• local variables work only in the local scope
• global variables work everywhere
• Python can assign multiple variables
• naming variables is vital (PEP8)
• possible to import multiple modules (not recommended)
• possible to import multiple functions
• asterisk (*) can import all (not recommended)

Python Intermediate Data Types (more)

• casting converts one data type to another – e.g. “float(4)”
• slicing cuts data types partially – e.g. a[2:15]
• “split()” separate text and outputs a list
• “strip()” removes empty spaces (beginning or end)
• “lower()” changes letters to all lowercase
• “upper()” changes letters to all uppercase
• “min()” & “max()” outputs lowest and maximum number, respectively
• “pow()” refers to the power of a number
• “abs()” produces the absolute value of a number
• indexing provides access to a specific item in a data type

• “sort()” arranges items in lists
• “len()” outputs the number of items in data types
• “count()” outputs the specific number of items in data types

Adding items

• “in” & “and” check items in a set
• dictionaries use keys for indexing
• “append()” & “insert()” add items in lists
• “add()” adds items in sets
• “update()” or new pair assignment add items in dictionaries

Removing items

• “pop()”, “remove()”, & “del” remove items from lists
• “discard()”, “remove()”, & “pop()” remove items from sets
• “pop()”, “popitem()”, & “del” remove items from dictionaries

Modifying items

• indexing and slicing modify items in lists
• “update()” & new pair assignment modify items in dictionaries

Python Intermediate Conditions (more)

• modulus (%) returns the remainder of two divided numbers
• exponential (*) raises a number to the power of another
• floor division (//) divides a number by another
• a += 1 is the short form for a = a +1
• “pass” statements bypass errors in empty conditional statements
• a nested “if” statement is one statement in another
• short form “if” statement – e.g. if a < 10: print (a, “is less than 10”)

Python Intermediate Loops (more)

• “continue” skips an iteration and continues with the rest
• “pass” statements bypass errors in empty loops
• a nested loop is one loop inside another

Python Intermediate Range (more)

• range is a built-in Python function
• outputs a sequence of numbers
• three arguments: start, end, and step
• only end argument is mandatory
• start = 0 and step = 1 by default
• common usage with loops

Python Intermediate Functions (more)

• keyword arguments avoid order issues
• default parameters set the default value settings
• “pass” statements bypass errors in empty functions
• “return” statements output values
• lambda is a small (single line) function – multiple arguments and only one output expression

Python Intermediate Classes (more)

• objects’ values can change through new value assignment
• “del” removes either object properties or entire objects
• “pass” statements bypass errors in empty classes
• “__str()__” returns the representation of the object in string format

Python Intermediate Files (more)

• both append and write modes create new file if non-existent
• “write()” writes new text into a file
• escape characters bypass special symbols in strings
• “\t” produces empty spaces (tab)
• “\n” produces a new line
• “\” escape symbols

Python Intermediate Errors (more)

• “except” statements execute only in the case of errors in the code
• “else” statements execute only in the case of no errors in the code
• “except” statements always execute, with errors or not

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