Python_Data_Types.md

Python has 12 primary built-in data types:

Category	Name	Description
None	None	The null object
Numeric	int	Integer
	float	Floating point number
	complex	Complex number
	bool	Boolean (True, False)
Sequences	str	String of characters
	list	List of arbitrary objects
	tuple	Group of arbitrary items
	range	Creates a range of integers
Mapping	dict	Dictionary of key-value pairs
Set	set	Mutable, unordered collection of unique items
	frozenset	Immutable set

Also, decimal and fractions module can be used for certain use cases:

• import decimal
• import fractions

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Modules for Data Structures and Algorithms

Collections

from collections import abc

Datatype or operation	Description
namedtuple()	Creates tuple subclasses with named fields
deque	Lists with fast appends and pops either end
ChainMap	Dictionary like class to create a signle view of multiple mappings
Counter	Dictionary subclass for counting hasable objects
OrderedDict	Dictionary subclass that remembers the entry order
defaultDict	Dictionary subclass that calls a function to supply missing values
UserDict, UserList, UserString	These 3 data types are simply wrappers for their underlyuing base classes. Their use has largely been replaced by the ability to subclass their respective base classes directly. Can be used to access the underlying obect as an attribute

Arrays

import array

It defines a datatype array that is similar to the list datatype except for the constraint that their contents must be of a single type of the underlying representation

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Conditional Statements: if, elif, else

x = -15

if x==0:
  print(x, "is zero)
elif x>0:
  print(x, "is positive)
elif x<0:
  print(x, "is negative)
else:
  print(x, "is unlike anything I've ever seen")

---

for loops

for N in [2,3,5,7]:
  print(N, end = ' ') #print all in the same line

# output: 2 3 5 7

---

while loops

i = 0
while i < 10:
  print(i, end = ' ')
  i += 1

# output: 0 1 2 3 4 5 6 7 8 9

---

break and continue: Fine-tuning your loops

• break - exit loop (breaks out of the loop entirely)
• continue - skip iteration (skips remainder of current loop, goes to next iteration)
• pass - do nothing (acts as a placeholder, often when you begin coding)

Loops with an else block (like a nobreak statement)

else block is executed only if the loop ends naturally, without encountering a break statement

# non-optimized algo of the Sieve of Eratosthenes (for finding prime numbers)

L = []
nmax = 30

for n in range(2, nmax):
 for factor in L:
   if n % factor == 0:
     break
 else: # no break)
     L.append(n)
print(L)

# output : [2,3,5,7,11,13,17,19,23,29]

---

Defining Functions

Defining Functions

def fibonacci(N):

  L = []
  a, b = 0, 1

  while len(L) < N:
    a, b = b, a+b
    L.append(a)

  return L

Using Functions

fibonacci(10)

[1,1,2,3,5,8,13,21,34,55]

Functions can return any Python object, simple or compound

Multiple Return Values (put in a tuple)

# define the function
def real_img_conj(val):
  return val.real, val.imag, val.conjugate()

# use the function
r, i, c = real_img_conj(3 + 4j)
print(r, i, c)

#output: 3.0 4.0 (3-4j)

Default Argument values in Function

#define the function with default arg. values
def fibonacci(N, a=0, b=1):
  L = []

  while len(L) < N:
    a, b = b, a+b
    L.append(a)

  return L

# use the function
fibonacci(10)
# output: [1,1,2,3,5,8,13,21,34,55]

fibonacci(10,0,2)
# output: [2,2,4,6,10,16,26,42,68,110]

fibonacci(10,b=3,a=1)
# output: [3,4,7,11,18,29,47,76,123,199]

*args and **kwargs: Flexible Arguments

enumerate

for index, word in enumerate(words):
  print(index, word)