Core Python Language¶
Mostly copied from the official python tutorial
Invoking Python¶
There are three main ways to use python.
- By running a python file, e.g.
python myscript.py - Through an interactive console (python interpreter or ipython shell)
- In an interactive iPython notebook
We will be using the iPython notebook.
Python Versions¶
There are two versions of the python language out there: python 2 and python 3. Python 2 is more common in the wild but is depracated. The community is moving to python 3. As new python learners, you should learn python 3. But it is important to be aware that python 2 exists. It is possible that a package you want to use is only supported in python 2. In general, it is pretty easy to switch between then.
Some of the main changes in python 3 are:
printis a function- Integer division returns a float
- Iterators behave differently
- Unicode is used for encoding code
Basic Variables: Numbers and String¶
# comments are anything that comes after the "#" symbol
a = 1 # assign 1 to variable a
b = "hello" # assign "hello" to variable b
The following identifiers are used as reserved words, or keywords of the language, and cannot be used as ordinary identifiers. They must be spelled exactly as written here:
False class finally is return
None continue for lambda try
True def from nonlocal while
and del global not with
as elif if or yield
assert else import pass
break except in raise
Additionally, the following a built in functions which are always available in your namespace once you open a python interpreter
abs() dict() help() min() setattr() all() dir() hex() next() slice() any()
divmod() id() object() sorted() ascii() enumerate() input() oct() staticmethod()
bin() eval() int() open() str() bool() exec() isinstance() ord() sum() bytearray()
filter() issubclass() pow() super() bytes() float() iter() print() tuple()
callable() format() len() property() type() chr() frozenset() list() range()
vars() classmethod() getattr() locals() repr() zip() compile() globals() map()
reversed() __import__() complex() hasattr() max() round() delattr() hash()
memoryview() set()# how to we see our variables?
print(a)
print(b)
print(a,b)
All variables are objects. Every object has a type (class). To find out what type your variables are
print(type(a))
print(type(b))
# as a shortcut, iPython notebooks will automatically print whatever is on the last line
type(b)
# we can check for the type of an object
print(type(a) is int)
print(type(a) is str)
Different objects attributes and methods, which can be accessed via the syntax variable.method
IPython will autocomplete if you press
# this returns the method itself
b.capitalize
# this calls the method
b.capitalize()
# there are lots of other methods
# binary operations act differently on different types of objects
c = 'World'
print(b + c)
print(a + 2)
print(a + b)
Math¶
Basic arithmetic and boolean logic is part of the core python library.
# addition / subtraction
1+1-5
# multiplication
5 * 10
# division
1/2
# that was automatically converted to a float
type(1/2)
# exponentiation
2**4
# rounding
round(9/10)
# built in complex number support
(1+2j) / (3-4j)
# logic
True and True
True and False
True or True
(not True) or (not False)
Conditionals¶
The first step to programming. Plus an intro to python syntax.
x = 100
if x > 0:
print('Positive Number')
elif x < 0:
print('Negative Number')
else:
print ('Zero!')
# indentation is MANDATORY
# blocks are closed by indentation level
if x > 0:
print('Positive Number')
if x >= 100:
print('Huge number!')
More Flow Control¶
# make a loop
count = 0
while count < 10:
# bad way
# count = count + 1
# better way
count += 1
print(count)
# use range
for i in range(5):
print(i)
Important point: in python, we always count from 0!
# what is range?
type(range)
range?
# iterate over a list we make up
for pet in ['dog', 'cat', 'fish']:
print(pet, len(pet))
What is the thing in brackets? A list! Lists are one of the core python data structures.
Lists¶
l = ['dog', 'cat', 'fish']
type(l)
# list have lots of methods
l.sort()
l
# we can convert a range to a list
r = list(range(5))
r
while r:
p = r.pop()
print('p:', p)
print('r:', r)
There are many different ways to interact with lists. Exploring them is part of the fun of python.
list.append(x) Add an item to the end of the list. Equivalent to a[len(a):] = [x].
list.extend(L) Extend the list by appending all the items in the given list. Equivalent to a[len(a):] = L.
list.insert(i, x) Insert an item at a given position. The first argument is the index of the element before which to insert, so a.insert(0, x) inserts at the front of the list, and a.insert(len(a), x) is equivalent to a.append(x).
list.remove(x) Remove the first item from the list whose value is x. It is an error if there is no such item.
list.pop([i]) Remove the item at the given position in the list, and return it. If no index is specified, a.pop() removes and returns the last item in the list. (The square brackets around the i in the method signature denote that the parameter is optional, not that you should type square brackets at that position. You will see this notation frequently in the Python Library Reference.)
list.clear() Remove all items from the list. Equivalent to del a[:].
list.index(x) Return the index in the list of the first item whose value is x. It is an error if there is no such item.
list.count(x) Return the number of times x appears in the list.
list.sort() Sort the items of the list in place.
list.reverse() Reverse the elements of the list in place.
list.copy() Return a shallow copy of the list. Equivalent to a[:].
Don't assume you know how list operations work!
# "add" two lists
x = list(range(5))
y = list(range(10,15))
z = x + y
z
# access items from a list
print('first', z[0])
print('last', z[-1])
print('first 3', z[:3])
print('last 3', z[-3:])
print('middle, skipping every other item', z[5:10:2])
MEMORIZE THIS SYNTAX! It is central to so much of python and often proves confusing for users coming from other languages.
In terms of set notation, python indexing is left inclusive, right exclusive. If you remember this, you will never go wrong.
# that means we get an error from the following
N = len(z)
z[N]
# this index notation also applies to strings
name = 'Ryan Abernathey'
print(name[:4])
# you can also test for the presence of items in a list
5 in z
Lists are not meant for math! They don't have a datatype.
z[4] = 'fish'
z
Python is full of tricks for iterating and working with lists
# a cool python trick: list comprehension
squares = [n**2 for n in range(5)]
squares
# iterate over two lists together uzing zip
for item1, item2 in zip(x,y):
print('first:', item1, 'second:', item2)
Other Data Structures¶
We are almost there. We have the building blocks we need to do basic programming. But python has some other data structures we need to learn about.
Tuples¶
Tuples are similar to lists, but they are immutable—they can't be extended or modified. What is the point of this? Generally speaking: to pack together inhomogeneous data. Tuples can then be unpacked and distributed by other parts of your code.
Tuples may seem confusing at first, but with time you will come to appreciate them.
# tuples are created with parentheses, or just commas
a = ('Ryan', 33, True)
b = 'Takaya', 25, False
type(b)
# can be indexed like arrays
print(a[1]) # not the first element!
# and they can be unpacked
name, age, status = a
Dictionaries¶
This is an extremely useful data structure. It maps keys to values.
Dictionaries are unordered!
# different ways to create dictionaries
d = {'name': 'Ryan', 'age': 33}
e = dict(name='Takaya', age=25)
e
# access a value
d['name']
Square brackets [...] are python for "get item" in many different contexts.
# test for the presence of a key
print('age' in d)
print('height' in e)
# try to access a non-existant key
d['height']
# add a new key
d['height'] = (5,11) # a tuple
d
# keys don't have to be strings
d[99] = 'ninety nine'
d
# iterate over keys
for k in d:
print(k, d[k])
# better way
### python 2
### for key, val in d.iteritems()
for key, val in d.items():
print(key, val)
Functions¶
Functions are a central part of advanced python programming. You should try to write and use your own functions as often as possible.
# define a function
def say_hello():
"""Return the word hello."""
return 'Hello'
# functions are also objects
type(say_hello)
# this doesnt call
say_hello?
# this does
say_hello()
# assign the result to something
res = say_hello()
res
# take some arguments
def say_hello_to(name):
"""Return a greeting to `name`"""
return 'Hello ' + name
# intended usage
say_hello_to('World')
say_hello_to(10)
# redefine the function
def say_hello_to(name):
"""Return a greeting to `name`"""
return 'Hello ' + str(name)
say_hello_to(10)
# take an optional keyword argument
def say_hello_or_hola(name, spanish=False):
"""Say hello in multiple languages."""
if spanish:
greeting = 'Hola '
else:
greeting = 'Hello '
return greeting + name
print(say_hello_or_hola('Ryan'))
print(say_hello_or_hola('Juan', spanish=True))
# flexible number of arguments
def say_hello_to_everyone(*args):
return ['hello ' + str(a) for a in args]
say_hello_to_everyone('Ryan', 'Juan', 'Takaya')
We could spend the rest of the day talking about functions, but we have to move on.
Individual Exercises¶
Fibonacci Sequence¶
The Fibonacci sequence is the 1,1,2,3,5,8..., the sum of each number with the preceding one. Write a function to compute the Fibonacci sequence of length n. (Hint, use some list methods.)
def fib(n):
l = [1,1]
for i in range(n-2):
l.append(l[-1] + l[-2])
return l
fib(10)
Add and Multiply Lists Item by Item¶
Write functions to add and multiply each item in a list.
def add(x,y):
return [a + b for a,b in zip(x,y)]
def multiply(x,y):
return [a * b for a,b in zip(x,y)]
add(range(10), range(10))
multiply(range(5), [9,3,2,5,3])
N = 100000
%timeit multiply(range(N), range(N))
import numpy as np
%timeit np.arange(N) * np.arange(N)
On to numpy