nuts_bolts

nuts_bolts.py

## nuts and bolts of python



# Single line comments start with a number symbol.

""" Multiline strings can be written
    using three "'s, and are often used
    as comments
"""

####################################################
## 1. Primitive Datatypes and Operators
####################################################

# You have numbers
3  # => 3

# Math is what you would expect
1 + 1  # => 2
8 - 1  # => 7
10 * 2  # => 20
35 / 5  # => 7

# Division is a bit tricky. It is integer division and floors the results
# automatically.
5 / 2  # => 2

# To fix division we need to learn about floats.
2.0     # This is a float
11.0 / 4.0  # => 2.75 ahhh...much better

# Enforce precedence with parentheses
(1 + 3) * 2  # => 8

# Boolean values are primitives
True
False

# negate with not
not True  # => False
not False  # => True

# Equality is ==
1 == 1  # => True
2 == 1  # => False

# Inequality is !=
1 != 1  # => False
2 != 1  # => True

# More comparisons
1 < 10  # => True
1 > 10  # => False
2 <= 2  # => True
2 >= 2  # => True

# Comparisons can be chained!
1 < 2 < 3  # => True
2 < 3 < 2  # => False

# Strings are created with " or '
"This is a string."
'This is also a string.'

# Strings can be added too!
"Hello " + "world!"  # => "Hello world!"

# A string can be treated like a list of characters
"This is a string"[0]  # => 'T'

# % can be used to format strings, like this:
"%s can be %s" % ("strings", "interpolated")

# A newer way to format strings is the format method.
# This method is the preferred way
"{0} can be {1}".format("strings", "formatted")
# You can use keywords if you don't want to count.
"{name} wants to eat {food}".format(name="Bob", food="lasagna")

# None is an object
None  # => None

# Don't use the equality "==" symbol to compare objects to None
# Use "is" instead
"etc" is None  # => False
None is None  # => True

# The 'is' operator tests for object identity. This isn't
# very useful when dealing with primitive values, but is
# very useful when dealing with objects.

# None, 0, and empty strings/lists all evaluate to False.
# All other values are True
bool(0)  # => False
bool("")  # => False


####################################################
## 2. Variables and Collections
####################################################

# Python has a print function, available in versions 2.7 and 3...
print("I'm Python. Nice to meet you!")
# and an older print statement, in all 2.x versions but removed from 3.
print "I'm also Python!"


# No need to declare variables before assigning to them.
some_var = 5    # Convention is to use lower_case_with_underscores
some_var  # => 5

# Accessing a previously unassigned variable is an exception.
# See Control Flow to learn more about exception handling.
some_other_var  # Raises a name error

# if can be used as an expression
"yahoo!" if 3 > 2 else 2  # => "yahoo!"

# Lists store sequences
li = []
# You can start with a prefilled list
other_li = [4, 5, 6]

# Add stuff to the end of a list with append
li.append(1)    # li is now [1]
li.append(2)    # li is now [1, 2]
li.append(4)    # li is now [1, 2, 4]
li.append(3)    # li is now [1, 2, 4, 3]
# Remove from the end with pop
li.pop()        # => 3 and li is now [1, 2, 4]
# Let's put it back
li.append(3)    # li is now [1, 2, 4, 3] again.

# Access a list like you would any array
li[0]  # => 1
# Look at the last element
li[-1]  # => 3

# Looking out of bounds is an IndexError
li[4]  # Raises an IndexError

# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
li[1:3]  # => [2, 4]
# Omit the beginning
li[2:]  # => [4, 3]
# Omit the end
li[:3]  # => [1, 2, 4]
# Select every second entry
li[::2]   # =>[1, 4]
# Revert the list
li[::-1]   # => [3, 4, 2, 1]
# Use any combination of these to make advanced slices
# li[start:end:step]

# Remove arbitrary elements from a list with "del"
del li[2]   # li is now [1, 2, 3]

# You can add lists
li + other_li   # => [1, 2, 3, 4, 5, 6] - Note: values for li and for other_li are not modified.

# Concatenate lists with "extend()"
li.extend(other_li)   # Now li is [1, 2, 3, 4, 5, 6]

# Check for existence in a list with "in"
1 in li   # => True

# Examine the length with "len()"
len(li)   # => 6


# Tuples are like lists but are immutable.
tup = (1, 2, 3)
tup[0]   # => 1
tup[0] = 3  # Raises a TypeError

# You can do all those list thingies on tuples too
len(tup)   # => 3
tup + (4, 5, 6)   # => (1, 2, 3, 4, 5, 6)
tup[:2]   # => (1, 2)
2 in tup   # => True

# You can unpack tuples (or lists) into variables
a, b, c = (1, 2, 3)     # a is now 1, b is now 2 and c is now 3
# Tuples are created by default if you leave out the parentheses
d, e, f = 4, 5, 6
# Now look how easy it is to swap two values
e, d = d, e     # d is now 5 and e is now 4


# Dictionaries store mappings
empty_dict = {}
# Here is a prefilled dictionary
filled_dict = {"one": 1, "two": 2, "three": 3}

# Look up values with []
filled_dict["one"]   # => 1

# Get all keys as a list with "keys()"
filled_dict.keys()   # => ["three", "two", "one"]
# Note - Dictionary key ordering is not guaranteed.
# Your results might not match this exactly.

# Get all values as a list with "values()"
filled_dict.values()   # => [3, 2, 1]
# Note - Same as above regarding key ordering.

# Check for existence of keys in a dictionary with "in"
"one" in filled_dict   # => True
1 in filled_dict   # => False

# Looking up a non-existing key is a KeyError
filled_dict["four"]   # KeyError

# Use "get()" method to avoid the KeyError
filled_dict.get("one")   # => 1
filled_dict.get("four")   # => None
# The get method supports a default argument when the value is missing
filled_dict.get("one", 4)   # => 1
filled_dict.get("four", 4)   # => 4

# "setdefault()" inserts into a dictionary only if the given key isn't present
filled_dict.setdefault("five", 5)  # filled_dict["five"] is set to 5
filled_dict.setdefault("five", 6)  # filled_dict["five"] is still 5


# Sets store ... well sets
empty_set = set()
# Initialize a "set()" with a bunch of values
some_set = set([1, 2, 2, 3, 4])   # some_set is now set([1, 2, 3, 4])

# Since Python 2.7, {} can be used to declare a set
filled_set = {1, 2, 2, 3, 4}   # => {1, 2, 3, 4}

# Add more items to a set
filled_set.add(5)   # filled_set is now {1, 2, 3, 4, 5}

# Do set intersection with &
other_set = {3, 4, 5, 6}
filled_set & other_set   # => {3, 4, 5}

# Do set union with |
filled_set | other_set   # => {1, 2, 3, 4, 5, 6}

# Do set difference with -
{1, 2, 3, 4} - {2, 3, 5}   # => {1, 4}

# Check for existence in a set with in
2 in filled_set   # => True
10 in filled_set   # => False


####################################################
## 3. Control Flow
####################################################

# Let's just make a variable
some_var = 5

# Here is an if statement. Indentation is significant in python!
# prints "some_var is smaller than 10"
if some_var > 10:
    print("some_var is totally bigger than 10.")
elif some_var < 10:    # This elif clause is optional.
    print("some_var is smaller than 10.")
else:           # This is optional too.
    print("some_var is indeed 10.")


"""
For loops iterate over lists
prints:
    dog is a mammal
    cat is a mammal
    mouse is a mammal
"""
for animal in ["dog", "cat", "mouse"]:
    # You can use % to interpolate formatted strings
    print("%s is a mammal" % animal)

"""
"range(number)" returns a list of numbers
from zero to the given number
prints:
    0
    1
    2
    3
"""
for i in range(4):
    print(i)

"""
While loops go until a condition is no longer met.
prints:
    0
    1
    2
    3
"""
x = 0
while x < 4:
    print(x)
    x += 1  # Shorthand for x = x + 1

# Handle exceptions with a try/except block

# Works on Python 2.6 and up:
try:
    # Use "raise" to raise an error
    raise IndexError("This is an index error")
except IndexError as e:
    pass    # Pass is just a no-op. Usually you would do recovery here.