Course Info¶
The book for this section of the course is Mark Pilgram’s “Dive into Python 3”. The full book is available online at http://www.diveintopython3.net/
My lecture notes (including source) and code examples are available at https://github.com/mlavin/lecture-notes
What is Python?¶
There is More than One Python¶
Standard Python¶
- Python 2.X - Last stable release 2.7.14
- Python 3.X - Currently 3.6.4
Non-standard Python¶
- Jython - Python implementation written in Java
- IronPython - Python implementation written in .NET
- Cython - Python extension for writing C/C++ extensions
- PyPy - Python implementation written in Python (sort of)
Where can I get Python?¶
You use Linux or a Mac then you probably already have Python 2.7 but you'll probably want a more recent version
For Mac I suggest pyenv or Homebrew
If you use Windows you can download an executable installer from Python.org
Who Uses Python?¶
4th on the TIOBE Index as of Feb 2018 below Java, C, and C++
Companies like:
- Web: Google, Reddit, Pintrest, Instagram, and Caktus Group
- Fortune 500: Honeywell, Phillips, and Red Hat
- Researchers and universities: NCSU, UNC, and Duke
- Other: Industrial Light & Magic and Disney
Read more: http://www.python.org/about/success/
# %load ../code/hello.py
# hello.py
print('Hello, World')
# %load ../code/fibonacci.py
def fibonacci(n):
if n <= 2:
return 1
else:
return fibonacci(n - 1) + fibonacci(n - 2)
for i in range(1, 15):
print(fibonacci(i))
Learn to Love Whitespace¶
Python was created with the idea that most code will be read more times than it’s written.
Whitespace is meaningful for seperating code blocks without the use of braces.
The pass statement can be used to hold an empty logical or function block.
PEP8¶
The convention is to use 4 spaces per indention and you cannot mix tabs and spaces.
Suggested max line length is 79 characters. Backslash is a line continuation character but lines can also be extended with parentheses.
def my_long_function(arg1, arg2, optional_arg1="fizz",
optional_arg2="buzz", optional_arg3="done"):
pass
You can read the full style guide online http://www.python.org/dev/peps/pep-0008/
import this
Declaring Functions¶
Functions are declared with the def keyword:
def my_function():
pass
Arguments can given starting with required then optional:
def short_name(first_name, last_name="Smith"):
return "%s %s" % (first_name[0], last_name)
Notice that the arguments do not declare their type.
Typing¶
Python is dynamically typed meaning you do not need to declare the types of your variables before using them. The variable type is determined when the program is executed.
Python is strongly typed meaning that type is enforced.
a = 1 # a is now an integer
b = '2' # b is now a string
a + b # this will fail
str(a) + b
Type Annotations¶
New in Python 3.5 - (PEP484)[https://www.python.org/dev/peps/pep-0484/]
You can annotate your functions with the types they take/return
def short_name(first_name: str, last_name="Smith": str) -> str:
return "%s %s" % (first_name[0], last_name)
This can help document your code but this isn't enforced at runtime.
Everything is an Object¶
Everything has:
- An identity
- A type
- Some content
Great expanation of Python Object model: http://www.effbot.org/zone/python-objects.htm
import math
math.sqrt(4)
math.sqrt.__doc__
# %load ../code/fibo2.py
import time
def fibonacci(n):
if n <= 2:
return 1
else:
return fibonacci(n - 1) + fibonacci(n - 2)
start = time.time()
fibonacci(25)
time.time() - start
# %load ../code/fibocache.py
import time
def fibonacci(n):
if hasattr(fibonacci, '_%s' % n):
return getattr(fibonacci, '_%s' % n)
if n <= 2:
value = 1
setattr(fibonacci, '_%s' % n, value)
return value
else:
value = fibonacci(n - 1) + fibonacci(n - 2)
setattr(fibonacci, '_%s' % n, value)
return value
start = time.time()
fibonacci(25)
time.time() - start
fibonacci._10
fibonacci._11
import math
def do_math(f, x):
print(f(x))
y = math.sqrt
do_math(y, 10)
y = math.log
do_math(y, 10)
import math
math.log(10)
def new_log(x):
return 5
math.log = new_log
math.log(10)
What Do I Put in The Function?¶
Many of the same operators you know and love from C:
# add, subtract, multiply, divide
a + b, a - b, a * b , a / b
# exponentiation, floor divide, modulo
a ** b, a // b, a % b
# bitwise inverse, left bit shift, right bit shift
~a, a << b, a >> b
# bitwise and, bitwise or, bitwise xor
a & b, a | b, a ^ b
Comparisons And Logic¶
Most will be familiar:
# less than, less equal, greater than, greater equal
a < b, a <= b, a > b, a >= b
# equal, not equal, object identity, object identity negation
a == b, a != b, a is b, a is not b
# collection membership, collection membership negation
a in b, a not in b
# logical and, logical or, logical negation
a and b, a or b, not a
Control Statements¶
The basic flow control statements should also look familiar from C though the syntax is slightly different.
if, else, for, while
The same as with functions there are no braces to define the logical blocks. Instead everything is defined by the whitespace indention.
If¶
The if statement defines a control block which will only execute when a logical statement is true. This can be paired with an else statement to define how to handle the false case. To avoid deep nesting you can also use elif statement.
if x > 100:
print("That's a lot!")
elif x > 10:
print("That's ok.")
else:
print("That's all you've got?")
For¶
The for statement is used to loop through any iterable. This includes lists and strings. User defined type can also have the ability to be iterated by defining the iteration protocol.
for x in [1, 2, 3]:
print(x)
You can use the enumerate function to add the current index.
for i, c in enumerate("blip"):
print("Character %s is %s" (i, c))
Range¶
range allows you to generate a sequence of integers between a particular range. It starts at zero and increases by one but those are available arguments.
for i in range(5):
print(i)
for i in range(1, 5):
print(i)
for i in range(1, 5, 2):
print(i)
for name in ['Newton', 'x', 'Euler']:
if 'x' in name:
continue
else:
print(name)
for name in []:
print("Names were given.")
else:
print("No names were given.")
While¶
In addition to the for loop there is also the while loop. The while loop will continue until a particular logical statement is false.
x = 10
while x > 5:
x -= 1
Pass¶
pass is a special keyword in Python that does nothing. It can be used to fill a control block or a function or a class definition.
Comments¶
Python comments are denoted with the # character. While not techinally a comment you can also use triple quoted strings as a multi-line comment. This is the style used to define doc strings previously discussed.
# My Comment
"""
This is a longer comment.
Blah blah blah.
Though technically it's a string literal.
"""
Building Python Module¶
Python modules are collections of Python statements. They stored in text files with the .py extension. The module name is the same as the file name without the extension.
Modules as Scripts¶
When you pass a module to the interpreter such as python hello.py the module name changes from hello to __main__. You can use this fact to handle the case where the module is executed differently than when the module is imported.
if __name__ == "__main__":
print("I am a script.")
else:
print("I am a module.")
Imports¶
We’ve already seen some import statements but there are three styles of Python imports.
# Add a reference to the module
import X
# Creates references to all public objects in X
from X import *
# Creates refernces to the names a, b, c
from X import a, b, c
# Add a reference to the module
X = __import__('X')
Python Path¶
Where does Python look for modules to import? The Python path.
This is defined by the PYTHONPATH environment variable in your shell.
import sys
sys.path
What Happens on Import?¶
When Python imports a module, it first checks the module registry (sys.modules) to see if the module is already imported. If that’s the case, Python uses the existing module object as is.
Otherwise, Python does something like this:
- Create a new, empty module object (this is essentially a dictionary)
- Insert that module object in the
sys.modulesdictionary - Load the module code object (if necessary, compile the module first)
- Execute the module code object in the new module’s namespace. All variables assigned by the code will be available via the module object.
import math
dir(math)
help(math)
dir(__builtin__)
Up Next¶
Built-in data types.