Session One: Introductions¶

Your instructors¶

Who are you?¶

Tell us a tiny bit about yourself:

• name
• programming background: what languages have you used?
• what do you hope to get from this class

Course Materials Online¶

An HTML rendered version of the slides for this course is online at:

http://uwpce-pythoncert.github.io/IntroPython2016a/

Note also the excercise descriptions and supplemental materials.

The source of these materials are in the class gitHub repo:

https://github.com/UWPCE-PythonCert/IntroPython2016a

The course content management system:

https://canvas.uw.edu/courses/1026775

Class Structure¶

Class Time:

• Some lecture – as little as possible
• Lots of demos
• Lab time: lots of hand-on practice - Take a break if you need one then...
• Lather, Rinse, Repeat.....

Interrupt me with questions – please!

(Some of the best learning prompted by questions)

Homework:¶

• Most homework will be reading, and the occasional Video

• Exercises will be started in class – but you can finish them at home.

• You are adults – it’s up to you to do it

• You can do a gitHub “pull request” if you want us to review your work.

  • We’ll review how to do that in the second Session

Mailing list and Office Hours¶

Discussion forum for questions and support:

https://canvas.uw.edu/courses/1026775/discussion_topics

Office Hours:

We will generally hold office hours 10 a.m. to noon on Sundays

Location, location, location?

Lightning Talks¶

Lightning Talks:

• 5 minutes each (including setup) - no kidding!
• Every student will give one
• Purposes: introduce yourself, share interests, show Python applications
• Any topic you like, that is related to Python – according to you!

What is Python?¶

• Dynamic
• Object oriented
• Byte-compiled
• Interpreted

But what does that mean?

Python Features¶

• Unlike C, C++, C#, Java ... More like Ruby, Lisp, Perl, Javascript ...
• Dynamic – no type declarations
  • Programs are shorter
  • Programs are more flexible
  • Less code means fewer bugs
• Interpreted – no separate compile, build steps - programming process is simpler

What’s a Dynamic language¶

Dynamic typing.

• Type checking and dispatch happen at run-time

In [1]: x = a + b

• What is a?
• What is b?
• What does it mean to add them?
• a and b can change at any time before this process

Strong typing.

In [1]: a = 5

In [2]: type(a)
Out[2]: int

In [3]: b = '5'

In [4]: type(b)
Out[4]: str

• everything has a type.
• the type of a thing determines what it can do.

Duck Typing¶

“If it looks like a duck, and quacks like a duck – it’s probably a duck”

If an object behaves as expected at run-time, it’s the right type.

Python Versions¶

Python 2.x

• “Classic” Python
• Evolved from original

Python 3.x (“py3k”)

• Updated version
• Removed the “warts”
• Allowed to break code

This class uses Python 3 – not Python 2

• Adoption of Python 3 is growing fast
  • Almost all key packages now supported (https://python3wos.appspot.com/)
  • But most code in the wild is still 2.x
• If you find yourself needing to work with Python 2 and 3, there are ways to write compatible code: https://wiki.python.org/moin/PortingPythonToPy3k
• We will cover that more later in the program. Also: a short intro to the differences you really need to know about up front later this session.

Your Command Line (cli)¶

Having some facility on the command line is important

We won’t cover this much in class, so if you are not comfortable, please bone up at home.

I suggest running through the cli tutorial at “learn code the hard way”:

http://cli.learncodethehardway.org/book/

Windows:

Most of the demos in class, etc, will be done using the “bash” command line shell on OS-X. This is identical to the bash shell on Linux.

Windows provides the “DOS” command line, which is OK, but pretty old and limited, or “Power Shell” – a more modern, powerful, flexible command shell.

If you are comfortable with either of these – go for it.

If not, you can use the “git Bash” shell – which is much like the bash shell on OS-X and Linux.

Your Interpreter¶

Python comes with a built-in interpreter.

You see it when you type python at the command line:

$ python
Python 3.5.0 (v3.5.0:374f501f4567, Sep 12 2015, 11:00:19)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.

That last thing you see, >>> is the “Python prompt”.

This is where you type code.

LAB: Getting set up¶

Before we move on – we need to get all of us on the same page, with the tools we need for class.

You will find instructions for how to get python, etc, up and running on your machine here:

Linux: :Setting Up Python For Linux

OS-X: :Setting up your Mac for Python

Windows: :Setting up Windows for Python

Python in the Interpreter¶

Try it out:

>>> print("hello world!")
hello world!
>>> 4 + 5
9
>>> 2 ** 8 - 1
255
>>> print ("one string" + " plus another")
one string plus another
>>>

When you are in an interpreter, there are a number of tools available to you.

There is a help system:

>>> help(str)
Help on class str in module __builtin__:

class str(basestring)
 |  str(object='') -> string
 |
 |  Return a nice string representation of the object.
 |  If the argument is a string, the return value is the same object.
 ...

You can type q to exit the help viewer.

You can also use the dir builtin to find out about the attributes of a given object:

>>> bob = "this is a string"
>>> dir(bob)
['__add__', '__class__', '__contains__', '__delattr__',
 '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__',
 '__getitem__', '__getnewargs__', '__getslice__', '__gt__',
 ...
 'rjust', 'rpartition', 'rsplit', 'rstrip', 'split', 'splitlines',
 'startswith', 'strip', 'swapcase', 'title', 'translate', 'upper',
 'zfill']
>>> help(bob.rpartition)

This allows you quite a bit of latitude in exploring what Python is.

In addition to the built-in interpreter, there are several more advanced interpreters available to you.

We’ll be using one in this course called iPython

More on this soon.

Your Editor¶

Typing code in an interpreter is great for exploring.

But for anything “real”, you’ll want to save the work you are doing in a more permanent fashion.

This is where an Editor fits in.

Any good text editor will do.

MS Word is not a text editor.

Nor is TextEdit on a Mac.

Notepad is a text editor – but a crappy one.

You need a real “programmers text editor”

A text editor saves only what it shows you, with no special formatting characters hidden behind the scenes.

At a minimum, your editor should have:

• Syntax Colorization
• Automatic Indentation

In addition, great features to add include:

• Tab completion
• Code linting
• Jump-to-definition

Have an editor that does all this? Feel free to use it.

If not, I suggest SublimeText:

http://www.sublimetext.com/

(Use version 3, even though it’s “beta”)

Why No IDE?¶

An IDE does not give you much that you can’t get with a good editor plus a good interpreter.

An IDE often weighs a great deal

Setting up IDEs to work with different projects can be challenging and time-consuming.

Particularly when you are first learning, you don’t want too much done for you.

Why No IDE?¶

That said... go get the educational edition of PyCharm:

https://www.jetbrains.com/pycharm-edu/

Which is awesome.

Our Class Environment¶

We are going to work from a common environment in this class.

We will take the time here in class to get this going.

This helps to ensure that you will be able to work.

Step 1: Python 3¶

Do you already have this??

$ python
Python 3.5.0 (v3.5.0:374f501f4567, Sep 12 2015, 11:00:19)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> ^D

If not:

• For OS X
• For Linux
• For Windows

Step 2: Pip¶

Python comes with quite a bit (“batteries included”).

Sometimes you need a bit more.

Pip allows you to install Python packages to expand your system.

The previous instructions include pip as well - make sure it’s working.

Once you’ve installed pip, you use it to install Python packages by name:

$ python -m pip install foobar
...

To find packages (and their proper names), you can search the python package index (PyPI):

https://pypi.python.org/pypi

Step 3: Install iPython¶

As this is an intro class, we are going to use almost entirely features of standard library. But there are a couple things you may want:

iPython is an “enhanced python shell” – it make s it easier to work with python interatively.

$ python -m pip install ipython

iPython Overview¶

You have installed iPython.

iPython is an advanced Python interpreter that offers enhancements.

You can read more about it in the official documentation.

Specifically, you’ll want to pay attention to the information about

Using iPython for Interactive Work.

The very basics of iPython¶

iPython can do a lot for you, but for starters, here are the key pieces you’ll want to know:

Start it up

$ ipython
Python 3.5.0 (v3.5.0:374f501f4567, Sep 12 2015, 11:00:19)
Type "copyright", "credits" or "license" for more information.

IPython 4.0.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

This is the stuff I use every day:

• command line recall:
  • hit the “up arrow” key
  • if you have typed a bit, it will find the last command that starts the same way.
• basic shell commands:
  • ls, cd, pwd
• any shell command:

• ! the_shell_command

• pasting from the clipboard:
  • %paste (this keeps whitespace cleaner for you)

• getting help:
  • something?
• tab completion:
  • something.<tab>
• running a python file:
  • run the_name_of_the_file.py

That’s it – you can get a lot done with those.

How to run a python file¶

A file with python code in it is a ‘module’ or ‘script’

(more on the distinction later on...)

It should be named with the .py extension: some_name.py

To run it, you have a couple options:

1. call python on the command line, and pass in your module name

$ python the_name_of_the_script.py

2. run iPython, and run it from within iPython with the run command

In [1]: run the_file.py

Values¶

All of programming is really about manipulating values.

• Values are pieces of unnamed data: 42, 'Hello, world',
• In Python, all values are objects
  • Try dir(42) - lots going on behind the curtain!
• Every value belongs to a type
  • Try type(42) - the type of a value determines what it can do

Literals for the Basic Value types:¶

Numbers:

• floating point: 3.4
• integers: 456

Text:

• "a bit of text"
• 'a bit of text'
• (either single or double quotes work – why?)

Boolean values:

• True
• False

(There are intricacies to all of these that we’ll get into later)

Code structure¶

Each line is a piece of code.

Comments:

In [3]: # everything after a '#' is a comment

Expressions:

In [4]: # evaluating an expression results in a value

In [5]: 3 + 4
Out[5]: 7

Statements:

In [6]: # statements do not return a value, may contain an expression

In [7]: line_count = 42

In [8]: return something

It’s kind of obvious, but handy when playing with code:

In [1]: print ("something")
something

You can print multiple things:

In [2]: print("the value is", 5)
the value is 5

Any python object can be printed (though it might not be pretty...)

In [1]: class bar(object):
   ...:     pass
   ...:

In [2]: print(bar)
<class '__main__.bar'>

Blocks of code are delimited by a colon and indentation:

def a_function():
    a_new_code_block
end_of_the_block

for i in range(100):
    print(i**2)

try:
    do_something_bad()
except:
    fix_the_problem()

Python uses indentation to delineate structure.

This means that in Python, whitespace is significant.

(but ONLY for newlines and indentation)

The standard is to indent with 4 spaces.

SPACES ARE NOT TABS

TABS ARE NOT SPACES

These two blocks look the same:

for i in range(100):
    print(i**2)

for i in range(100):
    print(i**2)

But they are not:

for i in range(100):
\s\s\s\sprint i**2

for i in range(100):
\tprint i**2

ALWAYS INDENT WITH 4 SPACES

NEVER INDENT WITH TABS

Make sure your editor is set to use spaces only –

Even when you hit the <tab> key

Expressions¶

An expression is made up of values and operators.

• An expression is evaluated to produce a new value: 2 + 2
  • The Python interpreter can be used as a calculator to evaluate expressions
• Integer vs. float arithmetic
  • (Python 3 smooths this out)
  • Always use / when you want float results, // when you want floored (integer) results
• Type conversions
  • This is the source of many errors, especially in handling text
• Type errors - checked at run time only

Symbols¶

Symbols are how we give names to values (objects).

• Symbols must begin with an underscore or letter
• Symbols can contain any number of underscores, letters and numbers
  • this_is_a_symbol
  • this_is_2
  • _AsIsThis
  • 1butThisIsNot
  • nor-is-this
• Symbols don’t have a type; values do
  • This is why python is “Dynamic”

Symbols and Type¶

Evaluating the type of a symbol will return the type of the value to which it is bound.

In [19]: type(42)
Out[19]: int

In [20]: type(3.14)
Out[20]: float

In [21]: a = 42

In [22]: b = 3.14

In [23]: type(a)
Out[23]: int

In [25]: a = b

In [26]: type(a)
Out[26]: float

Assignment¶

A symbol is bound to a value with the assignment operator: =

• This attaches a name to a value
• A value can have many names (or none!)
• Assignment is a statement, it returns no value

Evaluating the name will return the value to which it is bound

In [26]: name = "value"

In [27]: name
Out[27]: 'value'

In [28]: an_integer = 42

In [29]: an_integer
Out[29]: 42

In [30]: a_float = 3.14

In [31]: a_float
Out[31]: 3.14

Variables?¶

• In most languages, what I’m calling symbols, or names, are called “variables”.
• In fact, I’ll probably call them variables in this class.
• That’s because they are used, for the most part, for the same purposes.
• But often a “variable” is defined as something like: “a place in memory that can store values”
• That is NOT what a name in python is!
• A name can be bound to a value – but that has nothing to do with a location in memory.

In-Place Assignment¶

You can also do “in-place” assignment with +=.

In [32]: a = 1

In [33]: a
Out[33]: 1

In [34]: a = a + 1

In [35]: a
Out[35]: 2

In [36]: a += 1

In [37]: a
Out[37]: 3

also: -=, *=, /=, **=, \%=

(not quite – really in-place assignment for mutables....)

Multiple Assignment¶

You can assign multiple names from multiple expressions in one statement

In [48]: x = 2

In [49]: y = 5

In [50]: i, j = 2 * x, 3 ** y

In [51]: i
Out[51]: 4

In [52]: j
Out[52]: 243

Python evaluates all the expressions on the right before doing any assignments

Nifty Python Trick¶

Using this feature, we can swap values between two names in one statement:

In [51]: i
Out[51]: 4

In [52]: j
Out[52]: 243

In [53]: i, j = j, i

In [54]: i
Out[54]: 243

In [55]: j
Out[55]: 4

Multiple assignment and symbol swapping can be very useful in certain contexts

Deleting¶

You can’t actually delete anything in python...

del only deletes a name (or “unbinds” the name...)

In [56]: a = 5

In [57]: b = a

In [58]: del a

In [59]: a
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-59-60b725f10c9c> in <module>()
----> 1 a

NameError: name 'a' is not defined

The object is still there...python will only delete it if there are no references to it.

In [15]: a = 5

In [16]: b = a

In [17]: del a

In [18]: a
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-18-60b725f10c9c> in <module>()
----> 1 a

NameError: name 'a' is not defined

In [19]: b
Out[19]: 5

Identity¶

Every value in Python is an object.

Every object is unique and has a unique identity, which you can inspect with the id builtin:

In [68]: id(i)
Out[68]: 140553647890984

In [69]: id(j)
Out[69]: 140553647884864

In [70]: new_i = i

In [71]: id(new_i)
Out[71]: 140553647890984

Testing Identity¶

You can find out if the values bound to two different symbols are the same object using the is operator:

In [72]: count = 23

In [73]: other_count = count

In [74]: count is other_count
Out[74]: True

In [75]: count = 42

In [76]: other_count is count
Out[76]: False

Equality¶

You can test for the equality of certain values with the == operator

In [77]: val1 = 20 + 30

In [78]: val2 = 5 * 10

In [79]: val1 == val2
Out[79]: True

In [80]: val3 = '50'

In [81]: val1 == val3
Out[84]: False

Operator Precedence¶

Operator Precedence determines what evaluates first:

4 + 3 * 5 != (4 + 3) * 5

To force statements to be evaluated out of order, use parentheses.

Python Operator Precedence¶

Parentheses and Literals:

(), [], {}

"", b'', ''

Function Calls:

f(args)

Slicing and Subscription:

a[x:y]

b[0], c['key']

Attribute Reference:

obj.attribute

Exponentiation:

**

Bitwise NOT, Unary Signing:

~x

+x, -x

Multiplication, Division, Modulus:

*, /, %

Addition, Subtraction:

+, -

Bitwise operations:

<<, >>,

&, ^, |

Comparisons:

<, <=, >, >=, !=, ==

Membership and Identity:

in, not in, is, is not

Boolean operations:

or, and, not

Anonymous Functions:

lambda

String Literals¶

A “string” is a chunk of text.

You define a string value by writing a string literal:

In [1]: 'a string'
Out[1]: 'a string'

In [2]: "also a string"
Out[2]: 'also a string'

In [3]: "a string with an apostrophe: isn't it cool?"
Out[3]: "a string with an apostrophe: isn't it cool?"

In [4]: 'a string with an embedded "quote"'
Out[4]: 'a string with an embedded "quote"'

In [5]: """a multi-line
   ...: string
   ...: all in one
   ...: """
Out[5]: 'a multi-line\nstring\nall in one\n'

In [6]: "a string with an \n escaped character"
Out[6]: 'a string with an \n escaped character'

In [7]: r'a "raw" string, the \n comes through as a \n'
Out[7]: 'a "raw" string, the \\n comes through as a \\n'

Keywords¶

Python defines a number of keywords

These are language constructs.

You cannot use these words as symbols.

and       del       from      not       while
as        elif      global    or        with
assert    else      if        pass      yield
break     except    import    print
class     exec      in        raise
continue  finally   is        return
def       for       lambda    try

If you try to use any of the keywords as symbols, you will cause a SyntaxError:

In [13]: del = "this will raise an error"
  File "<ipython-input-13-c816927c2fb8>", line 1
    del = "this will raise an error"
        ^
SyntaxError: invalid syntax

In [14]: def a_function(else='something'):
   ....:     print(else)
   ....:
  File "<ipython-input-14-1dbbea504a9e>", line 1
    def a_function(else='something'):
                      ^
SyntaxError: invalid syntax

__builtins__¶

Python also has a number of pre-bound symbols, called builtins

Try this:

In [6]: dir(__builtins__)
Out[6]:
['ArithmeticError',
 'AssertionError',
 'AttributeError',
 'BaseException',
 'BufferError',
 ...
 'unicode',
 'vars',
 'xrange',
 'zip']

You are free to rebind these symbols:

In [15]: type('a new and exciting string')
Out[15]: str

In [16]: type = 'a slightly different string'

In [17]: type('type is no longer what it was')
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-17-907616e55e2a> in <module>()
----> 1 type('type is no longer what it was')

TypeError: 'str' object is not callable

In general, this is a BAD IDEA.

Exceptions¶

Notice that the first batch of __builtins__ are all Exceptions

Exceptions are how Python tells you that something has gone wrong.

There are several exceptions that you are likely to see a lot of:

• NameError: indicates that you have tried to use a symbol that is not bound to a value.
• TypeError: indicates that you have tried to use the wrong kind of object for an operation.
• SyntaxError: indicates that you have mis-typed something.
• AttributeError: indicates that you have tried to access an attribute or method that an object does not have (this often means you have a different type of object than you expect)

Functions¶

What is a function?

A function is a self-contained chunk of code

You use them when you need the same code to run multiple times, or in multiple parts of the program.

(DRY)

Or just to keep the code clean

Functions can take and return information

Minimal Function does nothing

def <name>():
    <statement>

Pass Statement (Note the indentation!)

def minimal():
    pass

Functions: def¶

def is a statement:

• it is executed
• it creates a local name
• it does not return a value

function defs must be executed before the functions can be called:

In [23]: unbound()
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-23-3132459951e4> in <module>()
----> 1 unbound()

NameError: name 'unbound' is not defined

In [18]: def simple():
   ....:     print("I am a simple function")
   ....:

In [19]: simple()
I am a simple function

Calling Functions¶

You call a function using the function call operator (parens):

In [2]: type(simple)
Out[2]: function
In [3]: simple
Out[3]: <function __main__.simple>
In [4]: simple()
I am a simple function

Calling a function is how you run the code in that function.

Functions: Call Stack¶

functions call functions – this makes an execution stack – that’s all a trace back is

In [5]: def exceptional():
   ...:     print("I am exceptional!")
   ...:     print 1/0
   ...:
In [6]: def passive():
   ...:     pass
   ...:
In [7]: def doer():
   ...:     passive()
   ...:     exceptional()
   ...:

You’ve defined three functions, one of which will call the other two.

Functions: Tracebacks¶

In [8]: doer()
I am exceptional!
---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
<ipython-input-8-685a01a77340> in <module>()
----> 1 doer()

<ipython-input-7-aaadfbdd293e> in doer()
      1 def doer():
      2     passive()
----> 3     exceptional()
      4

<ipython-input-5-d8100c70edef> in exceptional()
      1 def exceptional():
      2     print("I am exceptional!")
----> 3     print(1/0)
      4

ZeroDivisionError: integer division or modulo by zero

Functions: return¶

Every function ends by returning a value

This is actually the simplest possible function:

def fun():
    return None

if you don’t explicilty put return there, Python will:

In [9]: def fun():
   ...:     pass
   ...:
In [10]: fun()
In [11]: result = fun()
In [12]: print(result)
None

note that the interpreter eats None – you need to call print() to see it.

Only one return statement in a function will ever be executed.

Ever.

Anything after a executed return statement will never get run.

This is useful when debugging!

In [14]: def no_error():
   ....:     return 'done'
   ....:     # no more will happen
   ....:     print(1/0)
   ....:
In [15]: no_error()
Out[15]: 'done'

However, functions can return multiple results:

In [16]: def fun():
   ....:     return (1, 2, 3)
   ....:
In [17]: fun()
Out[17]: (1, 2, 3)

Remember multiple assignment?

In [18]: x,y,z = fun()
In [19]: x
Out[19]: 1
In [20]: y
Out[20]: 2
In [21]: z
Out[21]: 3

Functions: parameters¶

In a def statement, the values written inside the parens are parameters

In [22]: def fun(x, y, z):
   ....:     q = x + y + z
   ....:     print(x, y, z, q)
   ....:

x, y, z are local names – so is q

Functions: arguments¶

When you call a function, you pass values to the function parameters as arguments

In [23]: fun(3, 4, 5)
3 4 5 12

The values you pass in are bound to the symbols inside the function and used.

The if Statement¶

In order to do anything interesting at all, you need to be able to make a decision.

In [12]: def test(a):
   ....:     if a == 5:
   ....:         print("that's the value I'm looking for!")
   ....:     elif a == 7:
   ....:         print("that's an OK number")
   ....:     else:
   ....:         print("that number won't do!")

In [13]: test(5)
that's the value I'm looking for!

In [14]: test(7)
that's an OK number

In [15]: test(14)
that number won't do!

There is more to it than that, but this will get you started.

Enough For Now¶

That’s it for our basic intro to Python

Before next session, you’ll use what you’ve learned here today to do some exercises in Python programming

Schedule the lightning talks:¶

• We need to schedule your lightning talks.
• Let’s use Python for that !

[demo]

print()¶

In python2, print is a “statement”, rather than a function. That means it didn’t require parenthes around what you want printed:

print something, something_else

This made it a bit less flexible and powerful.

But – if you try to use it that way in Python3, you’ll get an error:

In [15]: print "this"
  File "<ipython-input-15-70c8add5d16e>", line 1
    print "this"
               ^
SyntaxError: Missing parentheses in call to 'print'

So – if you get this error, simply add the parentheses:

In [16]: print ("this")
this

In python 3, the divsion operator is “smart” when you divide integers:

In [17]: 1 / 2
Out[17]: 0.5

However in python2, integer division, will give you an integer result:

In [1]: 1/2
Out[1]: 0

In both versions, you can get “integer division” if you want it with a double slash:

In [1]: 1//2
Out[1]: 0

And in python2, you can get the behavior of py3 with “true division”:

In [2]: from __future__ import division

In [3]: 1/2
Out[3]: 0.5

For the most part, you just need to be a bit careful with the rare cases where py2 code counts on integer division.

Other py2/py3 differences¶

Most of the other differences are essentially of implementation details, like getting iterators instead of sequences – we’ll talk about that more when it comes up in class.

There are also a few syntax differences with more advances topics: Exceptions, super(), etc.

We’ll talk about all that when we cover those topics.

Task 1¶

Make sure you have a working development environment.

Linux: :Setting Up Python For Linux

OS-X: :Setting up your Mac for Python

Windows: :Setting up Windows for Python

Task 2¶

Set Up a Great Dev Environment

Make sure you have the basics of command line usage down:

Work through the supplemental tutorials on setting up your Command Line (:Shell Customizations for Python Development) for good development support.

Make sure you’ve got your editor set up productively – at the very very least, make sure it does Python indentation and syntax coloring well.

Advanced Editor Setup:

If you are using SublimeText, here are some notes to make it super-nifty:

:Turning Sublime Text Into a Lightweight Python IDE

At the end, your editor should support tab completion and pep8 and pyflakes linting.

If you are not using SublimeText, look for plugins that accomplish the same goals for your own editor. If none are available, please consider a change of editor.

Task 3¶

Python Pushups

To get a bit of exercise solving some puzzles with Python, work on the Python exercises at “Coding Bat”: http://codingbat.com/python

There are 8 sets of puzzles. Do as many as you can, but try to at least get all the “Warmups” done.

Task 4¶

Explore Errors

• Create a new directory in your working dir for the class:

  $ mkdir session01
  $ cd session01
  

• Add a new file to it called break_me.py

• In the break_me.py file write four simple Python functions:

  • Each function, when called, should cause an exception to happen
  • Each function should result in one of the four common exceptions from our lecture.
  • for review: NameError, TypeError, SyntaxError, AttributeError

(hint – the interpreter will quit when it hits a Exception – so you can comment out all but the one you are testing at the moment)

• Use the Python standard library reference on Built In Exceptions as a reference

Reading, etc.¶

Every one of you has a different backgrond and learning style.

So take a bit of time to figure out which resource works for you.

Useful Python Learning Resources provides some options. Do look it over.

But here are few to get you started this week:

Think Python: Chapters 1–7 (http://greenteapress.com/thinkpython2/)

Dive Into Python: Chapters 1–2 (http://www.diveintopython3.net/)

LPTHW: ex. 1–10, 18-21 (http://learnpythonthehardway.org/book/)

NOTE: LPTHW is python 2 – you will need to add parentheses to all yoru print calls!

Or follow this excellent introductory tutorial:

http://pyvideo.org/video/1850/a-hands-on-introduction-to-python-for-beginning-p

(also python2 – so same thing with the print function...)

You should be comfortable with working with variables, numbers, strings, and basic functions.

git¶

We’ll be covering the basics of git next week - enough to use for this class. Please read one of these so you’ll have a head start:

http://rogerdudler.github.io/git-guide/

or

https://try.github.io/levels/1/challenges/1

Office Hours¶

We will have office hours 10 a.m. to noon on Sundays.

Preferences?

Locations?