Intro-to-Python-Part-1-first-part-edition.pdf

Introduction to Python
Part 1
Brian Gregor
Research Computing Services
Information Services & Technology

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About You
 Working with Python already?
 Have you used any other programming languages?
 Why do you want to learn Python?

Running Python for the Tutorial
 If you have an SCC account, log into it and use Python
there.
 Run:
module load python/3.6.2
spyder &

Links on the Rm 107 Terminals
 On the Desktop open the folders:
Tutorial Files  RCS_Tutorials  Tutorial Files  Introduction to Python
 Copy the whole Introduction to Python folder to the desktop or to a flash
drive.
 When you log out the desktop copy will be deleted!


Run Spyder
 Click on the Start Menu in
the bottom left corner and
type: spyder
 After a second or two it will
be found. Click to run it.

Running Python: Installing it yourself
 There are many ways to install Python on your laptop/PC/etc.
 https://www.python.org/downloads/
 https://www.anaconda.com/download/
 https://www.enthought.com/product/enthought-python-distribution/
 https://python-xy.github.io/

BU’s most popular option: Anaconda
 https://www.anaconda.com/download/
 Anaconda is a packaged set of programs including the Python language,
a huge number of libraries, and several tools.
 These include the Spyder development environment and Jupyter
notebooks.
 Anaconda can be used on the SCC, with some caveats.

Python 2 vs. 3
 Python 2: released in 2000, Python 3 released in 2008
 Python 2 is in “maintenance mode” – no new features are expected
 Py3 is not completely compatible with Py2
 For learning Python these differences are almost negligible
 Which one to learn?
 If your research group / advisor / boss / friends all use one version that’s probably the best one
for you to choose.
 If you have a compelling reason to focus on one vs the other
 Otherwise just choose Py3. This is where the language development is happening!

Spyder – a Python development environment
 Pros:
 Faster development
 Easier debugging!
 Helps organize code
 Increased efficiency
 Cons
 Learning curve
 Can add complexity to smaller
problems

Tutorial Outline – Part 1
 What is Python?
 Operators
 Variables
 If / Else
 Lists
 Loops
 Functions

Tutorial Outline – Part 2
 Functions
 Tuples and dictionaries
 Modules
 numpy and matplotlib modules
 Script setup
 Classes
 Debugging

What is Python?
 Python…
 …is a general purpose interpreted programming language.
 …is a language that supports multiple approaches to software design,
principally structured and object-oriented programming.
 …provides automatic memory management and garbage collection
 …is extensible
 …is dynamically typed.
 By the end of the tutorial you will understand all of these terms!

Some History
 “Over six years ago, in December 1989, I was looking for a "hobby"
programming project that would keep me occupied during the week
around Christmas…I chose Python as a working title for the project, being
in a slightly irreverent mood (and a big fan of Monty Python's Flying
Circus).”
–Python creator Guido Van Rossum, from the foreward to Programming Python (1st
ed.)
 Goals:
 An easy and intuitive language just as powerful as major competitors
 Open source, so anyone can contribute to its development
 Code that is as understandable as plain English
 Suitability for everyday tasks, allowing for short development times

Compiled Languages (ex. C++ or Fortran)

Interpreted Languages (ex. Python or R)
Source code files
prog.py
math.py
Python interpreter
bytecode
conversion
Python interpreter:
follows bytecode
instructions
python prog.py
 Clearly, a lot less work is done to get a program to start running compared with compiled
languages!
 Bytecodes are an internal representation of the text program that can be efficiently run by
the Python interpreter.
 The interpreter itself is written in C and is a compiled program.

Comparison
Interpreted
 Faster development
 Easier debugging
 Debugging can stop anywhere, swap in
new code, more control over state of
program
 (almost always) takes less code to
get things done
 Slower programs
 Sometimes as fast as compiled, rarely
faster
 Less control over program behavior
Compiled
 Longer development
 Edit / compile / test cycle is longer!
 Harder to debug
 Usually requires a special compilation
 (almost always) takes more code to
get things done
 Faster
 Compiled code runs directly on CPU
 Can communicate directly with
hardware
 More control over program behavior

The Python Prompt
 The standard Python prompt looks like this:
 The IPython prompt in Spyder looks like this:
 IPython adds some handy behavior around the standard Python prompt.

The Spyder IDE
editor
Python console
Variable and file explorer

Operators
 Python supports a wide variety of operators which act like functions, i.e.
they do something and return a value:
 Arithmetic: + - * / % **
 Logical: and or not
 Comparison: > < >= <= != ==
 Assignment: =
 Bitwise: & | ~ ^ >> <<
 Identity: is is not
 Membership: in not in

Try Python as a calculator
 Go to the Python prompt.
 Try out some arithmetic operators:
+ - * / % ** == ( )
 Can you identify what they all do?

Try Python as a calculator
 Go to the Python prompt.
 Try out some arithmetic operators:
+ - * / % ** == ()
Operator Function
+ Addition
- Subtraction
* Multiplication
/ Division (Note: 3 / 4 is 0.75!)
% Remainder (aka modulus)
** Exponentiation
== Equals

More Operators
 Try some comparisons and Boolean operators. True and False are the
keywords indicating those values:

Comments
 # is the Python comment character. On
any line everything after the # character
is ignored by Python.
 There is no multi-line comment
character as in C or C++.
 An editor like Spyder makes it very easy
to comment blocks of code or vice-
versa. Check the Edit menu

Variables
 Variables are assigned values using the = operator
 In the Python console, typing the name of a variable
prints its value
 Not true in a script!
 Variables can be reassigned at any time
 Variable type is not specified
 Types can be changed with a reassignment

Variables cont’d
 Variables refer to a value stored in memory and are created when first
assigned
 Variable names:
 Must begin with a letter (a - z, A - B) or underscore _
 Other characters can be letters, numbers or _
 Are case sensitive: capitalization counts!
 Can be any reasonable length
 Assignment can be done en masse:
x = y = z = 1
 Multiple assignments can be done on one line:
x, y, z = 1, 2.39, 'cat'
Try these out!

Variable Data Types
 Python determines data types for variables based on the context
 The type is identified when the program runs, called dynamic typing
 Compare with compiled languages like C++ or Fortran, where types are identified by
the programmer and by the compiler before the program is run.
 Run-time typing is very convenient and helps with rapid code
development…but requires the programmer to do more code testing for
reliability.
 The larger the program, the more significant the burden this is!!

Variable Data Types
 Available basic types:
 Numbers: Integers and floating point (64-bit)
 Complex numbers: x = complex(3,1) or x = 3+1j
 Strings, using double or single quotes: "cat" 'dog'
 Boolean: True and False
 Lists, dictionaries, and tuples
 These hold collections of variables
 Specialty types: files, network connections, objects
 Custom types can be defined. This will be covered in Part 2.

Variable modifying operators
 Some additional arithmetic operators that modify variable values:
 The += operator is by far the most commonly used of these!
Operator Effect Equivalent to…
x += y Add the value of y to x x = x + y
x -= y Subtract the value of y
from x
x = x - y
x *= y Multiply the value of x
by y
x = x * y
x /= y Divide the value of x by
y
x = x / y

Check a type
 A built-in function, type(), returns the
type of the data assigned to a variable.
 It’s unusual to need to use this in a
program, but it’s available if you need it!
 Try this out in Python – do some
assignments and reassignments and
see what type() returns.

Strings
 Strings are a basic data type in Python.
 Indicated using pairs of single '' or
double "" quotes.
 Multiline strings use a triple set of
quotes (single or double) to start and
end them.
 Strings have many built-in functions…

String functions
 In the Python console, create a string variable
called mystr
 type: dir(mystr)
 Try out some functions:
 Need help? Try:
help(mystr.title)
len(mystr)
mystr.upper()
mystr.title()
mystr.isdecimal()
help(mystr.isdecimal)

The len() function
 The len() function is not a string specific function.
 It’ll return the length of any Python variable that contains
some sort of countable thing.
 In the case of strings it is the number of characters in the
string.

String operators
 Try using the + and += operators with strings in the
Python console.
 + concatenates strings.
 += appends strings.
 Index strings using square brackets, starting at 0.

String operators
 Changing elements of a string by an index is not allowed:
 Python strings are immutable, i.e. they can’t be changed.

String Substitutions
 Python provides an easy way
to stick variable values into
strings called substitutions
 Syntax for one variable:
 For more than one:
%s means sub in
value
variable name
comes after a %
Variables are listed in the
substitution order inside ()

Variables with operators
 Operators can be combined
freely with variables and
variable assignment.
 Try some out again!
 This time type them into the
editor. Click the green
triangle to run the file. Save
the file and it will run.

Spyder setup
 The first time you run a script Spyder
will prompt you with a setup dialog:
 Just click “Run” to run the script. This
will only appear once.

 The Variable Explorer
window is displaying
variables and types
defined in the console.
 Only the print function
printed values from the
script.
 Key difference between
scripts and the console!

If / Else
 If, elif, and else statements are used to implement conditional program
behavior
 Syntax:
 elif and else are not required – used to chain together multiple conditional
statements or provide a default case.
if Boolean_value:
…some code
elif Boolean_value:
…some other code
else:
…more code

 Try out something like this in the Spyder
editor.
 Do you get any error messages in the
console?
 Try using an elif or else statement by
itself without a preceding if. What error
message comes up?

Indentation of code…easier on the eyes!
 C:
or
 Matlab:
or

The Use of Indentation
 Python uses whitespace (spaces or tabs) to define code blocks.
 Code blocks are logical groupings of commands. They are always
preceded by a colon :
 This is due to an emphasis on code readability.
 Fewer characters to type and easier on the eyes!
 Spaces or tabs can be mixed in a file but not within a code block.
A code block
Another code block

If / Else code blocks
 Python knows a code block has
ended when the indentation is
removed.
 Code blocks can be nested
inside others therefore if-elif-else
statements can be freely nested
within others. • Note the lack of “end if”,
“end”, curly braces, etc.

File vs. Console Code Blocks
 Python knows a code block
has ended when the
indentation is removed.
 EXCEPT when typing code
into the Python console.
There an empty line indicates
the end of a code block.
 Let’s try this out in Spyder
 This sometimes causes
problems when pasting code
into the console.
 This issue is something the
IPython console helps with.

Lists
 A Python list is a general purpose 1-dimensional container for variables.
 i.e. it is a row, column, or vector of things
 Lots of things in Python act like lists or use list-style notation.
 Variables in a list can be of any type at any location, including other lists.
 Lists can change in size: elements can be added or removed
 Lists are not meant for high performance numerical computing!
 We’ll cover a library for that in Part 2
 Please don’t implement your own linear algebra with Python lists unless it’s for your
own educational interests.

Making a list and checking it twice…
 Make a list with [ ] brackets.
 Append with the append() function
 Create a list with some initial elements
 Create a list with N repeated elements
Try these out yourself!
Edit the file in Spyder and run it.
Add some print() calls to see the lists.

List functions
 Try dir(list_1)
 Like strings, lists have a number of
built-in functions
 Let’s try out a few…
 Also try the len() function to see how
many things are in the list: len(list_1)

Accessing List Elements
 Lists are accessed by index.
 All of this applies to accessing strings by index as well!
 Index #’s start at 0.
 List: x=['a', 'b', 'c', 'd' ,'e']
 First element: x[0]
 Nth element: x[2]
 Last element: x[-1]
 Next-to-last: x[-2]

List Indexing
 Elements in a list are accessed by an index number.
 Index #’s start at 0.
 List: x=['a', 'b', 'c', 'd' ,'e']
 First element: x[0]  'a'
 Nth element: x[2]  'c'
 Last element: x[-1] 'e'
 Next-to-last: x[-2] 'd'

List Slicing
 List: x=['a', 'b', 'c', 'd' ,'e']
 Slice syntax: x[start:end:step]
 The start value is inclusive, the end value is exclusive.
 Step is optional and defaults to 1.
 Leaving out the end value means “go to the end”
 Slicing always returns a new list copied from the existing list
 x[0:1]  ['a']
 x[0:2]  ['a','b']
 x[-3:]  ['c', 'd', 'e'] # Third from the end to the end
 x[2:5:2]  ['c', 'e']

List assignments and deletions
 Lists can have their elements overwritten or deleted (with the del) command.
 List: x=['a', 'b', 'c', 'd' ,'e']
 x[0] = -3.14  x is now [-3.14, 'b', 'c', 'd', 'e']
 del x[-1]  x is now [-3.14, 'b', 'c', 'd']

DIY Lists
 In the Spyder editor try the following things:
 Assign some lists to some variables.
 Try an empty list, repeated elements, initial set of elements
 Add two lists: a + b What happens?
 Try list indexing, deletion, functions from dir(my_list)
 Try assigning the result of a list slice to a new variable
• Go to the menu FileNew File
• Enter your list commands there
• Give the file a name when you save it
• Use print() to print out results

More on Lists and Variables
 Open the sample file list_variables.py
but don’t run it yet!
 What do you think will be printed?
 Now run it…were you right?

Variables and Memory Locations
 Variables refer to a value stored in
memory.
 y = x does not mean “make a copy of
the list x and assign it to y” it means
“make a copy of the memory location in
x and assign it to y”
 x is not the list it’s just a reference to it.
x
y

Copying Lists
 How to copy (2 ways…there are more!):
 y = x[:] or y=list(x)
 In list_variables.py uncomment the code at the bottom and run it.
 This behavior seems weird at first. It will make more sense when calling
functions.

While Loops
 While loops have a condition and a
code block.
 the indentation indicates what’s in the while loop.
 The loop runs until the condition is false.
 The break keyword will stop a while
loop running.
 In the Spyder edit enter in some
loops like these. Save and run them
one at a time. What happens with
the 1st loop?

For loops
 for loops are a little different. They
loop through a collection of things.
 The for loop syntax has a collection
and a code block.
 Each element in the collection is accessed in
order by a reference variable
 Each element can be used in the code block.
 The break keyword can be used in for
loops too.
collection
In-loop reference
variable for each
collection element
The code block

Processing lists element-by-element
 A for loop is a convenient way to process every element in a list.
 There are several ways:
 Loop over the list elements
 Loop over a list of index values and access the list by index
 Do both at the same time
 Use a shorthand syntax called a list comprehension
 Open the file looping_lists.py
 Let’s look at code samples for each of these.

The range() function
 The range() function auto-generates sequences of numbers that can be
used for indexing into lists.
 Syntax: range(start, exclusive end, increment)
 range(0,4)  produces the sequence of numbers 0,1,2,3
 range(-3,15,3)  -3,0,3,6,9,12
 range(4,-3,2)  4,2,0,-2
 Try this: print(range(4))

Lists With Loops
 Open the file read_a_file.py
 This is an example of reading a file
into a list. The file is shown to the
right, numbers.txt
 We want to read the lines in the file
into a list of strings (1 string for each
line), then extract separate lists of
the odd and even numbers.
odds  [1,3,5…]
evens  [2,4,6…]
• Edit read_a_file.py and try to
figure this out.
• A solution is available in
read_a_file_solved.py
• Use the editor and run the code
frequently after small changes!

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