Reference – Building Programs with Python

Key Points

Python Basics	Start the python interpreter by typing `python` in the shell. Variables are named memory locations, they are used to access data.
Arrays, Lists etc	A list is an ordered collection of items of any type. Values in the list can be accessed using their index in square brackets e.g. my_list[ix] Lists can be manipulated in place using attribute functions e.g. my_list.reverse() Ranges of values in a list can be obtained via slicing e.g. mylist[start:stop]
Repeating actions using loops	We can use the ‘for in’ syntax to loop over collections or generators.
Processing data files	The python function `open` lets us read `r` or write `w` to files by creating a file handler. We can use string operations such as `line.split(',')` to process data in files.
Making choices	We can use logical operations to change the behavior of our code when it meets certain conditions. Using if, elif, and else we can check conditions and add a branch that runs if none of the conditions are met. We can combine conditions using `and` and `or` to make more complicated logical statements.
Modularising your code using functions	A function is created using the `def` keyword. Functions take variables that are specified in the function definition and use the `return` keyword to specify their output. We can use a module to keep our functions separate to the main body of our code to improve code readability.
Handling Errors	Python has built in error names that give a hint to the type of problem you are looking for. We can use the traceback to find which bit of the code threw an error.
Command-Line Programs	Python uses the `sys` library to acess command line arguments. `sys.argv` is a list of command line arguments. Python program outputs can be used in a pipeline, however, due to the way python works we need to use the `signal` library to make sure it handles piping output correctly.
Reading and analysing Patient data using libraries	Python has many libraries that add to the core language to improve functionality in specific use cases. Numpy is a numerical python library that makes working with vectors, matricies, or large data tables easier. Numpy can be used to load datasets directly from CSV files bypassing Pythons built in file systems.
Data Visualisation	We can use `matplotlib` to create and manipulate a wide variety of plots in Python. Once a plot has been made we can use matplotlib’s function `savefig` to output it in formats appropriate for publication.
Python Style Guide	Pep8 provides a guide for styling your python code.
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Challenges
Why Python?

Analyzing Patient Data

Import a library into a program using import libraryname.
Use the numpy library to work with arrays in Python.
Use variable = value to assign a value to a variable in order to record it in memory.
Variables are created on demand whenever a value is assigned to them.
Use print something to display the value of something.
The expression array.shape gives the shape of an array.
Use array[x, y] to select a single element from an array.
Array indices start at 0, not 1.
Use low:high to specify a slice that includes the indices from low to high-1.
All the indexing and slicing that works on arrays also works on strings.
Use # some kind of explanation to add comments to programs.
Use array.mean(), array.max(), and array.min() to calculate simple statistics.
Use array.mean(axis=0) or array.mean(axis=1) to calculate statistics across the specified axis.
Use the pyplot library from matplotlib for creating simple visualizations.

Creating Functions

Define a function using def name(...params...).
The body of a function must be indented.
Call a function using name(...values...).
Numbers are stored as integers or floating-point numbers.
Integer division produces the whole part of the answer (not the fractional part).
Each time a function is called, a new stack frame is created on the call stack to hold its parameters and local variables.
Python looks for variables in the current stack frame before looking for them at the top level.
Use help(thing) to view help for something.
Put docstrings in functions to provide help for that function.
Specify default values for parameters when defining a function using name=value in the parameter list.
Parameters can be passed by matching based on name, by position, or by omitting them (in which case the default value is used).

Repeating Actions with Loops

Use for variable in collection to process the elements of a collection one at a time.
The body of a for loop must be indented.
Use len(thing) to determine the length of something that contains other values.

Storing Multiple Values in Lists

[value1, value2, value3, ...] creates a list.
Lists are indexed and sliced in the same way as strings and arrays.
Lists are mutable (i.e., their values can be changed in place).
Strings are immutable (i.e., the characters in them cannot be changed).

Analyzing Data in Multiple Files

Use glob.glob(pattern) to create a list of files whose names match a pattern.
Use * in a pattern to match zero or more characters, and ? to match any single character.

Making Choices

Use the ImageGrid class from the ipythonblocks library to create simple “images” made of colored blocks.
Specify colors use (red, green, blue) triples, each component of which is an integer in the range 0..255.
Use if condition to start a conditional statement, elif condition to provide additional tests, and else to provide a default.
The bodies of the branches of conditional statements must be indented.
Use == to test for equality.
X and Y is only true if both X and Y are true.
X or Y is true if either X or Y, or both, are true.
Zero, the empty string, and the empty list are considered false; all other numbers, strings, and lists are considered true.
Nest loops to operate on multi-dimensional data.
Put code whose parameters change frequently in a function, then call it with different parameter values to customize its behavior.

Command-Line Programs

The sys library connects a Python program to the system it is running on.
The list sys.argv contains the command-line arguments that a program was run with.
Avoid silent failures.
The “file” sys.stdin connects to a program’s standard input.
The “file” sys.stdout connects to a program’s standard output.

Glossary

additive color model: A way to represent colors as the sum of contributions from primary colors such as red, green, and blue.
argument: A value given to a function or program when it runs. The term is often used interchangeably (and inconsistently) with parameter.
assertion: An expression which is supposed to be true at a particular point in a program. Programmers typically put assertions in their code to check for errors; if the assertion fails (i.e., if the expression evaluates as false), the program halts and produces an error message. See also: invariant, precondition, postcondition.
assign: To give a value a name by associating a variable with it.
body: (of a function): the statements that are executed when a function runs.
call stack: A data structure inside a running program that keeps track of active function calls.
case-insensitive: Treating text as if upper and lower case characters of the same letter were the same. See also: case-sensitive.
case-sensitive: Treating text as if upper and lower case characters of the same letter are different. See also: case-insensitive.
comment: A remark in a program that is intended to help human readers understand what is going on, but is ignored by the computer. Comments in Python, R, and the Unix shell start with a # character and run to the end of the line; comments in SQL start with --, and other languages have other conventions.
compose: To apply one function to the result of another, such as f(g(x)).
conditional statement: A statement in a program that might or might not be executed depending on whether a test is true or false.
comma-separated values: (CSV) A common textual representation for tables in which the values in each row are separated by commas.
default value: A value to use for a parameter if nothing is specified explicitly.
defensive programming: The practice of writing programs that check their own operation to catch errors as early as possible.
delimiter: A character or characters used to separate individual values, such as the commas between columns in a CSV file.
docstring: Short for “documentation string”, this refers to textual documentation embedded in Python programs. Unlike comments, docstrings are preserved in the running program and can be examined in interactive sessions.
documentation: Human-language text written to explain what software does, how it works, or how to use it.
dotted notation: A two-part notation used in many programming languages in which thing.component refers to the component belonging to thing.
empty string: A character string containing no characters, often thought of as the “zero” of text.
encapsulation: The practice of hiding something’s implementation details so that the rest of a program can worry about what it does rather than how it does it.
floating-point number: A number containing a fractional part and an exponent. See also: integer.
for loop: A loop that is executed once for each value in some kind of set, list, or range. See also: while loop.
function call: A use of a function in another piece of software.
immutable: Unchangeable. The value of immutable data cannot be altered after it has been created. See also: mutable.
import: To load a library into a program.
in-place operators: An operator such as += that provides a shorthand notation for the common case in which the variable being assigned to is also an operand on the right hand side of the assignment. For example, the statement x += 3 means the same thing as x = x + 3.
index: A subscript that specifies the location of a single value in a collection, such as a single pixel in an image.
inner loop: A loop that is inside another loop. See also: outer loop.
integer: A whole number, such as -12343. See also: floating-point number.
invariant: An expression whose value doesn’t change during the execution of a program, typically used in an assertion. See also: precondition, postcondition.
library: A family of code units (functions, classes, variables) that implement a set of related tasks.
loop variable: The variable that keeps track of the progress of the loop.
member: A variable contained within an object.
method: A function which is tied to a particular object. Each of an object’s methods typically implements one of the things it can do, or one of the questions it can answer.
object: FIXME
outer loop: A loop that contains another loop. See also: inner loop.
parameter: A variable named in the function’s declaration that is used to hold a value passed into the call. The term is often used interchangeably (and inconsistently) with argument.
pipe: A connection from the output of one program to the input of another. When two or more programs are connected in this way, they are called a “pipeline”.
postcondition: A condition that a function (or other block of code) guarantees is true once it has finished running. Postconditions are often represented using assertions.
precondition: A condition that must be true in order for a function (or other block of code) to run correctly.
regression: To re-introduce a bug that was once fixed.
return statement: A statement that causes a function to stop executing and return a value to its caller immediately.
RGB: An additive model that represents colors as combinations of red, green, and blue. Each color’s value is typically in the range 0..255 (i.e., a one-byte integer).
sequence: FIXME
shape: An array’s dimensions, represented as a vector. For example, a 5×3 array’s shape is (5,3).
silent failure: Failing without producing any warning messages. Silent failures are hard to detect and debug.
slice: A regular subsequence of a larger sequence, such as the first five elements or every second element.
stack frame: A data structure that provides storage for a function’s local variables. Each time a function is called, a new stack frame is created and put on the top of the call stack. When the function returns, the stack frame is discarded.
standard input: A process’s default input stream. In interactive command-line applications, it is typically connected to the keyboard; in a pipe, it receives data from the standard output of the preceding process.
standard output: A process’s default output stream. In interactive command-line applications, data sent to standard output is displayed on the screen; in a pipe, it is passed to the standard input of the next process.
string: Short for “character string”, a sequence of zero or more characters.
syntax error: CHECKME: a programming error that occurs when statements are in an order or contain characters not expected by the programming language
test oracle: A program, device, data set, or human being against which the results of a test can be compared.
test-driven development: The practice of writing unit tests before writing the code they test.
traceback: CHECKME In Python, a list of the sequence of function calls that led to an error.
tuple: An immutable sequence of values.
type: CHECKME The classification of something in a program (for example, the contents of a variable) as a kind of number (e.g. floating-point, integer), string, or something else.
type of error: CHECKME Indicates the nature of an error in a program, for example, IOError in Python refers to problems in input/output. See also syntax error.
while loop: A loop that keeps executing as long as some condition is true. See also: for loop.

Building Programs with Python: Reference

Key Points

Glossary