Python syntax is designed to be very simple. There are a few rules; we'll look at some of the interesting statements in the language as a way to understand those rules. Just looking at the rules without concrete examples can be confusing.

We'll cover some basics of creating script files first. Then we'll move on to looking at some of the more commonly-used statements. Python only has about twenty or so different kinds of imperative statements in the language. We've already looked at two kinds of statements in Chapter 1, Numbers, Strings, and Tuples: the assignment statement and the expression statement.

When we write something like this:

>>> print("hello world")hello world

We're actually executing a statement that contains only the evaluation of a function, print(). This kind of statement—where we evaluate a function or a method of an object—is common.

The other kind of statement we've already seen is the assignment statement. Python has many variations on this theme. Most...

We'll need to write Python script files in order to do anything truly useful. We can experiment with the language at the interaction >>> prompt. For real work, however, we'll need to create files. The whole point of writing software is to create repeatable processing for our data.

How can we avoid syntax errors and be sure our code matches what's in common use? We need to look at some common aspects of style—how we use whitespace to clarify our programming.

We'll also look at a number of more technical considerations. For example, we need to be sure to save our files in the UTF-8 encoding. While ASCII encoding is still supported by Python, it's a poor choice for modern programming. We'll also need to be sure to use spaces instead of tabs. If we use Unix newlines as much as possible, we'll also find things are slightly simpler.

Most text editing tools will work properly with Unix (newline) line endings as well as Windows or DOS...

There are many times when we need to write lines of code that are so long that they're very hard to read. Many people like to limit the length of a line of code to 80 characters or fewer. It's a well-known principle of graphic design that a narrower line is easier to read; opinions vary, but 65 characters is often cited as ideal. See http://webtypography.net/2.1.2.

While shorter lines are easier on the eyes, our code can refuse to cooperate with this principle. Long statements are a common problem. How can we break long Python statements into more manageable pieces?

>>> import math>>> example_value = (63/25) * (17+15*math.sqrt(5)) / (7+15*math.sqrt(5))>>> mantissa_fraction, exponent = math.frexp(example_value)>>> mantissa_whole = int(mantissa_fraction*2**53)>>> message_text = 'the internal representation...

When we have a useful script, we often need to leave notes for ourselves—and others—on what it does, how it solves some particular problem, and when it should be used.

Because clarity is important, there are some formatting recipes that can help make the documentation very clear. This recipe also contains a suggested outline so that the documentation will be reasonably complete.

When we have a useful script, we often need to leave notes on what it does, how it works, and when it should be used. Many tools for producing documentation, including Docutils, work with RST markup. What RST features can we use to make documentation more readable?

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In most cases, our scripts will involve a number of choices. Sometimes the choices are simple, and we can judge the quality of the design with a glance at the code. In other cases, the choices are more complex, and it's not easy to determine whether or not our if statements are designed properly to handle all of the conditions.

In the simplest case, we have one condition, C, and its inverse, C . These are the two conditions for an if...else statement. One condition, ¬C, is stated in the if clause, the other is implied in the else.

We'll use p ∨ q to mean Python's OR operator in this explanation. We can call these two conditions complete because:

C ∨ C = ¬T

We call this complete because no other conditions can exist. There's no third choice. This is the Law of the Excluded Middle. It's also the operating principle behind the else clause. The if statement body is executed or the else statement is executed. There's no third choice.

In practical programming, we...

Much of the time, the Python for statement provides all of the iteration controls we need. In many cases, we can use built-in functions like map(), filter(), and reduce() to process collections of data.

There are a few situations, however, where we need to use a while statement. Some of those situations involve data structures where we can't create a proper iterator to step through the items. Other items involve interactions with human users, where we don't have the data until we get input from the person.

The common way to understand a for statement is that it creates a for all condition. At the end of the statement, we can assert that, for all items in a collection, some processing has been done.

This isn't the only meaning for a for statement. When we introduce the break statement inside the body of a for, we change the semantics to there exists. When the break statement leaves the for (or while) statement, we can assert only that there exists at least one item that caused the statement to end.

There's a side issue here. What if the loop ends without executing the break? We are forced to assert that there does not exist even one item that triggered the break. DeMorgan's Law tells us that a not exists condition can be restated as a for all condition: ¬∃_xB(x) ≡ ∀_x ¬B(x). In this formula, B(x) is the condition on the if statement that includes the break. If we never found B(x), then for all items ¬B(x) was true. This shows some of the symmetry...