What idioms should I use to make my code easier to read?
Read "The Python Cookbook", especially the first few chapters.
It's a great source of well-written Python code examples.
Use function factories to create utility functions.
Often, especially if you're using map and filter a lot,
you need utility functions that convert other functions or methods to
taking a single parameter. In particular, you often want to bind some data
to the function once, and then apply it repeatedly to different objects.
In the above example, we needed a function that multiplied a particular field
of an object by 3, but what we really want is a factory that's able to return
for any field name and amount a multiplier function in that family:
Use zip and dict to map fields to names.
zip turns a pair of sequences into a list of tuples containing
the first, second, etc. values from each sequence. For example,
zip('abc', [1,2,3]) == [('a',1),('b',2),('c',3)]. You can use
this to save a lot of typing when you have fields in a known order that
you want to map to names:
To attempt to explain it in the simplest terms, a continuation is a
representation, at a particular point in a program, of
everything the program is capable of doing subsequently. A
continuation is a potential that depends on initial conditions.
Rather than loop in a traditional way, it is possible to invoke
the same continuation recursively with different initial
conditions. One broad claim I have read is that
continuations, in a theoretical sense, are more fundamental and
underlie every other control structure. Don't worry if these
ideas cause your brain to melt; that is a normal reaction.
Defining the travel and tourism industry is a challenge, since it includes other industries offering various services. In a broad sense, the industry is about transportation and logistics. It's also about catering to travelers' needs for lodging, attractions, and dining after they arrive at the destination. Since 2006, the travel industry has been one of the greatest contributors to global GDP, contributing around 2.9 trillion US dollars in 2019, which is 79% more than 13 years before.