If you’ve programmed in Python for some time you’ve no doubt used to tuples to move around data in your code. Tuples are a very useful way of grouping related data in a single variable. One issue that often comes up with tuples is that they are very easy to abuse…
In this article we’ll have a look at the Arrow library. Arrow markets itself as Better dates and times for Python. Where the standard library has has a series of modules for handeling dates and times, Arrow offers a refreshing new take on things.
Just about every Python programmer has used the ‘%’ operator for string formatting. But another formatting method is available using the .format() method of the string object. This allows for much cleaner and more readable code than the incantations written using ‘%’ operators.
In a previous Pythonic post we saw list comprehensions, an efficient Pythonic way to create lists. I hope you got hooked and started using list comprehensions where your code could benefit from them. Similar to list comprehensions, Python has a similar feature that’s applicable to dictionaries. The fancy name? Yes, dictionary comprehensions or dict comprehenions. …
Whenever you write code similar to the following:
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index = 0 for element in my_list: # do something with element and index index += 1 |
you should consider making your code a bit more Python by using the builtin enumerate function:
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for index, element in enumerate(my_list): # do something with element and index |
The enumerate function takes an iterable and an optional parameter start (defaulting to 0). The return value is a tuple containing the index of the element and the element …
A common way to build lists in a program that we see is this construct
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squares = [] for i in range(0, 10): squares.append(i**2) |
The basic construct here is that by looping over something (an iterable or a condition) we add items to our list. I’m sure you’ve been there and have already used this construct in some of your code. There is …