8 Stunning Python Dictionary Tricks That Make Your Code Elegant

Handling dictionaries in a Pythonic way

All Python developers need to operate dictionaries, almost on daily basis.

Beginners may dislike this part, cause they usually have to write a long function to do a simple job.

I saw my girlfriend, who started learning Python last month, write nested for loops to merge two dictionaries.

What I told her was:

Senior Python developers, such as myself😎, can handle dictionaries in a Pythonic and elegant way. — Yang Zhou

This article will introduce the dict operation tricks that are used by senior Python engineers. Hopefully, you can get some new ideas after reading. 🙂

1. Using Union Operators To Merge Dictionaries

Of course, you can write for loops to combine the elements of different dictionaries.

But since Python 3.9, you never need to do it manually.

Using the union operations is the simplest way to merge dictionaries.

You can also make an in-place update using |=:

2. Unpacking Dictionaries with Asterisks

Due to its simplicity, I’ll always use the union operator if it’s possible.

However, there are inevitably some projects made with older versions of Python in your company. Do you need to write many lines of code for them?

No, you can use the dictionary unpacking trick instead:

As above, with the help of two asterisks, you can easily unpack and merge Python dictionaries.

3. Using Dictionary Comprehension To Create Dictionaries

Like list comprehensions in Python, the dict comprehension, which is a stunning way to create dictionaries, gives us the flexibility to filter our data, since it can contain the if statement. The template of the dict comprehension is as follows:

D = {key: value for key,value in iterable (if condition)}

The following example, which leverages the power of dict comprehensions, generates a dict from two lists in one line of code:

4. Reversing Keys and Values of a Dictionary

There are many one-liner ways to reverse the keys and values of a dict.

The follows are my favourite three methods:

5. Converting Lists Into Dictionaries

The list is a commonly-used data structure as well. In some cases, we need to convert lists into dictionaries.

If the list contains “keys” and “values”:

If not:

6. Sorting a Dictionary

Only one line of code is needed to sort a list as you like:

7. Using Defaultdict

When you get the value of a dict by a non-existing key, an exception will be raised:

>>> city = {'UK':'London','Japan':'Tokyo'}
>>> print(city['Italy'])
# KeyError: 'Italy'

To avoid unexpected issues, a good solution is to use the defaultdict:

from collections import defaultdict
city = defaultdict(str)
city['UK'] = 'London'
print(city['Italy'])
#

As shown above, with the help of the defaultdict(), we can avoid exceptions even if requiring a non-existing key.

8. Using Counter

If you are curious about how many times each letter is used in a string, the most intuitive way may write a for loop to go through all letters and calculate the numbers.

But if you know Counter, the above task will be as simple as the following code:

As its name implies, the Counter object helps us do the calculation part and saves the results as a dictionary. It can save you lots of code-writing time if you can remember this special dict in similar using scenarios.

Conclusion

Learning Python means that you can write a program returning correct results.

Mastering Python means that you can write the same program in an elegant, neat and Pythonic way.

The longer you use Python, the more you will like it. 🙂

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