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Lists are not the only iterable in Python, so let’s see how we can use comprehension to create dictionaries
Resources
The Syntax
# basic
{key:value for temp_variable(s) in iterable}
# with a conditional
{key:value for temp_variable(s) in iterable if condition}
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So far, we've looked at loops that
take an original list or string, and
0:00
outputs a new list or string.
0:05
We've been using list comprehensions
with the square brackets,
0:07
because we want our output to be a list or
list to revert it back to a string.
0:11
But, what if we want our return
value to be a dictionary?
0:16
Luckily, dictionary comprehensions
are also a feature of Python.
0:20
Let's say, we want to create a dictionary
that stores integers 1 to 10 and
0:25
their squared values.
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Using a loop, we can iterate through each
number produced by the range function, and
0:32
then add each number and its squared value
as the key and value of a new dictionary.
0:38
Here, we're using a list and
its values to create a dictionary.
0:44
We can also create a new dictionary
from an existing dictionary.
0:50
Let's say, we have a dictionary containing
products and their prices in USD.
0:54
We may wanna produce another
dictionary with the exact same products,
1:01
but with the prices in AUD.
1:05
This can be done with a loop by
stepping through each key value pair
1:08
of the dictionary,
applying the exchange rate, and
1:12
then adding it as another key
value pair in the new dictionary.
1:15
Since both of these can
be done with loops,
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then they can probably be
done using comprehensions.
1:23
This is the dictionary
comprehension syntax.
1:27
Let's break it down.
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The curly brackets are used to hold
the values generated by the dictionary
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comprehension.
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Python dictionaries
are wrapped in curly brackets.
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So, dictionary comprehensions are the same.
1:43
Iterable is the same as before.
1:47
This is the original list or
dictionary that we're pulling data from.
1:49
Temp_ vars is similar to the list
comprehension temporary variable.
1:54
It's what we've looped to
in the original iterable.
1:59
We'll explain why there
might be multiple soon.
2:04
Key, is an expression that returns
what we like to use as the key for
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each key value pair.
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Similarly, value is an expression
that returns what we'd like to use as
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the value for each added key value pair.
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Both of these will make much more
sense once we start working with it.
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So, let's dive right in.
2:27
Open up dictionary comprehension.py.
2:30
Just like before, we have two loops, two
syntax templates and two print statements.
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This first loop, creates a dictionary
that stores numbers 1 to 10,
2:40
produced by this range method and
their squared values.
2:44
It loops through each number, assigns
the temporary variable num as the key and
2:49
then its squared value num to
the power of 2 as the value.
2:54
This second loop, takes a dictionary
of products with prices in USD
3:00
nd creates a new dictionary of
the same products with prices in AUD.
3:05
It loops through each item in
the dictionary, unpacks the product and
3:11
price using items, and
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then uses those values to assign new
key value pairs in the new dictionary.
3:17
If this dictionary looping syntax
looks new, be sure to check
3:21
out the teacher's notes for the course
where this was first introduced.
3:25
Let's run this file to check out
the expected output from both loops.
3:31
With Python3, 5 tab.
3:37
And there we go.
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Now, let's refactor these to
dictionary comprehensions.
3:43
First, let's tackle the dictionary
containing squared values.
3:49
Let's uncomment this template and get
replacing. Original iterable is this range,
3:53
temporary variable,
is this num from our loop.
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Key expression,
is this key right here, num.
4:10
And value expression is the squared value,
so num to the power of 2.
4:15
Let's test this out.
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We'll comment out the original loop,
save the file, and then press up, Enter.
4:24
Great, everything looks the same.
4:32
Now let's refactor the dictionary
to dictionary loop.
4:35
We'll come down here, uncomment
the syntax template and get replacing.
4:40
Original iterable is this
dictionary right here,
4:46
plus the items method to make sure
we can unpack the product and price.
4:50
The key and value is what we've got here,
product and price.
4:57
Key expression is simply
this product right here.
5:04
And value expression is price
times the conversion rate.
5:08
Now for this,
we will use the raw value of 1.49 so
5:12
we can keep everything in one line.
5:17
Let's comment this out,
save the file and try running it.
5:20
It's looking good.
5:27
One more thing we can do here,
5:30
is to apply our conditional
knowledge from the last video.
5:32
Take some time now to try and
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add only the products that are under
5 USD to the new dictionary.
5:39
Pause this video and try to work it out.
5:44
I'll wait.
5:47
Here's what I did, I just added,
5:50
if price is less than 5 to
the end of the comprehension.
5:53
Now, it will loop through the products,
filter out the products where the price is
5:59
greater than 5, which is our butter and
convert the rest.
6:03
Let's save it and see it in action,
and there goes the butter.
6:08
Let's try another challenge.
6:14
Pause the video again and
6:16
try to add only products that
are under 5 AUD to the new dictionary.
6:17
This is the price after we've applied
the exchange rate, I'll wait.
6:23
Here's how I went about it.
6:28
I simply added the exchange
rate to the conditional,
6:31
price times 1.49, super easy, right?
6:36
Let's check it out.
6:40
And now we only have our parsley.
6:43
Great work.
6:45
You've learned about the dictionary
comprehension syntax.
6:46
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