Python Dictionaries

In Python, we can use a dictionary to associate keys with values.

This code creates a simple dictionary called en_to_es (short for “English to Español), that maps the words one, two and three (as Python strings) to their Spanish counterparts (as Python strings):

en_to_es = { 'one' : 'uno', 'two' : 'dos', 'three' : 'tres' }

Once you create a dictionary, you can access the values by looking up their key. Here, we show trying some Python dictionary code at the interactive Python shell:

>>> en_to_es = { 'one' : 'uno', 'two' : 'dos', 'three' : 'tres' }
>>> en_to_es['one']
>>> en_to_es['three']

If a particular key is not in the dictionary, and you try to look it up, you get a KeyError, like this:

>>> en_to_es['ten']
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: 'ten'

Handling KeyError with try/except

You can use a so-called try/except block to write custom code that looks for the KeyError and instead of printing a scary looking error message, does whatever you would prefer:

Suppose we run this file:

def translate(myDictionary,wordToLookup):
    ''' lookup word.  return NoneType value if word not found '''
        return myDictionary[wordToLookup]
    except KeyError:
        print "The word ",wordToLookup," was not in the dictionary"

en_to_es = { 'one' : 'uno', 'two' : 'dos', 'three' : 'tres' }

Then, we can use the function translate to do translation with a “nicer” error message.

=============== RESTART: /Users/pconrad/Documents/ ===============
>>> en_to_es
{'three': 'tres', 'two': 'dos', 'one': 'uno'}
>>> en_to_es['one']
>>> en_to_es['ten']

Traceback (most recent call last):
  File "<pyshell#2>", line 1, in <module>
KeyError: 'ten'
>>> translate(en_to_es,'one')
>>> translate(en_to_es,'ten')
The word  ten  was not in the dictionary

Dictionaries of Dictionaries

Two letter language codes for various human spoken languages have been standardized by the International Standards Organization, ISO, and can be looked up at this web page)

Here are just a few. The third column explains why, for example, German is de and Chinese is zh.

code Language (in English) Language (in that language,
using latin alphabet)
de German Deutsch
en English English
es Spanish Español
fr French Français
fa Persian Farsi
zh Chinese Zhongwen

We could construct a dictionary of these codes like this:

codeToLanguage = {
  'de' : 'German',
  'en' : 'English',
  'es' : 'Spanish',
  'fr' : 'French',
  'fa' : 'Persian',
  'zh' : 'Chinese',

If we wanted to translate the number ‘one’,’two’,’three’ into each of these languages, we could create six different dictionaries, like this:

en_to_de = { 'one' : 'eins', 'two' : 'zwei', 'three' : 'drei' }
en_to_es = { 'one' : 'uno', 'two' : 'dos', 'three' : 'tres' }
en_to_fr = { 'one' : 'un', 'two' : 'deux', 'three' : 'trois' }
# etc ...

But there is a better way. It turns out that the value part in a (key,value) pair can be any type; not just a string. One possibility is that it can, itself, be a dictionary.

This gives us many ways that we could construct a dictionary to translate one,two,three into various languages.

Method 1: Use English number as key, then each entry is a dictionary by language:

numDict = { 
    'one':   {'de' : 'eins', 'es':'uno',  'fa':'yek', 'fr':'un',    'zh':'yi' },
    'two':   {'de' : 'zwei', 'es':'dos',  'fa':'do',  'fr':'deux',  'zh':'er' },
    'three': {'de' : 'drei', 'es':'tres', 'fa':'seh', 'fr':'trois', 'zh':'san' }

In this dictionary, writing numDict['one'] returns to us another dictionary, where the keys are the language codes, ('de', 'es', 'fr', etc.). For example:

>>> numDict['one']
{'fa': 'yek', 'fr': 'un', 'de': 'eins', 'zh': 'yi', 'es': 'uno'}

Note that in a Dictionary, the keys don’t necessary appear in the order that we put them into the dictionary, and they don’t even necessarily appear in any particular order. In technical terms, we say that:

So, to get 'one' in a particular language, we can index the dictionary returned by numDict['one'] a second time, with the language that we want. For example, to get 'one' in Chinese ('zh'), we can use:

>>> numDict['one']['zh']

But that’s not the only way to do it.

Method 2: Index by language, then by word

We could also arrange our dictionary like this:

numberLookup = {
    'de' : { 'one' : 'eins', 'two' : 'zwei', 'three': 'drei'  },
    'es' : { 'one' : 'uno',  'two' : 'dos',  'three': 'tres'  },
    'fa' : { 'one' : 'yek',  'two' : 'do',   'three': 'seh'   },
    'fr' : { 'one' : 'un',   'two' : 'deux', 'three': 'trois' },
    'zh' : { 'one' : 'yi',   'two' : 'er',   'three': 'san'   }

Now, when we use numberLookup['es'] for example, we get a dictionary indexed by the numbers in English, 'one', 'two', 'three'.

>>> numberLookup['es']
{'three': 'tres', 'two': 'dos', 'one': 'uno'}

So, to lookup a particular, number, we add a second index:

>>> numberLookup['es']['two']

Why are dictionaries important?

Dictionaries are one of the most commonly used data structures in “real world” Python programming, because they correspond very nicely to the way that real world data is often structured. This includes data from data bases, websites, etc.

There is a notation called JSON, which stands for JavaScript Object Notation. Although this notation comes from the language JavaScript, it is used across many languages other than JavaScript, including Python.

Many websites and other data services provide access to data in JSON format.

One easy example to see is the social media site

The site has various online communities called subreddits. Most college/universities have one; for example, here are the ones for the various UC Campuses with undergraduate programs:

School Subreddit link School web page  
UC Berkeley  
UC Davis  
UC Irvine
UC Merced  
UC Riverside  
UC San Diego  
UC Santa Barbara  
UC Santa Cruz  

Suppose you visit the page for the UCSD subreddit. If you simply add the following characters: .json to the URL, you’ll get a representation of the content of the page in JSON format:

Here is a snapshot of what some of that JSON looks like. Because it goes on for pages and pages, I’m showing only the first few lines, and this excerpt will likely not be valid since its clipped off in the middle.

{"kind": "Listing", "data": {"modhash": "", "children": [{"kind": "t3", "data": 
{"domain": "self.UCSD", "banned_by": null, "media_embed": {}, "subreddit": "UCSD",
"selftext_html": "&lt;!-- SC_OFF --&gt;&lt;div class=\"md\"&gt;&lt;p&gt;I&amp;#39;m 
basically just copying this directly from last year&amp;#39;s Q&amp;amp;A, but
I don&amp;#39;t think many things have changed. (so thank &lt;a 
href=\"/u/inconditus\"&gt;/u/inconditus&lt;/a&gt; for this, because they wrote most
of it)&lt;/p&gt;\n\n&lt;p&gt;So, you got into UCSD, congratulations! It&amp;#39;s a
great school! But you have questions, most of which the administration can&amp;#39;t 
help you with. Come ask us! I&amp;#39;m rolling over a lot of info from the &lt;a 


The point is that data in JSON format can be easily converted into a Python dictionary.

That topic is explored on another page: Python: JSON