One-line Tree Datastructure in Python

Definition

Using Python's built-in defaultdict we can easily define a tree structure:

def tree(): return defaultdict(tree)

That's it! Think about it.

(If you're following along at home, make sure to from collections import defaultdict)

Examples

JSON-esque

Now we can create JSON-esque nested dictionaries without explicitly creating sub-dictionaries—they magically come into existence as we reference them:

users = tree()
users['harold']['username'] = 'hrldcpr'
users['handler']['username'] = 'matthandlersux'

We can print this as json with print(json.dumps(users)) and we get the expected:

{"harold": {"username": "hrldcpr"}, "handler": {"username": "matthandlersux"}}

Without assignment

We can even create structure with no assignment at all:

taxonomy = tree()
taxonomy['Animalia']['Chordata']['Mammalia']['Carnivora']['Felidae']['Felis']['cat']
taxonomy['Animalia']['Chordata']['Mammalia']['Carnivora']['Felidae']['Panthera']['lion']
taxonomy['Animalia']['Chordata']['Mammalia']['Carnivora']['Canidae']['Canis']['dog']
taxonomy['Animalia']['Chordata']['Mammalia']['Carnivora']['Canidae']['Canis']['coyote']
taxonomy['Plantae']['Solanales']['Solanaceae']['Solanum']['tomato']
taxonomy['Plantae']['Solanales']['Solanaceae']['Solanum']['potato']
taxonomy['Plantae']['Solanales']['Convolvulaceae']['Ipomoea']['sweet potato']

We'll prettyprint this time, which requires us to convert to standard dicts first:

def dicts(t): return {k: dicts(v) for k,v in t.items()}

Now we can print the structure with pprint(dicts(taxonomy)):

{'Animalia': {'Chordata': {'Mammalia': {'Carnivora': {'Canidae': {'Canis': {'coyote': {},
                                                                            'dog': {}}},
                                                      'Felidae': {'Felis': {'cat': {}},
                                                                  'Panthera': {'lion': {}}}}}}},
 'Plantae': {'Solanales': {'Convolvulaceae': {'Ipomoea': {'sweet potato': {}}},
                           'Solanaceae': {'Solanum': {'potato': {},
                                                      'tomato': {}}}}}}

So the substructures we referenced now exist as dicts, with empty dicts at the leaves.

Iteration

This tree can be fun to iteratively walk through, again because structure comes into being simply by referring to it.

For example, suppose we are parsing a list of new animals to add to our taxonomy above, so we want to call a function like:

insert(taxonomy, 'Animalia,Chordata,Mammalia,Cetacea,Balaenopteridae,Balaenoptera,blue whale'.split(','))

We can implement this simply as:

def insert(t, keys):
  for key in keys:
    t = t[key]

Again we are never assigning to the dictionary, but just by referencing the keys we have created our new structure:

{'Animalia': {'Chordata': {'Mammalia': {'Carnivora': {'Canidae': {'Canis': {'coyote': {},
                                                                            'dog': {}}},
                                                      'Felidae': {'Felis': {'cat': {}},
                                                                  'Panthera': {'lion': {}}}},
                                        'Cetacea': {'Balaenopteridae': {'Balaenoptera': {'blue whale': {}}}}}}},
 'Plantae': {'Solanales': {'Convolvulaceae': {'Ipomoea': {'sweet potato': {}}},
                           'Solanaceae': {'Solanum': {'potato': {},
                                                      'tomato': {}}}}}}