Dictionaries

Python’s built-in dictionary data type provides associative array functionality implemented using hash tables. The built-in len function returns the number of key-value pairs in a dictionary. The del statement can be used to delete a key-value pair. As with Lists , several dictionary methods (clear, copy, get, items, keys, update and values) are available.

>>> x = {1: "eins", 2: "zwei"}
>>> x[3] = "drei"
>>> x["viertes"] = "vier"
>>> list(x.keys())
[1, 2, 3, 'viertes']
>>> x[1]
'eins'
>>> x.get(1, "nicht vorhanden")
'eins'
>>> x.get(5, "nicht vorhanden")
'nicht vorhanden'

Keys must be of immutable type, including Numbers, Strings and Tuples.

Warning

Even if you can use different key types in a dictionary, you should avoid this, as it not only makes it more difficult to read, but also sorting is also made more difficult.

Values can be any type of object, including mutable types such as Lists and Dictionaries. If you try to access the value of a key that is not in the dictionary, a KeyError exception is thrown. To avoid this error, the dictionary method get optionally returns a custom value if a key is not contained in a dictionary.

setdefault

setdefault can be used to provide counters for the keys of a dict, for example:

>>> titles = ["Data types", "Lists", "Sets", "Lists"]
>>> for title in titles:
...     titles_count.setdefault(title, 0)
...     titles_count[title] += 1
...
>>> titles_count
{'Data types': 1, 'Lists': 2, 'Sets': 1}

Note

Such counting operations quickly became widespread, so the collections.Counter class was later added to the Python standard library. This class can perform the above-mentioned operations much more easily:

>>> collections.Counter(titles)
Counter({'Lists': 2, 'Data types': 1, 'Sets': 1})

Merging dictionaries

You can merge two dictionaries into a single dictionary using the dict.update() method:

>>> titles = {7.0: "Data Types", 7.1: "Lists", 7.2: "Tuples"}
>>> new_titles = {7.0: "Data types", 7.3: "Sets"}
>>> titles.update(new_titles)
>>> titles
{7.0: 'Data types', 7.1: 'Lists', 7.2: 'Tuples', 7.3: 'Sets'}

Note

The order of the operands is important, as 7.0 is duplicated and the value of the last key overwrites the previous one.

Extensions

python-benedict

dict subclass with keylist/keypath/keyattr support and I/O shortcuts.

pandas

can convert Dicts into Series and DataFrames.

Checks

• Suppose you have the two dictionaries x = {"a":1, "b":2, "c":3, "d":4} and y = {"a":5, "e":6, "f":7}. What would be the content of x after the following code snippets have been executed?

  >>> del x["b"]
  >>> z = x.setdefault("e", 8)
  >>> x.update(y)
  

  >>> x = {"a": 1, "b": 2, "c": 3, "d": 4}
  >>> y = {"a": 5, "e": 6, "f": 7}
  >>> del x["b"]
  >>> z = x.setdefault("e", 8)
  >>> x.update(y)
  >>> x
  {'a': 5, 'c': 3, 'd': 4, 'e': 6, 'f': 7}
  

• Which of the following expressions can be a key of a dictionary: 1; "Veit"; ("Veit", [1]); [("Veit", [1])]; ["Veit"]; ("Veit", "Tim", "Monique")

  >>> d = {}
  >>> d[1] = None
  >>> d["Veit"] = None
  >>> d[("Veit", [1])]
  Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
  TypeError: unhashable type: 'list'
  >>> d[["Veit"]] = None
  Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
  TypeError: unhashable type: 'list'
  >>> d[("Veit", "Tim", "Monique")] = None
  

• You can use a Dictionary like a spreadsheet table by using Tuples as key row and column values. Write sample code to add and retrieve values.

  >>> sheet = {}
  >>> sheet[("A", 0)] = 1
  >>> sheet[("A", 1)] = 2
  >>> sheet[("B", 0)] = 3
  >>> sheet[("B", 1)] = 4
  >>> print(sheet[("A", 1)])
  2