Mar 30, 2012 Dictionaries are the fundamental data structure in Python, and a key tool in any Python programmer’s arsenal. They allow O(1) lookup speed, and have been heavily optimized for memory overhead and lookup speed efficiency. Today I”m going to show you three ways of constructing a Python dictionary, as well as some additional tips and tricks. Dictionary in Python is an unordered collection of data values, used to store data values like a map, which unlike other Data Types that hold only single value as an element, Dictionary holds key:value pair. Python File Handling Python Read Files Python Write/Create Files Python Delete Files. The view object contains the keys of the dictionary, as a list. The view object will reflect any changes done to the dictionary, see example below. Dictionary.keys Parameter Values.
With Python, creating and using a dictionary is much like working with a list, except that you must now define a key and value pair. Here are the special rules for creating a key:
The key must be unique. When you enter a duplicate key, the information found in the second entry wins — the first entry is simply replaced with the second.
The key must be immutable. This rule means that you can use strings, numbers, or tuples for the key. You can’t, however, use a list for a key.
You have no restrictions on the values you provide. A value can be any Python object, so you can use a dictionary to access an employee record or other complex data. The following steps help you understand how to use dictionaries better.
1Open a Python Shell window.
You see the familiar Python prompt.
2Type Colors = {“Sam”: “Blue”, “Amy”: “Red”, “Sarah”: “Yellow”} and press Enter.
Python creates a dictionary containing three entries with people’s favorite colors. Notice how you create the key and value pair. The key comes first, followed by a colon and then the value. Each entry is separated by a comma.
3Type Colors and press Enter.
You see the key and value pairs. However, notice that the entries are sorted in key order. A dictionary automatically keeps the keys sorted to make access faster, which means that you get fast search times even when working with a large data set. The downside is that creating the dictionary takes longer than using something like a list because the computer is busy sorting the entries.
4Type Colors[“Sarah”] and press Enter.
You see the color associated with Sarah, Yellow. Using a string as a key, rather than using a numeric index, makes the code easier to read and makes it self-documenting to an extent.
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By making your code more readable, dictionaries save you considerable time in the long run (which is why they’re so popular). However, the convenience of a dictionary comes at the cost of additional creation time and a higher use of resources, so you have trade-offs to consider.
5Type Colors.keys( ) and press Enter.
The dictionary presents a list of the keys it contains. You can use these keys to automate access to the dictionary.
6Type the following code (pressing Enter after each line and pressing Enter twice after the last line):
The example code outputs a listing of each of the user names and the user’s favorite color. Using dictionaries can make creating useful output a lot easier. The use of a meaningful key means that the key can easily be part of the output.
7Type Colors[“Sarah”] = “Purple” and press Enter.
The dictionary content is updated so that Sarah now likes Purple instead of Yellow.
Python Dictionary Get Key Name
8Type Colors.update({“Harry”: “Orange”}) and press Enter.
A new entry is added to the dictionary.
9Place your cursor at the end of the third line of the code you typed in Step 6 and press Enter.
The editor creates a copy of the code for you. This is a time-saving technique that you can use in the Python Shell when you experiment while using code that takes a while to type. Even though you have to type it the first time, you have no good reason to type it the second time.
10Press Enter twice.
Notice that Harry is added in sorted order. In addition, Sarah’s entry is changed to the color Purple.
11Type del Colors[“Sam”] and press Enter.
Python removes Sam’s entry from the dictionary.
12Repeat Steps 9 and 10.
You verify that Sam’s entry is actually gone.
13Type len(Colors) and press Enter.
The output value of 3 verifies that the dictionary contains only three entries now, rather than 4.
14Type Colors.clear( ) and press Enter. Then, Type len(Colors) and press Enter.
Python reports that Colors has 0 entries, so the dictionary is now empty.