''' Initialize a dictionary with n key-value pairs. We used the following code to generate this graphic: import time Method 5 needed 0.93 seconds for 100 million dict entries.Method 4 needed 0.58 seconds for 100 million dict entries.Method 3 needed 0.69 seconds for 100 million dict entries.Method 2 needed 0.67 seconds for 100 million dict entries.Method 1 needed 0.69 seconds for 100 million dict entries.The winner Method 4 is 38% faster than the slowest Method 5 and 14% faster than the next fastest. Each key-value pair maps the key to its associated value. A dictionary consists of a collection of key-value pairs. ⚡ Experiment Results: The output shows that Method 4 is the fastest and scaled best, followed by Method 2, Method 3, Method 1, and finally Method 5 (the slowest). Dictionaries are Python’s implementation of a data structure that is more generally known as an associative array. This allowed us to stress-test the dictionary creation functions discussed in this article on large inputs to generate dictionaries with up to 100 million (!) entries. We used an Intel Core i7 with 1.8GHz TurboBost up to 4.6 GHz with 8GB DDR4 Memory and 512GB storage (not that it mattered) to compare each of the five methods on various values of n-using an exponentially increasing function as shown in the code below. □ Recommended Tutorial: Understanding Python Loops from the Ground Up Performance Evaluation Here are all of the methods of list objects: list.append(x) Add an item to the end of the list. Python works hard to make local variable lookups fast, and this is the only part of the chain that doesnt require a dictionary lookup. More on Lists The list data type has some more methods. ''' Initialize a dictionary with n key-value pairs. Data Structures This chapter describes some things you’ve learned about already in more detail, and adds some new things as well. Here’s a simple code snippet using this approach: def init_dict_1(n): Scroll down to see the winning method that is both easy and maximally efficient! □ Method 1: Basic For LoopĪ simple and straightforward-but not super concise-way to create and initialize a dictionary of size n is to use a simple for loop to fill up an initially empty dictionary by using dictionary assignments such as d = None in the loop body. Each key is separated from its value by a colon (:), the items are separated by commas, and the whole thing is enclosed in curly braces. Interestingly, the winner Method 4 is 38% faster than the slowest Method 5 and 14% faster than the next fastest. Next, you’ll learn the five main ways to solve this and compare their performance at the end of this article. How to initialize a Python dictionary of size n that is fast, easy, and efficient? ⚔️ Programming Challenge: Given an integer n that could be very high (e.g., n=1000000).
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