As a flexible and powerful programming language, Python has conquered the hearts of programmers, data experts and software craftsmen around the world. Python's massive adoption stems from its rich set of native commands that simplify complex processes, shorten development time, and improve script readability. In this article, we will take an in-depth look at ten key Python native commands that every programmer needs to master for a seamless and efficient coding journey.
len() command is a simple yet indispensable mechanism for determining the size (i.e., the count of components) of a specified iterable object such as a list, tuple, or string.
expression = "Python" size = len(expression) print(size)
6
sum() command provides the sum of all components in an iterable object. Use this command to avoid writing a loop to calculate the sum of a list or tuple.
digits = [1, 2, 3, 4, 5] aggregate = sum(digits) print(aggregate)
15
The map() command implements a specific function on all components in an iterable object (e.g., list, tuple) and generates an iterator. This command is useful when you need to use a specific function to manipulate each component in the collection.
def square(y): return y * y digits = [1, 2, 3, 4, 5] squared_digits = map(square, digits) print(list(squared_digits))
[1, 4, 9, 16, 25]
The filter() command separates components from an iterable object based on predetermined conditions. It accepts two parameters: a function used to define the filter conditions and an iterable object used to filter. The result is an iterator containing elements that satisfy the condition.
def is_even(y): return y % 2 == 0 digits = [1, 2, 3, 4, 5] even_digits = filter(is_even, digits) print(list(even_digits))
[2, 4]
The zip() command combines two or more iterable objects together to generate an iterator of tuples, in which the first elements of each iterable object are mixed together, and then the Subsequent elements are matched together, and so on. This command is particularly useful when you need to combine data from different sources.
identities = ['Alice', 'Bob', 'Charlie'] years = [25, 30, 35] merged_data = zip(identities, years) print(list(merged_data))
[('Alice', 25), ('Bob', 30), ('Charlie', 35)]
The sorted() command generates a new sorted list from the specified iterable object. By default, it sorts components in ascending order. The sorting method can be adjusted by using the optional "key" and "reverse" parameters.
digits = [5, 2, 1, 4, 3] sorted_digits = sorted(digits) print(sorted_digits)
[1, 2, 3, 4, 5]
any() command returns True if at least one component of the iterable object is true, otherwise it returns False. In contrast, the all() command returns True if all elements of the iterable object are true, otherwise it returns False. These commands are useful when you need to evaluate multiple conditions in a collection.
list1 = [True, False, True] list2 = [True, True, True] print(any(list1)) print(all(list1)) print(all(list2))
True False True
The enumerate() command is used to include a counter in an iterable object and return an enumeration object. It accepts two parameters: an iterable object and an optional 'start' value as a counter. This command becomes particularly valuable when the index and the value of the element are needed in a loop.
fruit_types = ['apple', 'banana', 'cherry'] for count, value in enumerate(fruit_types, start=1): print(f"{count}. {value}")
1. apple 2. banana 3. cherry
The range() command generates a range of numbers, often used in a loop to repeat a specific number. One, two or three parameters can be recognized, namely "start" (optional), "stop" and "step" (optional). The default values of start and step are set to 0 and 1 respectively.
for i in range(5): print(i) for i in range(1, 5, 2): print(i)
0 1 2 3 4 1 3
The isinstance() command is used to confirm whether the given question is an instance or subclass of the specified course. Returns True if the object is an instance or subclass of this class, False otherwise. This command is useful when you need to validate input data types or handle multiple types of inputs within a function.
numeral = 5 outcome = isinstance(numeral, int) print(outcome) expression = 'Python' outcome = isinstance(expression, int) print(outcome)
True False
Python’s native commands are essential tools for programmers, enabling them to write concise, efficient and readable scripts. The ten commands introduced in this article are not an exhaustive list, but they represent a solid foundation upon which any programmer can build. By mastering these commands and exploring other native Python tools, you'll become proficient in solving a variety of coding challenges.
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