


Introduction to Python functions: functions and usage examples of the len function
Python function introduction: functions and usage examples of the len function
In Python programming, len() is a commonly used built-in function, which is used to return the incoming The length or number of elements of the object. This function can be used for different types of data structures such as strings, lists, tuples, dictionaries, and sets. The len() function is very simple and easy to use. This article will introduce the specific functions and usage examples of the len() function, and provide corresponding code.
Function of len() function:
The main function of len() function is to return the length or number of elements of the incoming object. The specific usage is as follows:
len(object)
Among them, object is a required parameter, which can be objects of different data types such as strings, lists, tuples, dictionaries, and sets.
Usage Example 1: String
A string is a sequence of characters, and the number of characters in the string can be obtained through the len() function. The following is a sample code:
str = "Hello, World!" print(len(str))
The output result is: 13
Usage Example 2: List
The list is one of the commonly used data structures in Python, and the len() function can calculate the list The number of elements in . The following is a sample code:
list = [1, 2, 3, 4, 5] print(len(list))
The output result is: 5
Usage Example 3: Tuple
The tuple is an immutable data structure, and you can also use the len() function to count the number of elements in a tuple. The following is a sample code:
tuple = (1, 2, 3, 4, 5) print(len(tuple))
The output result is: 5
Usage Example 4: Dictionary
The dictionary is a key-value pair data structure in Python, the len() function You can count the number of keys in a dictionary. The following is a sample code:
dict = {"name": "Tom", "age": 25, "gender": "male"} print(len(dict))
The output result is: 3
Usage Example 5: Set
A set is an unordered, non-repeating element data structure in Python, len () function can count the number of elements in the set. The following is a sample code:
set = {1, 2, 3, 4, 5} print(len(set))
The output result is: 5
Summary:
Through the above sample code, we can see the use of the len() function in different data types methods and return results. The len() function is very flexible and convenient, and can help us quickly obtain the number or length of elements in various data structures. In actual programming, the len() function is often used in loops, conditional judgments and other scenarios to help us perform corresponding operations and processing.
It should be noted that the len() function can only calculate the length of iterable objects. For basic data types such as integers and floating point numbers, using the len() function will report an error. So when using the len() function, you need to ensure that the object passed in is iterable. In addition, for dictionaries, the len() function returns the number of key-value pairs in the dictionary, not the length of the dictionary.
By understanding and mastering the len() function, we can better write Python programs and implement more complex functions and logic. I hope the introduction in this article will be helpful to readers in the process of learning Python programming.
The above is the detailed content of Introduction to Python functions: functions and usage examples of the len function. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



PHP and Python have their own advantages and disadvantages, and the choice depends on project needs and personal preferences. 1.PHP is suitable for rapid development and maintenance of large-scale web applications. 2. Python dominates the field of data science and machine learning.

Efficient training of PyTorch models on CentOS systems requires steps, and this article will provide detailed guides. 1. Environment preparation: Python and dependency installation: CentOS system usually preinstalls Python, but the version may be older. It is recommended to use yum or dnf to install Python 3 and upgrade pip: sudoyumupdatepython3 (or sudodnfupdatepython3), pip3install--upgradepip. CUDA and cuDNN (GPU acceleration): If you use NVIDIAGPU, you need to install CUDATool

Enable PyTorch GPU acceleration on CentOS system requires the installation of CUDA, cuDNN and GPU versions of PyTorch. The following steps will guide you through the process: CUDA and cuDNN installation determine CUDA version compatibility: Use the nvidia-smi command to view the CUDA version supported by your NVIDIA graphics card. For example, your MX450 graphics card may support CUDA11.1 or higher. Download and install CUDAToolkit: Visit the official website of NVIDIACUDAToolkit and download and install the corresponding version according to the highest CUDA version supported by your graphics card. Install cuDNN library:

Docker uses Linux kernel features to provide an efficient and isolated application running environment. Its working principle is as follows: 1. The mirror is used as a read-only template, which contains everything you need to run the application; 2. The Union File System (UnionFS) stacks multiple file systems, only storing the differences, saving space and speeding up; 3. The daemon manages the mirrors and containers, and the client uses them for interaction; 4. Namespaces and cgroups implement container isolation and resource limitations; 5. Multiple network modes support container interconnection. Only by understanding these core concepts can you better utilize Docker.

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.

When selecting a PyTorch version under CentOS, the following key factors need to be considered: 1. CUDA version compatibility GPU support: If you have NVIDIA GPU and want to utilize GPU acceleration, you need to choose PyTorch that supports the corresponding CUDA version. You can view the CUDA version supported by running the nvidia-smi command. CPU version: If you don't have a GPU or don't want to use a GPU, you can choose a CPU version of PyTorch. 2. Python version PyTorch

PyTorch distributed training on CentOS system requires the following steps: PyTorch installation: The premise is that Python and pip are installed in CentOS system. Depending on your CUDA version, get the appropriate installation command from the PyTorch official website. For CPU-only training, you can use the following command: pipinstalltorchtorchvisiontorchaudio If you need GPU support, make sure that the corresponding version of CUDA and cuDNN are installed and use the corresponding PyTorch version for installation. Distributed environment configuration: Distributed training usually requires multiple machines or single-machine multiple GPUs. Place

CentOS Installing Nginx requires following the following steps: Installing dependencies such as development tools, pcre-devel, and openssl-devel. Download the Nginx source code package, unzip it and compile and install it, and specify the installation path as /usr/local/nginx. Create Nginx users and user groups and set permissions. Modify the configuration file nginx.conf, and configure the listening port and domain name/IP address. Start the Nginx service. Common errors need to be paid attention to, such as dependency issues, port conflicts, and configuration file errors. Performance optimization needs to be adjusted according to the specific situation, such as turning on cache and adjusting the number of worker processes.
