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他老爸想让更多小孩学会编程,去用电脑实现自己有趣的想法。本来打算只让这个机器跑Python(是只跑Python,像学习机一样的东西。并没有想过在上面弄一个完整的linux)。但是后来动真格的时候发现大材小用了于是就直接跑linux了,当然Python是不会落下的。可以看看记者对他爸做的访谈。
Python的优点大家都晓得,就不用我说了... 换个角度讲, 当C#在微软平台上成为主流开发语言的时候, python已经渐渐的成为了linux应用程序的主流开发语言之一了. 原因很简单, perl在淡出, ruby未发力, shell不够用, php不合适, java不解释.
记得Redhat 7的字符界面安装程序就是python写的, 那几乎是我第一次听说python的年代了. 因为功能强大,使用简单,修改调整方便
不用把时间精力浪费在和业务逻辑无关的东西上
昨天我老婆看了RPi.GPIO的文档,一个小时数十行代码就可以实现树莓派小车通过红外探测器循迹运行了。这是其他语言所做不到或者难做到的
视频戳这里:树莓派红外循迹小车 Python is the Basic of this decade. Python 的优越性不想在介绍了。
Python是小孩子都能用的非常棒的编程语言。
楼上说得好,人生苦短,我用Python 不仅仅是python啊,树莓派其实是一个小型的linux系统,功能非常强大的,除了python外,C、C++、Java、perl,php、shell等编程语言都能用,连go语言都可以。 Python的语法易于掌握,并且包含了从普通操作到科学运算的所有功能。
重要的是不需要配置任何环境就可以开发(Linux系统自备解释器 + vi编辑)。 努力学习python中 人生苦短,我用Py Raspberry Pi Documentation
PYTHON
Python is a wonderful and powerful programming language that's easy to use (easy to read and write) and with Raspberry Pi lets you connect your project to the real world.
Python syntax is very clean, with an emphasis on readability and uses standard English keywords. Start by opening IDLE from the desktop.

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.


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