Programming Effectively in Python

Python 是一种易于学习、功能强大的编程语言。如果您是一名开发人员，希望使用这种简单但功能强大的 Python 编程语言建立强大的编程基础，那么本课程适合您。

此学习路径是您探索围棋领域可能性的分步指南。通过本课程，您将从理解重构的原则开始，并通过识别需要重构的代码来发现机会。此外，您还将了解如何通过简单的步骤从程序中删除 Python 反模式。接下来，您将学习如何通过循环、数据结构、面向对象编程、函数等的快速提示、技巧和技术来提高代码的速度和性能。最后，在这一切之后，是时候对 Python 应用程序开发进行故障排除了 快速检测哪些代码行导致问题，并快速修复它们，而无需浏览数十万页。

内容和概述

该培训计划包括 3 门完整的课程，经过精心挑选，可为您提供最全面的培训。

第一门课程重构 Python 代码首先教您使用技术和方法解决 Python 反模式，以改进现有代码的设计。通过理解重构原理来解决错误，并通过识别需要重构的代码来学习发现机会。我们还将向您展示如何构建测试驱动的流程以使重构更容易。本课程将向您展示如何通过简单的步骤从程序中删除 Python 反模式。我们涵盖了重构和改进草率 Python 代码的特定技术。如果您想拥有一个有很多问题的遗留 Python 代码库，请参加本课程。应用现实世界的重构技术，将您的代码变成干净、高效且可维护的项目。

第二门课程 Python 提示、技巧和技术将带您从 Python 局外人转变为内部人员。您将受益于 Python 文档、PEP 和在线开发人员社区的见解，以学习解决常见编程模式的终极 Pythonic 方法。本课程涵盖循环、数据结构、面向对象编程、函数等方面的提示、技巧和技术，帮助您处理字典的有序集合和键值存储。您将能够提高代码的速度和性能，同时使其更易于调试。开始为您的应用程序编写更简洁的代码，并在短短 3 小时内学会更好地组织它。没有其他课程可以改变 Python 代码的每一个角落。立即参加本课程，成为一夜之间成为 Python 摇滚明星的开发人员。

第三门课程“Python 应用程序开发故障排除”将带您完成应用程序可能遇到的性能问题的结构化旅程，并介绍这些问题的直觉和解决方案。您将完成工作，无需冗长地了解 Python 的实现方式或计算理论。快速检测哪些代码行导致问题，并快速修复它们，而无需浏览 300 页不必要的细节。

MP4 | Video: h264, 1280×720 | Audio: AAC, 48000 Hz
Language: English | Size: 2.68 GB | Duration: 8h 15m

What you’ll learn
Practice refactoring methods and get to grips with real-world scenarios
Refactor classes and objects by making them easier to understand, maintain, and more efficient
Implementing pattern-based refactoring
Make major progress by using third-party refactoring tools to speed up your refactoring work
Learn to use dictionaries in a smarter way to keep track of your application’s state.
Save time writing custom subclasses by learning new data structures built right into Python.
Evolve into a seasoned Python developer with top Pythonic tips
Locate root causes by benchmarking and profiling your application
Make your apps run faster with parallel programming
Organize your code better using Object Oriented Programming

Requirements
A strong understanding of Python Programming is assumed.
Description
Python is an easy to learn, powerful programming language. If you’re a developer who wishes to build a strong programming foundation with this simple yet powerful programming language Python, then this course is for you.

This learning path is your step-by-step guide to exploring the possibilities in the field of Go. With this course, you’ll start with understanding the principles of refactoring, & spot opportunities by identifying code that requires refactoring. Also, you will be shown how to remove Python anti-patterns from your programs in simple steps. Next, you will learn how you can increase the speed & performance of your code with quick tips, tricks, and techniques for loops, data structures, object-oriented programming, functions, and more. Finally, after all this, its time to troubleshoot Python Application Development Quickly detect which lines of code are causing problems, and fix them quickly without going through lakhs of pages.

Contents and Overview

This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Refactoring Python Code starts with teaching you to resolve Python anti-patterns with techniques and methods to improve the design of your existing code. Tackle bugs by understanding the principles of refactoring, and learn to spot opportunities by identifying code that requires refactoring. We will also show you how to build test-driven processes to make refactoring easier. This course will show you how to remove Python anti-patterns from your programs in simple steps. We cover specific techniques for refactoring and improving the sloppy Python code. Take this course if you want to have a legacy Python code base with a lot of issues. Apply real-world refactoring techniques, and turn your code into clean, efficient, and maintainable projects.

The second course, Python Tips, Tricks, and Techniques will take you from a Python outsider to an insider. You will benefit from insights from the Python documentation, PEPs, and online developer communities to learn the ultimate Pythonic ways to tackle common programming patterns. This course covers tips, tricks, and techniques for loops, data structures, object-oriented programming, functions, and more, helping you work on ordered collections and key-value stores for dictionaries. You will be able to increase the speed and performance of your code while making it easier to debug. Start writing cleaner code for your applications and learn to organize it better in just 3 hours. No other course can transform every corner of your Python code. Take this course NOW and become an overnight Python rockstar developer.

The third course, Troubleshooting Python Application Development takes you through a structured journey of performance problems that your application is likely to encounter, and presents both the intuition and the solution to these issues. You’ll get things done, without a lengthy detour into how Python is implemented or computational theory. Quickly detect which lines of code are causing problems, and fix them quickly without going through 300 pages of unnecessary detail.

About the Authors:

James Cross is a Big Data Engineer and certified AWS Solutions Architect with a passion for data-driven applications. He’s spent the last 3-5 years helping his clients to design and implement huge scale streaming Big Data platforms, Cloud-based analytics stacks, and serverless architectures. He started his professional career in Investment Banking, working with well-established technologies such as Java and SQL Server, before moving into the big data space. Since then he’s worked with a huge range of big data tools including most of the Hadoop eco-system, Spark and many No-SQL technologies such as Cassandra, MongoDB, Redis, and DynamoDB. More recently his focus has been on Cloud technologies and how they can be applied to data analytics, culminating in his work at Scout Solutions as CTO, and more recently with Mckinsey. James is an AWS-certified solutions architect with several years’ experience designing and implementing solutions on this cloud platform. As CTO of Scout Solutions Ltd, he built a fully serverless set of APIs and an analytics stack based around Lambda and Redshift. He is interested in almost anything that has to do with technology. He has worked with everything from WordPress to Hadoop, from C++ to Java, and from Oracle to DynamoDB. If it’s new and solves a problem in an innovative way he’s keen to give it a go!

Colibri Ltd is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and cloud computing. Over the past few years, they have worked with some of the world’s largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world’s most popular soft drinks companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. After taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feedback into how our AI generates content. Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy where he experienced firsthand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO’s Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye. In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which to learn deeply about reinforcement learning and supervised learning topics in a commercial setting. Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean’s List, and received awards such as the Deutsche Bank Artificial Intelligence prize.

Who this course is for:
This course is targeted at Python developers, software architects and senior software engineers, who use Python for their everyday work and build their applications and projects using Python ● .