Learn Java the Easy Way : A Hands-On Introduction to Programming Kindle Edition by Bryson Payne

Java is the world’s most popular programming language, but it’s known for having a steep learning curve. Learn Java the Easy Way takes the chore out of learning Java with hands-on projects that will get you building real, functioning apps right away.

You’ll start by familiarizing yourself with JShell, Java’s interactive command line shell that allows programmers to run single lines of code and get immediate feedback. Then, you’ll create a guessing game, a secret message encoder, and a multitouch bubble-drawing app for both desktop and mobile devices using Eclipse, an industry-standard IDE, and Android Studio, the development environment for making Android apps.

As you build these apps, you’ll learn how to:
-Perform calculations, manipulate text strings, and generate random colors
-Use conditions, loops, and methods to make your programs responsive and concise
-Create functions to reuse code and save time
-Build graphical user interface (GUI) elements, including buttons, menus, pop-ups, and sliders 
-Take advantage of Eclipse and Android Studio features to debug your code and find, fix, and prevent common mistakes

If you’ve been thinking about learning Java, Learn Java the Easy Way will bring you up to speed in no time.

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Classic Computer Science Problems in Python

Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means.

Classic Computer Science Problems in Python deepens your Python language skills by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems

Key Features

·   Breadth-first and depth-first search algorithms

·   Constraints satisfaction problems

·   Common techniques for graphs

·   Adversarial Search

·   Neural networks and genetic algorithms

·   Written for data engineers and scientists with experience using Python.

For readers comfortable with the basics of Python

About the technology

Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and you’ll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges you’ll face as you grow your skill as a programmer.

David Kopec teaches at Champlain College in Burlington, VT and is the author of Manning’s Classic Computer Science Problemsin Swift.

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Classic Computer Science Problems in Python 

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Python for the Busy Java Developer: The Language, Syntax, and Ecosystem Kindle Edition by Deepak Sarda (Author)

Are you a seasoned Java developer who wishes to learn Python? Perhaps you’ve just joined a project where a chunk of system integration code is written in Python. Or maybe you need to implement a report generation module in the next sprint and your colleague mentioned that Python would be the perfect tool for the job. In any case, if you are in a situation where you have to pick up the Python programming language overnight, this book is just for you! 

Hit the ground running and gain a fast-paced overview of what the Python language is all about, the syntax that it uses and the ecosystem of libraries and tools that surround the language. This concise book doesn’t spend time on details from an introductory programming course or document every single Python feature. Instead, Python for the Busy Java Developer is designed for experienced Java developers to obtain sufficient familiarity with the language and dive into coding, quickly.

What You'll Learn

• Discover the fundamentals of the core Python language and how they compare to Java
• Understand Python syntax and the differences between Python 2.x and 3.x
• Explore the Python ecosystem, its standard libraries, and how to implement them

Who This Book Is For

Working programmers who are comfortable with Java or another object-oriented programming language such as C#

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Python for the Busy Java Developer: The Language, Syntax, and Ecosystem 

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Website Scraping with Python: Using BeautifulSoup and Scrapy Kindle Edition by Gábor László Hajba

Closely examine website scraping and data processing: the technique of extracting data from websites in a format suitable for further analysis. You'll review which tools to use, and compare their features and efficiency. Focusing on BeautifulSoup4 and Scrapy, this concise, focused book highlights common problems and suggests solutions that readers can implement on their own.

Website Scraping with Python starts by introducing and installing the scraping tools and explaining the features of the full application that readers will build throughout the book. You'll see how to use BeautifulSoup4 and Scrapy individually or together to achieve the desired results. Because many sites use JavaScript, you'll also employ Selenium with a browser emulator to render these sites and make them ready for scraping.

By the end of this book, you'll have a complete scraping application to use and rewrite to suit your needs. As a bonus, the author shows you options of how to deploy your spiders into the Cloud to leverage your computer from long-running scraping tasks.

What You'll Learn

• Install and implement scraping tools individually and together
• Run spiders to crawl websites for data from the cloud
• Work with emulators and drivers to extract data from scripted sites

Who This Book Is For

Readers with some previous Python and software development experience, and an interest in website scraping.

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Website Scraping with Python: Using BeautifulSoup and Scrapy Kindle Edition by Gábor László Hajba 

 

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Deep Learning with Python Paperback – Import, 30 Nov 2017 by Francois Chollet

Deep learning is applicable to a widening range of artificial
intelligence problems, such as image classification, speech recognition,
text classification, question answering, text-to-speech, and optical
character recognition.

Deep Learning with Python is structured around a series of practical
code examples that illustrate each new concept introduced and
demonstrate best practices. By the time you reach the end of this book,
you will have become a Keras expert and will be able to apply deep
learning in your own projects.

KEY FEATURES

• Practical code examples
• In-depth introduction to Keras
• Teaches the difference between Deep Learning and AI

ABOUT THE TECHNOLOGY
Deep learning is the technology behind photo tagging systems at
Facebook and Google, self-driving cars, speech recognition systems on
your smartphone, and much more.

AUTHOR BIO
Francois Chollet is the author of Keras, one of the most widely used
libraries for deep learning in Python. He has been working with deep neural
networks since 2012. Francois is currently doing deep learning research at
Google. He blogs about deep learning at blog.keras.io.

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Deep Learning with Python Paperback – Import, 30 Nov 2017 by Francois Chollet  

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Learning PHP, MySQL & JavaScript, 5th Edition With jQuery, CSS & HTML5 (Learning PHP, MYSQL, Javascript, CSS & HTML5)

Build interactive, data-driven websites with the potent combination of open-source technologies and web standards, even if you have only basic HTML knowledge. With this popular hands-on guide, you'll tackle dynamic web programming with the help of today's core technologies: PHP, MySQL, JavaScript, jQuery, CSS and HTML5.

Explore each technology separately, learn how to use them together and pick up valuable web programming practices along the way. At the end of the book, you'll put everything together to build a fully functional social networking site, using XAMPP or any development stack you choose.

• Learn PHP in-depth, along with the basics of object-oriented programming
• Explore MySQL, from database structure to complex queries
• Use the MySQLi Extension, PHP's improved MySQL interface
• Create dynamic PHP web pages that tailor themselves to the user
• Manage cookies and sessions and maintain a high level of security
• Master the JavaScript language-and enhance it with jQuery
• Use Ajax calls for background browser/server communication
• Acquire CSS2 and CSS3 skills for professionally styling your web pages
• Implement all of the new HTML5 features, including geolocation, audio, video and the canvas

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Learning PHP, MySQL & JavaScript with j Query, CSS & HTML5 Paperback – 2015 by Robin Nixon  

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Java XML and JSON, 2nd Edition Document Processing for Java SE

Use this guide to master the XML metalanguage and JSON data format along with significant Java APIs for parsing and creating XML and JSON documents from the Java language. New in this edition is coverage of Jackson (a JSON processor for Java) and Oracle’s own Java API for JSON processing (JSON-P), which is a JSON processing API for Java EE that also can be used with Java SE. This new edition of Java XML and JSON also expands coverage of DOM and XSLT to include additional API content and useful examples.

All examples in this book have been tested under Java 11. In some cases, source code has been simplified to use Java 11’s var language feature. The first six chapters focus on XML along with the SAX, DOM, StAX, XPath, and XSLT APIs. The remaining six chapters focus on JSON along with the mJson, GSON, JsonPath, Jackson, and JSON-P APIs. Each chapter ends with select exercises designed to challenge your grasp of the chapter's content. An appendix provides the answers to these exercises.

What You'll Learn

• Master the XML language
• Create, validate, parse, and transform XML documents
• Apply Java’s SAX, DOM, StAX, XPath, and XSLT APIs
• Master the JSON format for serializing and transmitting data
• Code against third-party APIs such as Jackson, mJson, Gson, JsonPath
• Master Oracle’s JSON-P API in a Java SE context

Who This Book Is For

Intermediate and advanced Java programmers who are developing applications that must access data stored in XML or JSON documents. The book also targets developers wanting to understand the XML language and JSON data format.

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Java XML and JSON: Document Processing for Java SE Paperback – Import, 11 Jan 2019 by Jeff Friesen  

 

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Working with Dictionary in Python

Python Dictionaries

A dictionary is a set of unordered key, value pairs. In a dictionary, the keys must be unique and they are stored in an unordered manner.
In this blog you will learn the basics of how to use the Python dictionary.

By the end of the tutorial you will be able to - Create Dictionaries - Get values in a Dictionary - Add and delete elements in a Dictionary - To and For Loops in a Dictionary

Creating a Dictionary

Let’s try to build a profile of three people using dictionaries. To do that you separate the key-value pairs by a colon(“:”). The keys would need to be of an immutable type, i.e., data-types for which the keys cannot be changed at runtime such as int, string, tuple, etc. The values can be of any type. Individual pairs will be separated by a comma(“,”) and the whole thing will be enclosed in curly braces({...}).

For example, you can have the fields “city”, “name,” and “food” for keys in a dictionary and assign the key, value pairs to the dictionary variable person1_information.

>>> person_information = {'city': 'San Francisco', 'name': 'Sam', "food": "shrimps"}
>>> type(person1_information)

>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam', 'food': 'shrimps'}

Get the values in a Dictionary

To get the values of a dictionary from the keys, you can directly reference the keys. To do this, you enclose the key in brackets [...] after writing the variable name of the dictionary.
So, in the following example, a dictionary is initialized with keys “city”, “name,” and “food” and you can retrieve the value corresponding to the key “city.”

>>> create a dictionary person1_information
>>> person1_information = {'city': 'San Francisco', 'name': 'Sam', "food":"shrimps"}
>>> print the dictionary
>>> print(person1_information["city"])
San Francisco

You can also use the get method to retrieve the values in a dict. The only difference is that in the get method, you can set a default value. In direct referencing, if the key is not present, the interpreter throws KeyError.

>>> # create a small dictionary
>>> alphabets = {1: ‘a’}
>>> # get the value with key 1
>>> print(alphabets.get(1))
'a'
>>> # get the value with key 2. Pass “default” as default. Since key 2 does not exist, you get “default” as the return value.
>>> print(alphabets.get(2, "default"))
'default'
>>> # get the value with key 2 through direct referencing
>>> print(alphabets[2])
Traceback (most recent call last):
File "stdin", line 1, in module KeyError: 2

Looping over dictionary

Say, you got a dictionary, and you want to print the keys and values in it. Note that the key-words for and in are used which are used when you try to loop over something. To learn more about looping please look into tutorial on looping.

>>> person1_information = {'city': 'San Francisco', 'name': 'Sam', "food": "shrimps"}
>>> for k, v in person1_information.items():
... print("key is: %s" % k)
... print("value is: %s" % v)
... print("###########################")
... key is: food
value is: shrimps
###########################
key is: city
value is: San Francisco
###########################
key is: name
value is: Sam
###########################

Add elements to a dictionary

You can add elements by updating the dictionary with a new key and then assigning the value to a new key.

>>> # initialize an empty dictionary
>>> person1_information = {}
>>> # add the key, value information with key “city”
>>> person1_information["city"] = "San Francisco"
>>> # print the present person1_information
>>> print(person1_information)
{'city': 'San Francisco'}
>>> # add another key, value information with key “name”
>>> person1_information["name"] = "Sam"
>>> # print the present dictionary
>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam'}
>>> # add another key, value information with key “food”
>>> person1_information["food"] = "shrimps"
>>> # print the present dictionary
>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam', 'food': 'shrimps'}

Or you can combine two dictionaries to get a larger dictionary using the update method.

>>> # create a small dictionary
>>> person1_information = {'city': 'San Francisco'}
>>> # print it and check the present elements in the dictionary
>>> print(person1_information)
{'city': 'San Francisco'}
>>> # have a different dictionary
>>> remaining_information = {'name': 'Sam', "food": "shrimps"}
>>> # add the second dictionary remaining_information to personal1_information using the update method
>>> person1_information.update(remaining_information)
>>> # print the current dictionary
>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam', 'food': 'shrimps'}

Delete Elements in a Dicitionary

To delete a key, value pair in a dictionary, you can use the del method.

>>> # initialise a dictionary with the keys “city”, “name”, “food”
>>> person1_information = {'city': 'San Francisco', 'name': 'Sam', "food": "shrimps"}
>>> # delete the key, value pair with the key “food”
>>> del person1_information["food"]
>>> # print the present personal1_information. Note that the key, value pair “food”: “shrimps” is not there anymore.
>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam'}

A disadvantage is that it gives KeyError if you try to delete a nonexistent key.

>>> # initialise a dictionary with the keys “city”, “name”, “food”
>>> person1_information = {'city': 'San Francisco', 'name': 'Sam', "food": "shrimps"}
>>> # deleting a non existent key gives key error.
>>> del person1_information["non_existent_key"]
Traceback (most recent call last):
File "", line 1, in
KeyError: 'non_existent_key'

So, instead of the del statement you can use the pop method. This method takes in the key as the parameter. As a second argument, you can pass the default value if the key is not present.

>>> # initialise a dictionary with key, value pairs
>>> person1_information = {'city': 'San Francisco', 'name': 'Sam', "food": "shrimps"}
>>> # remove a key, value pair with key “food” and default value None
>>> print(person1_information.pop("food", None))
'Shrimps'
>>> # print the updated dictionary. Note that the key “food” is not present anymore
>>> print(person1_information)
{'city': 'San Francisco', 'name': 'Sam'}
>>> # try to delete a nonexistent key. This will return None as None is given as the default value.
>>> print(person1_information.pop("food", None))
None

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