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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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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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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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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 ava 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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Working with Lists in Python

Working with Lists in Python – A Complete Beginner’s Guide

If you learn only one data structure in Python, make it a list.

Why? Because almost everything you build in Python—apps, scripts, automation, data analysis—relies on lists.

Lists are:

• Easy to use

• Extremely powerful

• Used everywhere

Let’s master them step by step 👇

---

What is a List in Python?

A list is a collection of items stored in a single variable.

numbers = [1, 2, 3, 4, 5]

A list can store:

• Integers

• Strings

• Floats

• Even other lists

data = [10, "Python", 3.14, True]

---

Accessing List Elements

Each element has an index (starting from 0).

langs = ["Python", "Java", "C++"]
print(langs[0])   # Python
print(langs[2])   # C++

Negative Indexing

print(langs[-1])  # C++

---

Modifying List Values

Lists are mutable (you can change them).

langs[1] = "JavaScript"
print(langs)

Output:

['Python', 'JavaScript', 'C++']

---

Common List Operations

1. Adding Elements

lst = [1, 2]
lst.append(3)

lst.insert(0, 99)

---

2. Removing Elements

lst.remove(99)

lst.pop()

del lst[0]

---

3. Length of List

len(lst)

---

Looping Through a List

Basic Loop

for item in lst:
    print(item)

With Index

for i in range(len(lst)):
    print(i, lst[i])

---

Slicing Lists

Extract parts of a list:

nums = [10, 20, 30, 40, 50]
print(nums[1:4])

Output:

[20, 30, 40]

---

Useful List Methods

Method	Purpose
append()	Add at end
insert()	Add at index
remove()	Remove value
pop()	Remove last
sort()	Sort list
reverse()	Reverse
count()	Count value
index()	Find position

Example:

nums.sort()
nums.reverse()

---

List Comprehension (Power Feature)

One line instead of loops:

squares = [x*x for x in range(5)]
print(squares)

Output:

[0, 1, 4, 9, 16]

---

Nested Lists (2D Lists)

matrix = [
    [1, 2],
    [3, 4]
]

print(matrix[1][0])  # 3

Used in:

• Tables

• Matrices

• Game boards

---

Common Beginner Mistake

This does NOT modify the list:

arr = [1, 2, 3]
for i in arr:
    i = i * 10
print(arr)

Output:

[1, 2, 3]

Correct way:

for i in range(len(arr)):
    arr[i] *= 10

---

Why Lists Are So Important

Lists are used in:

• Web scraping

• Data science

• Machine learning

• Automation

• Game development

• APIs & JSON

If you know lists well, you already know 40% of Python.

---

Final Thoughts

Mastering lists means:

• Cleaner code

• Faster logic

• Better problem-solving

Before learning:

• NumPy

• Pandas

• Machine Learning

👉 First, become deadly with Python lists.

Because every advanced concept is built on top of them. 🚀

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Android Application Development For Dummies

The Android OS continues to rapidly expand offering app developers access to one of the largest platforms available, and this easy–to–follow guide walks you through the development process step by step. In this new edition of the bestselling Android Application Development For Dummies, Android programming experts Michael Burton and Donn Felker explain how to download the SDK, get Eclipse up and running, code Android applications, and share your finished products with the world.

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Android Application Development For Dummies by Michael Burton  

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Android Application Development For Dummies 

Featuring two sample programs, this book explores everything from the simple basics to advanced aspects of Android application development.

• Walks you through all the steps in developing applications for the Android platform, including the latest Android features like scrollable widgets, enhanced UI tools, social media integration, and new calendar and contact capabilities
• Starts off with downloading the SDK, then explains how to bring your applications to life and submit your work to the Android Market
• Includes real–world advice from expert programmers Donn Felker and Michael Burton, who break every aspect of the development process down into practical, digestible pieces

Whether you′re new to Android development or already on your way, Android Application Development For Dummies, 2nd Edition is the guide you need to dig into the app dev process!

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