By Roberto Ulloa
Mobiles and pills have introduced with them a dramatic switch within the application of purposes. Compatibility has develop into crucial, and this has elevated the type of interplay that clients anticipate: gestures, multi-touches, animations, and magic pens. Kivy is an open resource Python resolution that covers those marketplace wishes with an easy-to-learn and quick improvement technique. Kivy is starting to be quickly and gaining consciousness as a substitute to the demonstrated constructing platforms.
Kivy: Interactive functions in Python quick introduces you to the Kivy improvement method. you are going to study a few examples of ways to take advantage of some of the Kivy elements, in addition to know how to combine and mix them into large tasks. This publication serves as a reference advisor and is equipped in this sort of manner that after accomplished, you might have already accomplished your first undertaking.
Read or Download Kivy: Interactive Applications in Python PDF
Best python books
Tools used for penetration trying out are usually bought or downloaded from the net. every one software is predicated on a programming language resembling Perl, Python, or Ruby. If a penetration tester desires to expand, increase, or swap the performance of a device to accomplish a try in a different way than the default configuration, the tester needs to understand the fundamentals of coding for the similar programming language. Coding for Penetration Testers offers the reader with an knowing of the scripting languages which are customary whilst constructing instruments for penetration trying out. It additionally publications the reader via particular examples of customized device improvement and the occasions the place such instruments will be used. whereas constructing a greater figuring out of every language, the reader is guided via real-world eventualities and gear improvement that may be integrated right into a tester's toolkit.
* Discusses using quite a few scripting languages in penetration testing
* offers step by step directions on how one can construct custom-made penetration trying out instruments utilizing Perl, Ruby, Python, and different languages
* offers a primer on scripting together with, yet no longer constrained to, internet scripting, scanner scripting, and exploitation scripting
Mobiles and drugs have introduced with them a dramatic swap within the software of purposes. Compatibility has develop into crucial, and this has elevated the type of interplay that clients count on: gestures, multi-touches, animations, and magic pens. Kivy is an open resource Python resolution that covers those industry wishes with an easy-to-learn and swift improvement process.
Python is readily changing into the go-to language for analysts and knowledge scientists as a result of its simplicity and suppleness, and in the Python facts house, scikit-learn is the unequivocal selection for computing device studying. Its constant API and plethora of good points aid remedy any computer studying challenge it comes throughout.
Observe potent studying algorithms to real-world difficulties utilizing scikit-learn
About This booklet
• layout and troubleshoot computer studying platforms for universal initiatives together with regression, category, and clustering
• Acquaint your self with renowned computer studying algorithms, together with choice bushes, logistic regression, and help vector machines
• a pragmatic example-based advisor that can assist you achieve services in enforcing and comparing laptop studying structures utilizing scikit-learn
[ Who This e-book Is For
If you're a software program developer who desires to learn the way computer studying types paintings and the way to use them successfully, this publication is for you. Familiarity with computer studying basics and Python may be valuable, yet isn't really crucial.
What you'll examine
• evaluation basic options together with supervised and unsupervised reviews, universal projects, and function metrics
• expect the values of constant variables utilizing linear regression
• Create representations of files and photographs that may be utilized in laptop studying versions
• Categorize records and textual content messages utilizing logistic regression and help vector machines
• Classify photos by means of their matters
• become aware of hidden buildings in facts utilizing clustering and visualize complicated information utilizing decomposition
• assessment the functionality of laptop studying structures in universal projects
• Diagnose and redress issues of versions because of bias and variance
This ebook examines desktop studying versions together with logistic regression, determination bushes, and aid vector machines, and applies them to universal difficulties reminiscent of categorizing records and classifying photographs. It starts with the basics of computer studying, introducing you to the supervised-unsupervised spectrum, the makes use of of teaching and try facts, and comparing types. you'll tips on how to use generalized linear versions in regression difficulties, in addition to resolve issues of textual content and express features.
You could be conversant in using logistic regression, regularization, and some of the loss capabilities which are utilized by generalized linear versions. The ebook also will stroll you thru an instance venture that activates you to label the main doubtful education examples. additionally, you will use an unmanaged Hidden Markov version to foretell inventory prices.
By the tip of the publication, you can be knowledgeable in scikit-learn and may be good versed in laptop studying
- Understanding Network Hacks: Attack and Defense with Python
- CherryPy Essentials: Rapid Python Web Application Development
- Programmation Python
- Pi : a source book
Extra resources for Kivy: Interactive Applications in Python
Therefore, the context is restored correctly on the PushMatrix. before because they are added after the existents instructions. In other words, if we were to add them in the canvas, the StickMan would be drawn before the translation and scaling. kv files, so we are not presenting them again. The context and vertex instructions are easy to understand. However, we must be very careful with the order of execution, and make sure to leave the coordinate space context in its original state after executing the desired vertex instructions.
Let's proceed with the shape B (Pac-Man-like shape) as shown in the following code: 20. 21. 22. 23. 24. Ellipse: angle_start: 120 angle_end: 420 pos: 110, 110 size: 80,80 The Ellipse works very similar to the Rectangle but we have three new properties: angle_start, angle_end, and segments. The first two properties specify the initial and final angle of the ellipse. The angle 0° is north (or 12 o'clock) and they add up in the clock direction. That explains the angle 120° (90° + 30°) in line 21. It is not yet clear why the angle_end property is 420° (360° + (90°-30°)) and not just 60°.
In the next section, we will teach you how to embed layouts, and we will offer a more comprehensive example of them. Embedding layouts The layouts studied in the previous section are subclasses of Widget. We have already been embedding widgets inside widgets since the beginning of this chapter and, of course, it won't matter if the widgets we are embedding are layouts as well. The following Python code is the base of a comprehensive example about embedding Layouts: 92. py 93. app import App 94.
Kivy: Interactive Applications in Python by Roberto Ulloa