Full Stack Python Guide to Deployments

By Matthew Makai

The total Stack Python advisor to Deployments

Learn every little thing you want to comprehend to installation Python internet purposes to a server. In each one bankruptcy, we'll practice a handbook deployment to completely comprehend what we're doing, then automate every one step with textile and Ansible.

Throughout the e-book we'll take an instance open resource Python net program via a whole deployment on a digital inner most server.

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Python 3 Object-Oriented Programming - Second Edition

By Dusty Phillips

Unleash the ability of Python three objects

About This Book

  • Stop writing scripts and begin architecting programs
  • Learn the newest Python syntax and libraries
  • A sensible, hands-on educational that teaches you all approximately summary layout styles and the way to enforce them in Python 3

Who This publication Is For

If you are new to object-oriented programming concepts, or when you have easy Python abilities and need to benefit extensive how and whilst to properly practice object-oriented programming in Python to layout software program, this can be the e-book for you.

What you are going to Learn

  • Implement items in Python by means of developing periods and defining methods
  • Separate comparable items right into a taxonomy of sessions and describe the homes and behaviors of these gadgets through the category interface
  • Extend type performance utilizing inheritance
  • Understand while to exploit object-oriented positive factors, and extra importantly whilst to not use them
  • Discover what layout styles are and why they're assorted in Python
  • Uncover the simplicity of unit checking out and why it is so vital in Python
  • Grasp universal concurrency innovations and pitfalls in Python 3
  • Exploit object-oriented programming in key Python applied sciences equivalent to Kivy and Django.
  • Object-oriented programming simultaneously with asyncio

In Detail

Python three is extra flexible and more uncomplicated to exploit than ever. It runs on all significant systems in an incredible array of use circumstances. Coding in Python minimizes improvement time and raises productiveness compared to different languages. fresh, maintainable code is simple to either learn and write utilizing Python's transparent, concise syntax.

Object-oriented programming is a well-liked layout paradigm during which info and behaviors are encapsulated in this kind of method that they are often manipulated jointly. Many smooth programming languages make the most of the robust techniques at the back of object-oriented programming and Python is not any exception.

Starting with an in depth research of object-oriented research and layout, you are going to use the Python programming language to obviously grab key thoughts from the object-oriented paradigm. This booklet absolutely explains periods, info encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on if you can use every one precept to enhance well-designed software.

You'll get an in-depth research of many universal object-oriented layout styles which are more desirable to Python's certain variety. This ebook won't simply educate Python syntax, yet also will construct your self assurance in the best way to program.

You also will how to create maintainable purposes by means of learning greater point layout styles. Following this, you are going to study the complexities of string and dossier manipulation, and the way Python distinguishes among binary and textual info. now not one, yet very strong automatic trying out platforms could be brought within the e-book. when you detect the enjoyment of unit trying out and simply how effortless it may be, you will research greater point libraries equivalent to database connectors and GUI toolkits and learn the way they uniquely follow object-oriented ideas. you are going to learn the way those rules will let you make higher use of key individuals of the Python eco-system equivalent to Django and Kivy.

This new version comprises the entire issues that made Python three Object-oriented Programming an quick Packt vintage. it is also filled with up to date content material to mirror fresh adjustments within the center Python library and covers smooth third-party programs that weren't on hand at the Python three platform while the booklet used to be first published.

Style and approach

Throughout the ebook you'll examine key object-oriented programming options established via entire case reports within the context of a bigger project.

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Instant Data Intensive Apps with pandas How-to

By Trent Hauck

Manipulate, visualize, and study your information with pandas with this booklet and ebook

Overview

  • Learn anything new right away! a brief, quick, concentrated consultant providing quick results
  • Follow easy recipes that may train universal initiatives while appearing info research with Pandas
  • Build an information product for exhibiting details over the web
  • Create visualizations of the information together with showing tables and line graphs

In Detail

Pandas is helping to relieve a surely advanced scenario in facts analytics libraries. Many incumbent languages should not approachable or are rather unproductive as a rule computing projects compared to Python. even though with Pandas it is easy to start operating with tabular datasets in a language that is more uncomplicated to benefit and use.

Instant facts extensive Apps with Pandas How-to begins with Pandas’ functionalities comparable to becoming a member of datasets, cleansing info, and different info munging initiatives. It speedy strikes onto construction a knowledge reporting device, which is composed of study in Pandas to figure out what’s correct and current that appropriate facts in an easy-to-consume manner.

Instant info in depth Apps with Pandas How-to begins with information manipulation and different useful initiatives for a primary knowing, and during successive recipes you are going to achieve a extra ecocnomic figuring out of Pandas.

Throughout this booklet the recipes are offered in a dependent manner. It begins with information transformation innovations, yet builds as much as extra complicated examples akin to appearing statistical research and integrating Pandas gadgets with net functions. the opposite recipes disguise visualization and computer studying, between different things.

Instant facts extensive Apps with Pandas How-to gets the reader up and working quick with Pandas and positioned the person capable of movement up the training curve faster.

What you'll examine from this book

  • Learn info manipulation in Pandas together with subsetting facts, facts transformation, and knowledge reshaping
  • Combine info units to get an idea of what the output with tabular information appears to be like like
  • Perform mixture information operations similar to counts and sums for exploratory analysis
  • Use simple computing device studying to spot inventory functionality similarities
  • Create visualizations of information together with showing tables and line graphs
  • Integrate different libraries with Pandas and perform an easy analysis
  • Create an online program to exhibit Pandas info in an internet page

Approach

Filled with sensible, step by step directions and transparent causes for crucial and precious initiatives. This booklet has a realistic process with step by step recipes to assist readers familiarize yourself with Pandas.

Who this publication is written for

Users of different information research instruments will locate price in seeing projects they usually come upon translated to Pandas and clients of Python will come upon an advent to a really amazing device in a syntax they inherently recognize. when it comes to basic abilities, it really is assumed that the reader knows simple information buildings reminiscent of arrays or lists dictionaries or hash map in addition to having a few figuring out of command line paintings. fitting Pandas isn't really lined, however the on-line documentation is easy. additionally, readers are inspired to take advantage of IPython to have interaction and test with the code.

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Python 2.6 Text Processing: Beginners Guide

With a easy wisdom of Python you've got the aptitude to adopt time-saving textual content processing. This booklet is a smart creation to many of the ideas, and teaches via functional examples and transparent reasons. review the best way to profit textual content processing with Python offers with crucial textual facts codecs you'll stumble upon learn how to use the preferred textual content processing libraries to be had for Python jam-packed with examples to lead you thru What you are going to research from this booklet understand the choices on hand for processing textual content in Python Parse JSON facts that's frequently used as an information supply mechanism on the web arrange a log-processing software through modules and applications to make it extra extensible practice conditional fits through look-ahead and look-behind assertions through the use of simple normal expressions approach XML and HTML files in quite a few methods according to the desires of your program enforce callback how you can practice SAX processing and stroll in-memory DOM constructions comprehend Unicode, personality encoding, internationalization, and localization Lay out a Mako template-based venture by utilizing strategies resembling template inheritance, extra tags, and customized filters set up and use the Mako templating process to create your personal Mako templates approach loads of e mail messages utilizing the Python normal library and index them with Nucular for quick looking out repair universal exceptions that happen whereas facing types of textual content encoding construct easy PDF output utilizing the ReportLab toolkit's high-level PLATYPUS framework Generate Microsoft Excel output utilizing the xlwt module Open and edit latest Open rfile documents to exploit them as template resources comprehend assisting features and sessions, corresponding to the Python IO procedure and packaging elements strategy This ebook is a part of the Beginner's consultant sequence. every one bankruptcy covers the stairs for varied initiatives to procedure info

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Python Pocket Reference (Pocket Reference (O'Reilly))

By Mark Lutz

Updated for either Python 3.4 and 2.7, this useful pocket advisor is the proper on-the-job quickly reference. You’ll locate concise, need-to-know info on Python varieties and statements, targeted procedure names, integrated features and exceptions, widespread ordinary library modules, and different in demand Python instruments. The convenient index enables you to pinpoint precisely what you need.

Written by way of Mark Lutz—widely famous because the world’s best Python trainer—Python Pocket Reference is a perfect spouse to O’Reilly’s vintage Python tutorials, studying Python and Programming Python, additionally written through Mark.

This 5th version covers:

  • Built-in item forms, together with numbers, lists, dictionaries, and more
  • Statements and syntax for developing and processing objects
  • Functions and modules for structuring and reusing code
  • Python’s object-oriented programming tools
  • Built-in features, exceptions, and attributes
  • Special operator overloading methods
  • Widely used regular library modules and extensions
  • Command-line innovations and improvement tools
  • Python idioms and hints
  • The Python SQL Database API

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NumPy Cookbook - Second Edition

By Ivan Idris

Over ninety attention-grabbing recipes to benefit and practice mathematical, clinical, and engineering Python computations with NumPy

About This Book

  • Perform high-performance calculations with fresh and effective NumPy code
  • Simplify huge info units by means of analysing them with statistical functions
  • A solution-based advisor full of enticing recipes to execute advanced linear algebra and mathematical computations

Who This ebook Is For

If you're a Python developer with a few event of engaged on medical, mathematical, and statistical functions and need to achieve knowledgeable figuring out of NumPy programming on the subject of technological know-how, math, and finance utilizing useful recipes, then this booklet is for you.

What you are going to Learn

  • Learn complex indexing and linear algebra
  • Deal with lacking inventory fee facts utilizing masked arrays
  • Explore every little thing you must learn about photo processing
  • Dive into broadcasting and histograms
  • Profile NumPy code and visualize the results
  • Speed up your code with Cython
  • Use common features and interoperability features
  • Analyze your functionality utilizing caliber Assurance
  • Learn approximately exploratory and predictive facts research with NumPy

In Detail

NumPy has the facility to provide you pace and excessive productiveness. excessive functionality calculations will be performed simply with fresh and effective code, and it permits you to execute advanced algebraic and mathematical computations in no time.

This e-book provide you with a superb starting place in NumPy arrays and common features. beginning with the install and configuration of IPython, you are going to know about complicated indexing and array thoughts in addition to commonplace but powerful capabilities. you'll then hide sensible strategies resembling photo processing, particular arrays, and common capabilities. additionally, you will know about plotting with Matplotlib and the comparable SciPy venture with assistance from examples. on the finish of the publication, you are going to research the right way to discover atmospheric strain and its similar strategies. by the point you end this ebook, you can still write fresh and quick code with NumPy.

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Learning IPython for Interactive Computing and Data Visualization - Second Edition

By Cyrille Rossant

Get all started with Python for facts research and numerical computing within the Jupyter notebook

About This Book

  • Learn the fundamentals of Python within the Jupyter Notebook
  • Analyze and visualize information with pandas, NumPy, matplotlib, and seaborn
  • Perform highly-efficient numerical computations with Numba, Cython, and ipyparallel

Who This booklet Is For

This booklet ambitions scholars, lecturers, researchers, engineers, analysts, newshounds, hobbyists, and all facts fans who're attracted to examining and visualizing real-world datasets. while you are new to programming and information research, this booklet is strictly for you. in case you are already accustomed to one other language or research software program, additionally, you will enjoy this advent to the Python information research platform. ultimately, there are extra technical subject matters for complex readers. No past adventure is needed; this ebook comprises every thing you want to know.

What you'll Learn

  • Install Anaconda and code in Python within the Jupyter Notebook
  • Load and discover datasets interactively
  • Perform advanced information manipulations successfully with pandas
  • Create attractive information visualizations with matplotlib and seaborn
  • Simulate mathematical types with NumPy
  • Visualize and procedure photographs interactively within the Jupyter laptop with scikit-image
  • Accelerate your code with Numba, Cython, and IPython.parallel
  • Extend the pc interface with HTML, JavaScript, and D3

In Detail

Python is a elementary and robust programming language. IPython bargains a handy interface to the language and its research libraries, whereas the Jupyter workstation is a wealthy setting well-adapted to information technological know-how and visualization. jointly, those open resource instruments are favourite by way of newbies and specialists around the globe, and in an enormous number of fields and endeavors.

This publication is a beginner-friendly advisor to the Python info research platform. After an advent to the Python language, IPython, and the Jupyter laptop, you are going to the way to examine and visualize info on real-world examples, find out how to create graphical person interfaces for photograph processing within the pc, and the way to accomplish quick numerical computations for medical simulations with NumPy, Numba, Cython, and ipyparallel. through the top of this e-book, it is possible for you to to accomplish in-depth analyses of all kinds of data.

Style and approach

This is a hands-on beginner-friendly advisor to research and visualize facts on real-world examples with Python and the Jupyter Notebook.

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Python Passive Network Mapping: P2NMAP

By Chet Hosmer

Python Passive community Mapping: P2NMAP is the 1st e-book to bare a innovative and open resource procedure for exposing nefarious community activity.

The "Heartbleed" vulnerability has published major weaknesses inside of company environments relating to the inability of a definitive mapping of community resources. In Python Passive community Mapping, Chet Hosmer indicates you ways to successfully and definitively passively map networks. energetic or probing easy methods to community mapping have generally been used, yet they've got many drawbacks - they could disrupt operations, crash structures, and - most significantly - omit severe nefarious task. You require a correct photo of the environments you guard and function on the way to speedily examine, mitigate, after which get over those new assault vectors. This ebook provides a deep knowing of latest concepts to passive community mapping, whereas supplying open resource Python-based instruments that may be placed into perform immediately.

Python Passive community Mapping is for practitioners, forensic investigators, IT groups, and people who interact whilst appearing incident reaction and investigating power harm, or are reading the affects of recent malware threats. these protecting severe infrastructures can have a different curiosity in this book, as lively or probing equipment of community mapping are hardly used inside those environments as any ensuing affects could be disastrous. Python Passive community Mapping is excellent to be used as a textual content in a number of educational courses to show and have interaction scholars within the artwork of passively mapping firm networks, with the additional advantage of supplying publicity to open resource Python solutions.

  • First ebook to teach you the way to take advantage of open resource Python to behavior passive community mapping
  • Provides a brand new strategy for accomplishing incident reaction and investigating the level of power harm in your systems
  • Python code forensics toolkit for community mapping incorporated at the better half website

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Numerical Python: A Practical Techniques Approach for Industry

By Robert Johansson

Numerical Python by Robert Johansson exhibits you ways to leverage the numerical and mathematical modules in Python and its average Library in addition to well known open resource numerical Python programs like NumPy, FiPy, matplotlib and extra to numerically compute ideas and mathematically version functions in a couple of components like titanic info, cloud computing, monetary engineering, enterprise administration and more.

After interpreting and utilizing this booklet, you will get a few takeaway case learn examples of purposes that may be present in parts like company administration, monstrous data/cloud computing, monetary engineering (i.e., recommendations buying and selling funding alternatives), or even games.

Up until eventually very lately, Python used to be generally considered as only a net scripting language. good, computational scientists and engineers have lately came across the pliability and gear of Python to do extra. significant facts analytics and cloud computing programmers are seeing Python's sizeable use. monetary engineers also are now applying Python of their paintings. Python seems evolving as a language which can even rival C++, Fortran, and Pascal/Delphi for numerical and mathematical computations.

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Mastering Machine Learning With scikit-learn

By Gavin Hackeling

Apply powerful studying algorithms to real-world difficulties utilizing scikit-learn

About This Book

  • Design and troubleshoot laptop studying platforms for universal projects together with regression, type, and clustering
  • Acquaint your self with well known laptop studying algorithms, together with determination timber, logistic regression, and help vector machines
  • A sensible example-based consultant that can assist you achieve services in enforcing and comparing laptop studying structures utilizing scikit-learn

Who This publication Is For

If you're a software program developer who desires to learn the way computer studying versions paintings and the way to use them successfully, this ebook is for you. Familiarity with computer studying basics and Python can be priceless, yet isn't really essential.

What you are going to Learn

  • Review primary thoughts together with supervised and unsupervised stories, universal projects, and function metrics
  • Predict the values of continuing variables utilizing linear regression
  • Create representations of files and photographs that may be utilized in desktop studying models
  • Categorize files and textual content messages utilizing logistic regression and aid vector machines
  • Classify photos by way of their subjects
  • Discover hidden constructions in information utilizing clustering and visualize complicated information utilizing decomposition
  • Evaluate the functionality of laptop studying platforms in universal tasks
  • Diagnose and redress issues of versions because of bias and variance

In Detail

This booklet examines laptop studying versions together with logistic regression, choice bushes, and help vector machines, and applies them to universal difficulties comparable to categorizing files and classifying photos. It starts with the basics of laptop studying, introducing you to the supervised-unsupervised spectrum, the makes use of of teaching and attempt info, and comparing types. you are going to the best way to use generalized linear types in regression difficulties, in addition to clear up issues of textual content and express features.

You can be familiar with using logistic regression, regularization, and some of the loss capabilities which are utilized by generalized linear types. The ebook also will stroll you thru an instance undertaking that activates you to label the main doubtful education examples. additionally, you will use an unmonitored Hidden Markov version to foretell inventory prices.

By the tip of the ebook, you may be knowledgeable in scikit-learn and should be good versed in desktop learning

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