By taking you thru the improvement of a true net program from starting to finish, the up to date moment version of this hands-on advisor demonstrates the sensible benefits of test-driven improvement (TDD) with Python. You’ll how you can write and run checks sooner than development each one a part of your app, after which strengthen the minimal volume of code required to cross these exams. the outcome? fresh code that works.
By Brett Slatkin
It is easy to begin writing code with Python: that is why the language is so immensely renowned. notwithstanding, Python has certain strengths, charms, and expressivity that may be not easy to understand firstly -- in addition to hidden pitfalls which may simply journey you up should you should not conscious of them. Effective Python might help you harness the whole energy of Python to jot down incredibly strong, effective, maintainable, and well-performing code. using the concise, scenario-driven variety pioneered in Scott Meyers's best-selling Effective C++, Brett Slatkin brings jointly fifty nine Python top practices, counsel, shortcuts, and sensible code examples from specialist programmers.
Through lifelike examples, Slatkin uncovers little-known Python quirks, intricacies, and idioms that powerfully effect code habit and function. you will select the most productive and powerful strategy to accomplish key projects while a number of suggestions exist, and the way to put in writing code that is more uncomplicated to appreciate, keep, and improve.
Drawing on his deep figuring out of Python's features, Slatkin deals functional suggestion for every significant sector of improvement with either Python 3.x and Python 2.x. insurance includes:
- Built-in modules
- Production techniques
- And more
every one part comprises particular, actionable instructions geared up into goods, each one with conscientiously worded suggestion supported by way of special technical arguments and illuminating examples. utilizing Effective Python, you could systematically enhance all of the Python code you write: no longer by means of blindly following principles or mimicking incomprehensible idioms, yet by way of gaining a deep knowing of the technical explanation why they make feel.
By Michael T. Goodrich
Based at the authors’ industry best info constructions books in Java and C++, this book deals a complete, definitive creation to facts constructions in Python by means of authoritative authors. Data constructions and Algorithms in Python is the 1st authoritative object-oriented publication on hand for Python info buildings. Designed to supply a finished advent to info constructions and algorithms, together with their layout, research, and implementation, the textual content will continue a similar basic constitution as Data constructions and Algorithms in Java and Data constructions and Algorithms in C++.
- Begins by means of discussing Python’s conceptually easy syntax, which permits for a better specialise in concepts.
- Employs a constant object-oriented standpoint through the text.
- Presents each one information constitution utilizing ADTs and their respective implementations and introduces vital layout styles as a method to prepare these implementations into periods, equipment, and objects.
- Provides a radical dialogue at the research and layout of primary facts structures.
- Includes many beneficial Python code examples, with resource code supplied at the website.
- Uses illustrations to offer facts buildings and algorithms, in addition to their research, in a transparent, visible manner.
- Provides countless numbers of workouts that advertise creativity, support readers how you can imagine like programmers, and toughen vital concepts.
- Contains many Python-code and pseudo-code fragments, and hundreds and hundreds of routines, that are divided into approximately forty% reinforcement workouts, forty% creativity routines, and 20% programming projects.
By Mark Lutz
If you might have mastered Python's basics, you are ready to begin utilizing it to get actual paintings performed. Programming Python will convey you ways, with in-depth tutorials at the language's basic program domain names: approach management, GUIs, and the net. you will additionally discover how Python is utilized in databases, networking, front-end scripting layers, textual content processing, and extra. This e-book makes a speciality of ordinary instruments and libraries to offer you a complete realizing of Python’s many jobs in useful, real-world programming.
You'll examine language syntax and programming options in a transparent and concise demeanour, with plenty of examples that illustrate either right utilization and customary idioms. thoroughly up to date for model 3.x, Programming Python additionally delves into the language as a software program improvement software, with many code examples scaled in particular for that purpose.
- Quick Python tour: construct an easy demo that comes with info illustration, object-oriented programming, item endurance, GUIs, and web site basics
- System programming: discover procedure interface instruments and methods for command-line scripting, processing documents and folders, operating courses in parallel, and more
- GUI programming: learn how to use Python’s tkinter widget library
- Internet programming: entry client-side community protocols and electronic mail instruments, use CGI scripts, and examine web site implementation techniques
- More how you can observe Python: enforce info constructions, parse text-based info, interface with databases, and expand and embed Python
By Robert Dempsey
The quantity of information produced by way of companies and units goes nowhere yet up. during this state of affairs, the most important benefit of Python is that it's a general-purpose language and provides you many of flexibleness in information buildings. Python is a wonderful software for extra really expert research projects, and is powered with comparable libraries to technique information streams, to imagine datasets, and to hold out clinical calculations. utilizing Python for enterprise intelligence (BI) might be useful remedy tough difficulties in a single go.
Rather than spending daily scouring net boards for “how-to” info, right here you'll locate greater than 60 recipes that take you thru the total means of growing actionable intelligence out of your uncooked info, it doesn't matter what form or shape it's in. in the first half-hour of commencing this publication, you'll the best way to use the newest in Python and NoSQL databases to glean insights from facts simply ready to be exploited.
We'll start with a quick-fire creation to Python for BI and exhibit you what difficulties Python solves. From there, we circulation directly to operating with a predefined info set to extract info as according to enterprise requisites, utilizing the Pandas library and MongoDB as our garage engine.
Next, we'll learn info and practice changes for BI with Python. via this, you'll assemble insightful information to help you make expert judgements on your company. the ultimate a part of the publication will exhibit you an important activity of BI―visualizing info by means of development attractive dashboards utilizing Matplotlib, PyTables, and iPython workstation.
By Wes McKinney
Python for information Analysis is anxious with the nuts and bolts of manipulating, processing, cleansing, and crunching facts in Python. it's also a pragmatic, sleek advent to clinical computing in Python, adapted for data-intensive functions. this can be a booklet in regards to the components of the Python language and libraries you’ll have to successfully resolve a extensive set of knowledge research difficulties. This publication isn't an exposition on analytical tools utilizing Python because the implementation language.
Written by means of Wes McKinney, the most writer of the pandas library, this hands-on ebook is jam-packed with functional instances reviews. It’s perfect for analysts new to Python and for Python programmers new to medical computing.
- Use the IPython interactive shell as your basic improvement environment
- Learn uncomplicated and complex NumPy (Numerical Python) features
- Get begun with information research instruments within the pandas library
- Use high-performance instruments to load, fresh, rework, merge, and reshape data
- Create scatter plots and static or interactive visualizations with matplotlib
- Apply the pandas groupby facility to slice, cube, and summarize datasets
- Measure facts through closing dates, no matter if it’s particular cases, fastened sessions, or intervals
- Learn find out how to clear up difficulties in internet analytics, social sciences, finance, and economics, via unique examples
By Magnus Lie Hetland
Gain a basic realizing of Python’s syntax and lines with the second one version of Beginning Python, an up–to–date advent and useful reference. protecting a wide range of Python–related programming subject matters, together with addressing language internals, database integration, community programming, and net providers, you’ll be guided by means of sound improvement rules. Ten accompanying initiatives will make sure you can get your fingers soiled in no time.
Updated to mirror the most recent in Python programming paradigms and several other of the main an important positive aspects present in Python 3.0 (otherwise referred to as Python 3000), complicated issues, comparable to extending Python and packaging/distributing Python purposes, also are coated.
What you’ll learn
- Become a educated Python programmer through following besides a pleasant, functional consultant to the language’s key features
- Write code quicker via studying tips to make the most of complicated beneficial properties comparable to magic tools, exceptions, and abstraction
- Gain perception into glossy Python programming paradigms together with checking out, documentation, packaging, and distribution
- Learn by means of following in addition to ten attention-grabbing tasks, together with a P2P file–sharing program, chat customer, online game, distant textual content editor, and more
- Complete, downloadable code is supplied for every undertaking!
Who this ebook is for
Programmers, beginner and another way, looking a finished creation to the Python programming language.
By Noah Gift
Python is a perfect language for fixing difficulties, specifically in Linux and Unix networks. With this pragmatic publication, directors can overview quite a few projects that regularly take place within the administration of those platforms, and find out how Python provides a extra effective and not more painful method to deal with them.
every one bankruptcy in Python for Unix and Linux procedure Administration offers a selected administrative factor, akin to concurrency or facts backup, and provides Python strategies via hands-on examples. when you end this booklet, you will improve your personal set of command-line utilities with Python to take on quite a lot of difficulties. detect how this language might help you:
- Read textual content records and extract information
- Run initiatives at the same time utilizing the threading and forking options
- Get info from one approach to a different utilizing community facilities
- Create clickable GUIs to deal with huge and intricate utilities
- Monitor huge clusters of machines by way of interacting with SNMP programmatically
- Master the IPython Interactive Python shell to interchange or increase Bash, Korn, or Z-Shell
- Integrate Cloud Computing into your infrastructure, and learn how to write a Google App Engine Application
- Solve designated facts backup demanding situations with personalized scripts
- Interact with MySQL, SQLite, Oracle, Postgres, Django ORM, and SQLAlchemy
With this booklet, you will package deal and set up your Python purposes and libraries, and write code that runs both good on a number of Unix systems. you will additionally find out about a number of Python-related applied sciences that may make your existence a lot easier.
By Matt Harrison
Examine Python decorators the ideal approach!
By Jacob Perkins
Use Python's NLTK suite of libraries to maximise your ordinary Language Processing services. * fast familiarize yourself with normal Language Processing ? with textual content research, textual content Mining, and past * learn the way machines and crawlers interpret and method average languages * simply paintings with large quantities of information and the right way to deal with disbursed processing * a part of Packt's Cookbook sequence: each one recipe is a gently equipped series of directions to accomplish the duty as successfully as attainable intimately average Language Processing is used in every single place ? in se's, spell checkers, cellphones, machine video games ? even your washer. Python's typical Language Toolkit (NLTK) suite of libraries has quickly emerged as probably the most effective instruments for traditional Language Processing. you must hire not anything lower than the easiest concepts in usual Language Processing ? and this publication is your solution. Python textual content Processing with NLTK 2.0 Cookbook is your convenient and illustrative consultant, in an effort to stroll you thru the entire ordinary Language Processing ideas in a step?by-step demeanour. it's going to demystify the complex positive factors of textual content research and textual content mining utilizing the great NLTK suite. This booklet cuts brief the preamble and also you dive correct into the technological know-how of textual content processing with a pragmatic hands-on method. start off with studying tokenization of textual content. Get an summary of WordNet and the way to exploit it. study the fundamentals in addition to complicated gains of Stemming and Lemmatization. realize a number of how you can exchange phrases with less complicated and extra universal (read: extra searched) variations. Create your individual corpora and learn how to create customized corpus readers for JSON documents in addition to for info saved in MongoDB. Use and manage POS taggers. remodel and normalize parsed chunks to provide a canonical shape with no altering their which means. Dig into characteristic extraction and textual content type. how to simply deal with large quantities of information with none loss in potency or pace. This booklet will train you all that and past, in a hands-on learn-by-doing demeanour. Make your self a professional in utilizing the NLTK for ordinary Language Processing with this convenient significant other. What you are going to examine from this e-book * research textual content categorization and subject id * examine Stemming and Lemmatization and the way to head past the standard spell checker * exchange negations with antonyms on your textual content * discover ways to tokenize phrases into lists of sentences and phrases, and achieve an perception into WordNet * rework and manage chunks and bushes * research complex positive aspects of corpus readers and create your personal customized corpora * Tag various elements of speech via growing, education, and utilizing a part-of-speech tagger * enhance accuracy through combining a number of part-of-speech taggers * the best way to do partial parsing to extract small chunks of textual content from a part-of-speech tagged sentence * Produce an alternate canonical shape with out altering the which means by means of normalizing parsed chunks * find out how se's use average Language Processing to procedure textual content * Make your website extra discoverable by way of studying easy methods to instantly exchange phrases with extra searched equivalents * Parse dates, instances, and HTML * teach and manage kinds of classifiers procedure The learn-by-doing method of this booklet will aid you dive correct into the center of textual content processing from the first actual web page. each one recipe is punctiliously designed to meet your urge for food for usual Language Processing. filled with quite a few illustrative examples and code samples, it'll make the duty of utilizing the NLTK for common Language Processing effortless and simple. Who this ebook is written for This booklet is for Python programmers who are looking to fast familiarize yourself with utilizing the NLTK for common Language Processing. Familiarity with uncomplicated textual content processing recommendations is needed. Programmers skilled within the NLTK also will locate it worthy. scholars of linguistics will locate it beneficial.