Cargando…
Functional Python programming : discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads /
Python is an easy-to-learn and extensible programming language that offers a number of functional programming features. This practical guide demonstrates the Python implementation of a number of functional programming techniques and design patterns. Through this book, you'll understand what fun...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Edición: | Second edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Ii 4500 | ||
|---|---|---|---|
| 001 | EBSCO_on1032707716 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr |n|---||||| | ||
| 008 | 180428s2018 enk o 001 0 eng d | ||
| 040 | |a EBLCP |b eng |e pn |c EBLCP |d OCLCQ |d MERUC |d IDB |d OCLCF |d VT2 |d OCLCQ |d LVT |d C6I |d YDX |d N$T |d UKMGB |d ZCU |d UKAHL |d OCLCQ |d K6U |d OCLCO |d OCLCQ |d OCLCO | ||
| 015 | |a GBB877786 |2 bnb | ||
| 016 | 7 | |a 018847176 |2 Uk | |
| 019 | |a 1032660598 |a 1032720633 |a 1065326113 | ||
| 020 | |a 9781788621854 | ||
| 020 | |a 1788621859 | ||
| 020 | |a 9781788627061 | ||
| 020 | |a 1788627067 | ||
| 024 | 3 | |a 9781788627061 | |
| 029 | 1 | |a UKMGB |b 018847176 | |
| 029 | 1 | |a AU@ |b 000067301876 | |
| 035 | |a (OCoLC)1032707716 |z (OCoLC)1032660598 |z (OCoLC)1032720633 |z (OCoLC)1065326113 | ||
| 037 | |a B09385 |b 01201872 | ||
| 050 | 4 | |a QA76.73.P98 |b L688 2018 | |
| 072 | 7 | |a COM |x 051360 |2 bisacsh | |
| 082 | 0 | 4 | |a 005.1/17 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Lott, Steven F., |e author. | |
| 245 | 1 | 0 | |a Functional Python programming : |b discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads / |c Steven F. Lott. |
| 250 | |a Second edition. | ||
| 260 | |a Birmingham, UK : |b Packt Publishing, |c 2018. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index. | ||
| 520 | |a Python is an easy-to-learn and extensible programming language that offers a number of functional programming features. This practical guide demonstrates the Python implementation of a number of functional programming techniques and design patterns. Through this book, you'll understand what functional programming is all about, its impact on ... | ||
| 505 | 0 | |a Cover -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Understanding Functional Programming -- Identifying a paradigm -- Subdividing the procedural paradigm -- Using the functional paradigm -- Using a functional hybrid -- Looking at object creation -- The stack of turtles -- A classic example of functional programming -- Exploratory data analysis -- Summary -- Chapter 2: Introducing Essential Functional Concepts -- First-class functions -- Pure functions -- Higher-order functions -- Immutable data -- Strict and non-strict evaluation -- Recursion instead of an explicit loop state -- Functional type systems -- Familiar territory -- Learning some advanced concepts -- Summary -- Chapter 3: Functions, Iterators, and Generators -- Writing pure functions -- Functions as first-class objects -- Using strings -- Using tuples and named tuples -- Using generator expressions -- Exploring the limitations of generators -- Combining generator expressions -- Cleaning raw data with generator functions -- Using lists, dicts, and sets -- Using stateful mappings -- Using the bisect module to create a mapping -- Using stateful sets -- Summary -- Chapter 4: Working with Collections -- An overview of function varieties -- Working with iterables -- Parsing an XML file -- Parsing a file at a higher level -- Pairing up items from a sequence -- Using the iter() function explicitly -- Extending a simple loop -- Applying generator expressions to scalar functions -- Using any() and all() as reductions -- Using len() and sum() -- Using sums and counts for statistics -- Using zip() to structure and flatten sequences -- Unzipping a zipped sequence -- Flattening sequences -- Structuring flat sequences -- Structuring flat sequences -- an alternative approach -- Using reversed() to change the order. | |
| 505 | 8 | |a Using enumerate() to include a sequence number -- Summary -- Chapter 5: Higher-Order Functions -- Using max() and min() to find extrema -- Using Python lambda forms -- Lambdas and the lambda calculus -- Using the map() function to apply a function to a collection -- Working with lambda forms and map() -- Using map() with multiple sequences -- Using the filter() function to pass or reject data -- Using filter() to identify outliers -- The iter() function with a sentinel value -- Using sorted() to put data in order -- Writing higher-order functions -- Writing higher-order mappings and filters -- Unwrapping data while mapping -- Wrapping additional data while mapping -- Flattening data while mapping -- Structuring data while filtering -- Writing generator functions -- Building higher-order functions with callables -- Assuring good functional design -- Review of some design patterns -- Summary -- Chapter 6: Recursions and Reductions -- Simple numerical recursions -- Implementing tail-call optimization -- Leaving recursion in place -- Handling difficult tail-call optimization -- Processing collections through recursion -- Tail-call optimization for collections -- Reductions and folding a collection from many items to one -- Group-by reduction from many items to fewer -- Building a mapping with Counter -- Building a mapping by sorting -- Grouping or partitioning data by key values -- Writing more general group-by reductions -- Writing higher-order reductions -- Writing file parsers -- Parsing CSV files -- Parsing plain text files with headers -- Summary -- Chapter 7: Additional Tuple Techniques -- Using tuples to collect data -- Using named tuples to collect data -- Building named tuples with functional constructors -- Avoiding stateful classes by using families of tuples -- Assigning statistical ranks -- Wrapping instead of state changing. | |
| 505 | 8 | |a Rewrapping instead of state changing -- Computing Spearman rank-order correlation -- Polymorphism and type-pattern matching -- Summary -- Chapter 8: The Itertools Module -- Working with the infinite iterators -- Counting with count() -- Counting with float arguments -- Re-iterating a cycle with cycle() -- Repeating a single value with repeat() -- Using the finite iterators -- Assigning numbers with enumerate() -- Running totals with accumulate() -- Combining iterators with chain() -- Partitioning an iterator with groupby() -- Merging iterables with zip_longest() and zip() -- Filtering with compress() -- Picking subsets with islice() -- Stateful filtering with dropwhile() and takewhile() -- Two approaches to filtering with filterfalse() and filter() -- Applying a function to data via starmap() and map() -- Cloning iterators with tee() -- The itertools recipes -- Summary -- Chapter 9: More Itertools Techniques -- Enumerating the Cartesian product -- Reducing a product -- Computing distances -- Getting all pixels and all colors -- Performance analysis -- Rearranging the problem -- Combining two transformations -- Permuting a collection of values -- Generating all combinations -- Recipes -- Summary -- Chapter 10: The Functools Module -- Function tools -- Memoizing previous results with lru_cache -- Defining classes with total ordering -- Defining number classes -- Applying partial arguments with partial() -- Reducing sets of data with the reduce() function -- Combining map() and reduce() -- Using the reduce() and partial() functions -- Using the map() and reduce() functions to sanitize raw data -- Using the groupby() and reduce() functions -- Summary -- Chapter 11: Decorator Design Techniques -- Decorators as higher-order functions -- Using the functools update_wrapper() functions -- Cross-cutting concerns -- Composite design -- Preprocessing bad data. | |
| 505 | 8 | |a Adding a parameter to a decorator -- Implementing more complex decorators -- Complex design considerations -- Summary -- Chapter 12: The Multiprocessing and Threading Modules -- Functional programming and concurrency -- What concurrency really means -- The boundary conditions -- Sharing resources with process or threads -- Where benefits will accrue -- Using multiprocessing pools and tasks -- Processing many large files -- Parsing log files -- gathering the rows -- Parsing log lines into namedtuples -- Parsing additional fields of an Access object -- Filtering the access details -- Analyzing the access details -- The complete analysis process -- Using a multiprocessing pool for concurrent processing -- Using apply() to make a single request -- Using the map_async(), starmap_async(), and apply_async() functions -- More complex multiprocessing architectures -- Using the concurrent.futures module -- Using concurrent.futures thread pools -- Using the threading and queue modules -- Designing concurrent processing -- Summary -- Chapter 13: Conditional Expressions and the Operator Module -- Evaluating conditional expressions -- Exploiting non-strict dictionary rules -- Filtering true conditional expressions -- Finding a matching pattern -- Using the operator module instead of lambdas -- Getting named attributes when using higher-order functions -- Starmapping with operators -- Reducing with operator module functions -- Summary -- Chapter 14: The PyMonad Library -- Downloading and installing -- Functional composition and currying -- Using curried higher-order functions -- Currying the hard way -- Functional composition and the PyMonad * operator -- Functors and applicative functors -- Using the lazy List() functor -- Monad bind() function and the>> operator -- Implementing simulation with monads -- Additional PyMonad features -- Summary. | |
| 505 | 8 | |a Chapter 15: A Functional Approach to Web Services -- The HTTP request-response model -- Injecting state through cookies -- Considering a server with a functional design -- Looking more deeply into the functional view -- Nesting the services -- The WSGI standard -- Throwing exceptions during WSGI processing -- Pragmatic WSGI applications -- Defining web services as functions -- Creating the WSGI application -- Getting raw data -- Applying a filter -- Serializing the results -- Serializing data into JSON or CSV formats -- Serializing data into XML -- Serializing data into HTML -- Tracking usage -- Summary -- Chapter 16: Optimizations and Improvements -- Memoization and caching -- Specializing memoization -- Tail recursion optimizations -- Optimizing storage -- Optimizing accuracy -- Reducing accuracy based on audience requirements -- Case study-making a chi-squared decision -- Filtering and reducing the raw data with a Counter object -- Reading summarized data -- Computing sums with a Counter object -- Computing probabilities from Counter objects -- Computing expected values and displaying a contingency table -- Computing the chi-squared value -- Computing the chi-squared threshold -- Computing the incomplete gamma function -- Computing the complete gamma function -- Computing the odds of a distribution being random -- Functional programming design patterns -- Summary -- Other Books You May Enjoy -- Index. | |
| 588 | 0 | |a Print version record. | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Application software |x Development. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Logiciels d'application |x Développement. | |
| 650 | 7 | |a COMPUTERS |x Programming Languages |x Python. |2 bisacsh | |
| 650 | 7 | |a Application software |x Development |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 776 | 0 | 8 | |i Print version: |a F. Lott, Steven. |t Functional Python Programming : Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads, 2nd Edition. |d Birmingham : Packt Publishing, ©2018 |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1795477 |z Texto completo |
| 938 | |a Askews and Holts Library Services |b ASKH |n BDZ0036647439 | ||
| 938 | |a EBL - Ebook Library |b EBLB |n EBL5353672 | ||
| 938 | |a EBSCOhost |b EBSC |n 1795477 | ||
| 938 | |a YBP Library Services |b YANK |n 15302009 | ||
| 994 | |a 92 |b IZTAP | ||