Learning concurrency in Python : speed up your Python code with clean, readable, and advanced concurrency techniques

Learning concurrency in Python speed up your Python code with clean, readable, and advanced concurrency techniques

Practically and deeply understand concurrency in Python to write efficient programs About This Book Build highly efficient, robust, and concurrent applications Work through practical examples that will help you address the challenges of writing concurrent code Improve the overall speed of execution...

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Detalles Bibliográficos
Otros Autores: Forbes, Elliot, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham : Packt 2017.
Edición:1st edition
Materias:
Python (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630708406719
Tabla de Contenidos:
  • Cover
  • Copyright
  • Credits
  • About the Author
  • About the Reviewer
  • www.PacktPub.com
  • Customer Feedback
  • Table of Contents
  • Preface
  • Chapter 1: Speed It Up!
  • History of concurrency
  • Threads and multithreading
  • What is a thread?
  • Types of threads
  • What is multithreading?
  • Processes
  • Properties of processes
  • Multiprocessing
  • Event-driven programming
  • Turtle
  • Breaking it down
  • Reactive programming
  • ReactiveX - RxPy
  • Breaking it down
  • GPU programming
  • PyCUDA
  • OpenCL
  • Theano
  • The limitations of Python
  • Jython
  • IronPython
  • Why should we use Python?
  • Concurrent image download
  • Sequential download
  • Breaking it down
  • Concurrent download
  • Breaking it down
  • Improving number crunching with multiprocessing
  • Sequential prime factorization
  • Breaking it down
  • Concurrent prime factorization
  • Breaking it down
  • Summary
  • Chapter 2: Parallelize It
  • Understanding concurrency
  • Properties of concurrent systems
  • I/O bottlenecks
  • Understanding parallelism
  • CPU-bound bottlenecks
  • How do they work on a CPU?
  • Single-core CPUs
  • Clock rate
  • Martelli model of scalability
  • Time-sharing - the task scheduler
  • Multi-core processors
  • System architecture styles
  • SISD
  • SIMD
  • MISD
  • MIMD
  • Computer memory architecture styles
  • UMA
  • NUMA
  • Summary
  • Chapter 3: Life of a Thread
  • Threads in Python
  • Thread state
  • State flow chart
  • Python example of thread state
  • Breaking it down
  • Different types of threads
  • POSIX threads
  • Windows threads
  • The ways to start a thread
  • Starting a thread
  • Inheriting from the thread class
  • Breaking it down
  • Forking
  • Example
  • Breaking it down
  • Daemonizing a thread
  • Example
  • Breaking it down
  • Handling threads in Python
  • Starting loads of threads
  • Example
  • Breaking it down.
  • Slowing down programs using threads
  • Example
  • Breaking it down
  • Getting the total number of active threads
  • Example
  • Breaking it down
  • Getting the current thread
  • Example
  • Breaking it down
  • Main thread
  • Example
  • Breaking it down
  • Enumerating all threads
  • Example
  • Breaking it down
  • Identifying threads
  • Example
  • Breakdown
  • Ending a thread
  • Best practice in stopping threads
  • Example
  • Output
  • Orphan processes
  • How does the operating system handle threads
  • Creating processes versus threads
  • Example
  • Breaking it down
  • Multithreading models
  • One-to-one thread mapping
  • Many-to-one
  • Many-to-many
  • Summary
  • Chapter 4: Synchronization between Threads
  • Synchronization between threads
  • The Dining Philosophers
  • Example
  • Output
  • Race conditions
  • Process execution sequence
  • The solution
  • Critical sections
  • Filesystem
  • Life-critical systems
  • Shared resources and data races
  • The join method
  • Breaking it down
  • Putting it together
  • Locks
  • Example
  • Breaking it down
  • RLocks
  • Example
  • Breaking it down
  • Output
  • RLocks versus regular locks
  • Condition
  • Definition
  • Example
  • Our publisher
  • Our subscriber
  • Kicking it off
  • The results
  • Semaphores
  • Class definition
  • Example
  • The TicketSeller class
  • Output
  • Thread race
  • Bounded semaphores
  • Events
  • Example
  • Breaking it down
  • Barriers
  • Example
  • Breaking it down
  • Output
  • Summary
  • Chapter 5: Communication between Threads
  • Standard data structures
  • Sets
  • Extending the class
  • Exercise - extending other primitives
  • Decorator
  • Class decorator
  • Lists
  • Queues
  • FIFO queues
  • Example
  • Breaking it down
  • Output
  • LIFO queues
  • Example
  • Breaking it down
  • Output
  • PriorityQueue
  • Example
  • Breakdown
  • Output
  • Queue objects
  • Full/empty queues
  • Example.
  • Output
  • The join() function
  • Example
  • Breakdown
  • Output
  • Deque objects
  • Example
  • Breakdown
  • Output
  • Appending elements
  • Example
  • Breaking it down
  • Output
  • Popping elements
  • Example
  • Breaking it down
  • Output
  • Inserting elements
  • Example
  • Breaking it down
  • Output
  • Rotation
  • Example
  • Breaking it down
  • Output
  • Defining your own thread-safe communication structures
  • A web Crawler example
  • Requirements
  • Design
  • Our Crawler class
  • Our starting point
  • Extending the queue object
  • Breaking it down
  • Output
  • Future enhancements
  • Conclusion
  • Exercise - testing your skills
  • Summary
  • Chapter 6: Debug and Benchmark
  • Testing strategies
  • Why do we test?
  • Testing concurrent software systems
  • What should we test?
  • Unit tests
  • PyUnit
  • Example
  • Output
  • Expanding our test suite
  • Unit testing concurrent code
  • Integration tests
  • Debugging
  • Make it work as a single thread
  • Pdb
  • An interactive example
  • Catching exceptions in child threads
  • Benchmarking
  • The timeit module
  • Timeit versus time
  • Command-line example
  • Importing timeit into your code
  • Utilizing decorators
  • Timing context manager
  • Output
  • Profiling
  • cProfile
  • Simple profile example
  • The line_profiler tool
  • Kernprof
  • Memory profiling
  • Memory profile graphs
  • Summary
  • Chapter 7: Executors and Pools
  • Concurrent futures
  • Executor objects
  • Creating a ThreadPoolExecutor
  • Example
  • Output
  • Context manager
  • Example
  • Output
  • Maps
  • Example
  • Output
  • Shutdown of executor objects
  • Example
  • Output
  • Future objects
  • Methods in future objects
  • The result() method
  • The add_done_callback() method
  • The .running() method
  • The cancel() method
  • The .exception() method
  • The .done() method
  • Unit testing future objects.
  • The set_running_or_notify_cancel() method
  • The set_result() method
  • The set_exception() method
  • Cancelling callable
  • Example
  • Output
  • Getting the result
  • Example
  • Output
  • Using as_completed
  • Example
  • Output
  • Setting callbacks
  • Example
  • Output
  • Chaining callbacks
  • Exception classes
  • Example
  • Output
  • ProcessPoolExecutor
  • Creating a ProcessPoolExecutor
  • Example
  • Output
  • Context Manager
  • Example
  • Output
  • Exercise
  • Getting started
  • Improving the speed of computationally bound problems
  • Full code sample
  • Output
  • Improving our crawler
  • The plan
  • New improvements
  • Refactoring our code
  • Storing the results in a CSV file
  • Exercise - capture more info from each page crawl
  • concurrent.futures in Python 2.7
  • Summary
  • Chapter 8: Multiprocessing
  • Working around the GIL
  • Utilizing sub-processes
  • Example
  • Output
  • The life of a process
  • Starting a process using fork
  • Spawning a process
  • Forkserver
  • Daemon processes
  • Example
  • Breaking it down
  • Output
  • Identifying processes using PIDs
  • Example
  • Output
  • Terminating a process
  • Example
  • Getting the current process
  • Subclassing processes
  • Example
  • Output
  • Multiprocessing pools
  • The difference between concurrent.futures.ProcessPoolExecutor and Pool
  • Context manager
  • Example
  • Output
  • Submitting tasks to a process pool
  • Apply
  • Apply_async
  • Map
  • Map_async
  • Imap
  • Imap_unordered
  • Starmap
  • Starmap_async
  • Maxtasksperchild
  • Communication between processes
  • Pipes
  • Anonymous pipes
  • Named pipes
  • Working with pipes
  • Example
  • Handling Exceptions
  • Using pipes
  • Multiprocessing managers
  • Namespaces
  • Example
  • Queues
  • Example
  • Output
  • Listeners and clients
  • Example
  • The Listener class
  • The Client class
  • Output
  • Logging
  • Example.
  • Communicating sequential processes
  • PyCSP
  • Processes in PyCSP
  • Output
  • Summary
  • Chapter 9: Event-Driven Programming
  • Event-driven programming
  • The event loop
  • Asyncio
  • Getting started
  • Event loops
  • The run_forever() method
  • The run_until_complete() method
  • The stop() method
  • The is_closed() method
  • The close() function
  • Tasks
  • Example
  • The all_tasks(loop=None) method
  • The current_tasks() function
  • The cancel() function
  • Task functions
  • The as_completed(fs, *, loop=
  • The ensure_future(coro_or_future, *, loop=
  • The wrap_future(future, *, loop=
  • The gather(*coroes_or_futures, loop=
  • The wait() function
  • Futures
  • Example
  • Output
  • Coroutines
  • Chaining coroutines
  • Output
  • Transports
  • Protocols
  • Synchronization between coroutines
  • Locks
  • Queues
  • Events and conditions
  • Semaphores and BoundedSemaphores
  • Sub-processes
  • Debugging asyncio programs
  • Debug mode
  • Twisted
  • A simple web server example
  • Gevent
  • Event loops
  • Greenlets
  • Simple example-hostnames
  • Output
  • Monkey patching
  • Summary
  • Chapter 10: Reactive Programming
  • Basic reactive programming
  • Maintaining purity
  • ReactiveX, or RX
  • Installing RxPY
  • Observables
  • Creating observers
  • Example
  • Example 2
  • Breaking it down
  • Output
  • Lambda functions
  • Example
  • Breaking it down
  • On_next, on_completed, and on_error in lambda form
  • Output
  • Operators and chaining
  • Filter example
  • Breaking it down
  • Chained operators
  • The different operators
  • Creating observables
  • Transforming observables
  • Filtering observables
  • Error-handling observables
  • Hot and cold observables
  • Emitting events
  • Example
  • Breaking it down
  • Output
  • Multicasting
  • Example
  • Output
  • Combining observables
  • Zip() example
  • Output
  • The merge_all() operator
  • Output
  • Concurrency.
  • Example.

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