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HEAD FIRST DESIGN PATTERNS: BUILDING EXTENSIBLE AND MAINTAINABLE OBJECT-ORIENTED SOFTWARE, SECOND EDITION
NRS 2360.00
 
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EFFECTIVE PYTHON: 59 SPECIFIC WAYS TO WRITE BETTER PYTHON
Effective python will help students harness the full power of python to write exceptionally robust, efficient, maintainable, and well-performing code. utilizing the concise, scenario-driven style pioneered in scott meyers's best-selling effective c++, brett slatkin brings together 53 python best practices, tips, shortcuts, and realistic code examples from expert programmers. each section contains specific, actionable guidelines organized into items, each with carefully worded advice supported by detailed technical arguments and illuminating examples. table of content chapter 1: pythonic thinking item 1: know which version of python you're using item 2: follow the pep 8 style guide item 3: know the differences between bytes, str, and unicode item 4: write helper functions instead of complex expressions item 5: know how to slice sequences item 6: avoid using start, end, and stride in a single slice item 7: use list comprehensions instead of map and filter item 8: avoid more than two expressions in list comprehensions item 9: consider generator expressions for large comprehensions item 10: prefer enumerate over range item 11: use zip to process iterators in parallel item 12: avoid else blocks after for and while loops item 13: take advantage of each block in try/except/else/finally chapter 2: functions item 14: prefer exceptions to returning none item 15: know how closures interact with variable scope item 16: consider generators instead of returning lists item 17: be defensive when iterating over arguments item 18: reduce visual noise with variable positional arguments item 19: provide optional behavior with keyword arguments item 20: use none and docstrings to specify dynamic default arguments item 21: enforce clarity with keyword-only arguments chapter 3: classes and inheritance item 22: prefer helper classes over bookkeeping with dictionaries and tuples item 23: accept functions for simple interfaces instead of classes item 24: use @classmethod polymorphism to construct objects generically item 25: initialize parent classes with super item 26: use multiple inheritance only for mix-in utility classes item 27: prefer public attributes over private ones item 28: inherit from collections.abc for custom container types chapter 4: metaclasses and attributes item 29: use plain attributes instead of get and set methods item 30: consider @property instead of refactoring attributes item 31: use descriptors for reusable @property methods item 32: use __getattr__, __getattribute__, and __setattr__ for lazy attributes item 33: validate subclasses with metaclasses item 34: register class existence with metaclasses item 35: annotate class attributes with metaclasses chapter 5: concurrency and parallelism item 36: use subprocess to manage child processes item 37: use threads for blocking i/o, avoid for parallelism item 38: use lock to prevent data races in threads item 39: use queue to coordinate work between threads item 40: consider coroutines to run many functions concurrently item 41: consider concurrent.futures for true parallelism chapter 6: built-in modules item 42: define function decorators with functools.wraps item 43: consider contextlib and with statements for reusable try/finally behavior item 44: make pickle reliable with copyreg item 45: use datetime instead of time for local clocks item 46: use built-in algorithms and data structures item 47: use decimal when precision is paramount item 48: know where to find community-built modules chapter 7: collaboration item 49: write docstrings for every function, class, and module item 50: use packages to organize modules and provide stable apis item 51: define a root exception to insulate callers from apis item 52: know how to break circular dependencies item 53: use virtual environments for isolated and reproducible dependencies chapter 8: production item 54: consider module-scoped code to configure deployment environments item 55: use repr strings for debugging output item 56: test everything with unittest item 57: consider interactive debugging with pdb item 58: profile before optimizing item 59: use tracemalloc to understand memory usage and leaks salient features • covers python algorithms, objects, concurrency, collaboration, built-in modules, and much more • addresses both python 3 and python 2 • guides students to a far deeper understanding of the python language, so they know why its unique idioms and rules of thumb make sense • follows the enormously popular "effective" format proven in scott meyers' classic effective c++.

Author : Brett slatkin
Publication : Pearson
Isbn : 9789332552364
Store book number : 107
NRS 600.00
  
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