Index

A

• Anaconda Python distribution
  • URL / Installing pandas
• appDirs
  • URL / Installing Parakeet

B

• Big O notation
  • about / Running time complexity

C

• code optimization
  • about / How to choose the right option
  • with Cython / When to go with Cython
  • with PyPy / When to go with PyPy
• Compute Unified Device Architecture (CUDA)
  • from Nvidia, URL / Multithreading
• configuration, Numba
  • No GIL / No GIL
  • NoPython mode / NoPython mode
• constant time - O(1)
  • about / Constant time – O(1)
• cProfile
  • URL / Getting to know our new best friends: the profilers
  • about / Getting to know our new best friends: the profilers, cProfile
  • example / cProfile
  • limitations / A note about limitations
  • API / The API provided
  • methods, using / The API provided
  • Stats class / The Stats class
  • Fibonacci example / Fibonacci again
  • Tweet stats example / Tweet stats
• cStringIO
  • using / Consider using cStringIO to concatenate strings
  • URL / Consider using cStringIO to concatenate strings
• ctypes library
  • about / ctypes
  • URL / ctypes
  • custom C library, loading / Loading your own custom C library
  • system library, loading / Loading a system library
• CUDA programming
  • URL / Running your code on the GPU
  • about / Running your code on the GPU
• Cython
  • about / Cython
  • URL / Cython, Installing Cython
  • installing / Installing Cython
  • C functions, calling / Calling C functions
  • naming conflicts, solving / Solving naming conflicts
  • types, defining / Defining types
  • standard Python functions, defining / Defining types during function definitions
  • C functions, defining / Defining types during function definitions
  • function types, defining / Defining types during function definitions
  • example / A Cython example
  • type definition, considerations / When to define a type
  • limitations / Limitations
  • considerations / When to go with Cython
• Cython, limitations
  • generator expressions / Generator expressions
  • comparison of char* literals / Comparison of char* literals
  • tuples, as function arguments / Tuples as function arguments
  • stack frames / Stack frames
• Cython module
  • building / Building a Cython module
  • definition files / Building a Cython module
  • implementation files / Building a Cython module
  • reference link / Building a Cython module

D

• data analysis
  • with pandas / Using pandas for data analysis
• default arguments
  • about / Usage of default arguments
• definition files
  • about / Building a Cython module
• deterministic profiler
  • about / cProfile
• dsltools
  • URL / Installing Parakeet

E

• event-based profilers
  • about / Event-based profiling
• event-based profiling
  • about / Event-based profiling
  • programming language support / Event-based profiling
• events
  • about / Events
• execution time
  • profiling / Execution time

F

• factorial time - O(n!)
  • about / Factorial time – O(n!)
• first in first out (FIFO) / Interprocess communication

G

• generators
  • about / List comprehension and generators
• Global Interpreter Lock (GIL)
  • about / Multithreading
• GPU
  • code, executing / Running your code on the GPU

I

• implementation files
  • about / Building a Cython module
• initial code base
  • about / The initial code base
  • analysing / Analyzing the code
  • scraper / Scraper
  • for analyzer script / Analyzer
• inverted index
  • URL / Inverted index
  • creating, with line_profiler / Inverted index
  • about / Inverted index
  • getOffsetUpToWord function, using / getOffsetUpToWord, getOffsetUpToWord
  • getWords function, using / getWords, getWords
  • list2dict function, using / list2dict, list2dict
  • readFileContent function, using / readFileContent
  • saveIndex function, using / saveIndex, saveIndex
  • __start__ method, using / __start__
• issues
  • solving / The problem to solve
  • data, getting from Web / Getting data from the Web
  • data, postprocessing / Postprocessing the data

J

• Just-in-time (JIT) compiler
  • about / PyPy
  • using / A Just-in-time compiler
  • optimizing / Optimizing for the JIT
  • functions, using / Think of functions
  • cStringIO, using / Consider using cStringIO to concatenate strings
  • disabling / Actions that disable the JIT
• JVM Tools Interface (JVMTI)
  • about / Event-based profiling

K

• KCacheGrind
  • about / KCacheGrind – pyprof2calltree
  • TweetStats example / A profiling example – TweetStats
  • inverted index example / A profiling example – Inverted Index
• kernprof
  • about / kernprof
  • using / kernprof
  • considerations / Some things to consider about kernprof
  • Fibonacci example / Back to Fibonacci

L

• linearithmic time - O(nlog n)
  • about / Linearithmic time – O(nlog n)
• linear time - O(n)
  • about / Linear time – O(n)
• line_profiler
  • about / Getting to know our new best friends: the profilers, line_profiler
  • URL / Getting to know our new best friends: the profilers
  • installing / line_profiler
  • kernprof, using / line_profiler
  • using / line_profiler
  • kernprof / kernprof
  • Fibonacci example / Back to Fibonacci
  • inverted index, creating / Inverted index
• list comprehension
  • about / List comprehension and generators
• logarithmic time - O(log n)
  • about / Logarithmic time – O(log n)
• lookup tables
  • about / Memoization / lookup tables
  • on list / Performing a lookup on a list or linked list
  • on linked list / Performing a lookup on a list or linked list
  • on dictionary / Simple lookup on a dictionary
  • binary search / Binary search
  • use cases / Use cases for lookup tables
• lsprofcalltree.py tool
  • about / KCacheGrind – pyprof2calltree
  • URL / KCacheGrind – pyprof2calltree

M

• matplotlib
  • URL / Using pandas for data analysis
• memory consumption
  • about / Memory consumption and memory leaks
• memory leaks
  • about / Memory consumption and memory leaks
• miniconda
  • about / Installation
  • URL / Installation
• multiprocessing
  • benefits / Multithreading
  • about / Multiprocessing
  • advantages / Multiprocessing
  • disadvantages / Multiprocessing
• multiprocessing, with Python
  • URL / Multiprocessing with Python
  • about / Multiprocessing with Python
  • exit status / Exit status
  • process pooling / Process pooling
  • interprocess communication / Interprocess communication
  • pipes / Pipes
  • events / Events
• multithreading
  • about / Multithreading
  • drawbacks / Multithreading

N

• namedtuples
  • URL / Other tips and tricks
• Natural Language Processing (NLP) / Postprocessing the data
• nfl sort
  • versus stdname sort / The Stats class
• NLTK
  • URL / Postprocessing the data
• Numba
  • about / Numba
  • URL / Numba
  • installing / Installation
  • using / Using Numba
  • code generation / Numba's code generation
  • compilation / Eager compilation
  • configuration settings / Other configuration settings
  • code, executing in GPU / Running your code on the GPU
  • reference link / Running your code on the GPU
• NumPy
  • URL / Installing Parakeet

O

• OCaml
  • URL / Multithreading
• OpenCL
  • from Khronos Group, URL / Multithreading
• OProfile
  • URL / Statistical profiling
• optimization
  • tips / Other tips and tricks
  • tricks / Other tips and tricks

P

• pandas
  • about / The pandas tool
  • URL / The pandas tool
  • installing / Installing pandas
  • used, for data analysis / Using pandas for data analysis
• Parakeet
  • about / Parakeet
  • features / Parakeet
  • installing / Installing Parakeet
  • URL / Installing Parakeet
  • working with / How does Parakeet work?
• parallelism
  • versus concurrency / Parallelism versus concurrency
• pip
  • URL / Installation
• pip command-line tool / Getting data from the Web
• pipes
  • URL / Pipes
  • about / Pipes
• premature optimization
  • risk / The risk of premature optimization
• profilers
  • about / Getting to know our new best friends: the profilers
  • cProfile / Getting to know our new best friends: the profilers
  • line_profiler / Getting to know our new best friends: the profilers
• profiling
  • about / What is profiling?
  • event-based profiling / Event-based profiling
  • statistical profiling / Statistical profiling
  • importance / The importance of profiling
  • measuring / What can we profile?
  • execution time / Execution time
  • bottlenecks / Where are the bottlenecks?
  • best practices / Profiling best practices
• profiling, best practices
  • regression-test suite, building / Build a regression-test suite
  • functional code / Mind your code
  • be patient / Be patient
  • data, gathering / Gather as much data as you can
  • data, preprocessing / Preprocess your data
  • data, visualizing / Visualize your data
• pyprof2calltree
  • about / KCacheGrind – pyprof2calltree
  • installation / Installation
  • usage / Usage
  • TweetStats example / A profiling example – TweetStats
  • inverted index example / A profiling example – Inverted Index
• PyPy
  • about / PyPy
  • URL / PyPy
  • features / PyPy
  • Just-in-time (JIT) compiler / A Just-in-time compiler
  • sandboxing / Sandboxing
  • code sample / Code sample
  • considerations / When to go with PyPy
• PyPy
  • installing / Installing PyPy

Q

• QCacheGrind
  • installing / Installation
  • URL / Installation
• quadratic time - O(n^)
  • about / Quadratic time – O(n^)

R

• read-eval-print loop(REPL)
  • about / Usage
• RTC
  • about / Running time complexity
  • constant time - O(1) / Constant time – O(1)
  • linear time - O(n) / Linear time – O(n)
  • logarithmic time - O(log n) / Logarithmic time – O(log n)
  • linearithmic time - O(nlog n) / Linearithmic time – O(nlog n)
  • factorial time - O(n!) / Factorial time – O(n!)
  • quadratic time - O(n^) / Quadratic time – O(n^)
• RunSnakeRun
  • about / RunSnakeRun
  • features / RunSnakeRun
  • installation / Installation
  • usage / Usage
  • lowest common multiplier, obtaining / Profiling examples – the lowest common multiplier
  • word, searching inside inverted index / A profiling example – search using the inverted index

S

• sandboxing
  • about / Sandboxing
• Science Fiction & Fantasy
  • URL / Getting data from the Web
• statistical profiling
  • about / Statistical profiling
  • advantages / Statistical profiling
• Stats class
  • about / The Stats class
  • methods / The Stats class
  • sorting criteria / The Stats class
  • example / The Stats class
• stdname sort
  • versus nfl sort / The Stats class
• string concatenation
  • about / String concatenation

T

• threading module
  • working with / Working with the threading module
  • thread class, URL / Working with the threading module
  • event construct, URL / Interthread communication with events
• thread module
  • used, for creating threads / Creating a thread with the thread module
  • URL / Creating a thread with the thread module
• threads
  • about / Threads
  • in Python / Threads
  • thread module / Threads
  • threading module / Threads
  • creating, thread module used / Creating a thread with the thread module
  • interthread communication, with events / Interthread communication with events
• tracing profilers
  • about / Event-based profiling

W

• wxPython
  • URL / Installation