Python Language
- Getting started with Python Language
- Awesome Book
- Awesome Community
- Awesome Course
- Awesome Tutorial
- Awesome YouTube
- *args and **kwargs
- 2to3 tool
- Abstract Base Classes (abc)
- Abstract syntax tree
- Accessing Python source code and bytecode
- Alternatives to switch statement from other languages
- ArcPy
- Arrays
- Asyncio Module
- Attribute Access
- Audio
- Basic Curses with Python
- Basic Input and Output
- Binary Data
- Bitwise Operators
- Boolean Operators
- Call Python from C#
- Checking Path Existence and Permissions
- ChemPy - python package
- Classes
- CLI subcommands with precise help output
- Code blocks, execution frames, and namespaces
- Collections module
- Comments and Documentation
- Common Pitfalls
- Commonwealth Exceptions
- Comparisons
- Complex math
- Conditionals
- configparser
- Connecting Python to SQL Server
- Context Managers (“with” Statement)
- Copying data
- Counting
- Create virtual environment with virtualenvwrapper in windows
- Creating a Windows service using Python
- Creating Python packages
- ctypes
- Data Serialization
- Data Visualization with Python
- Database Access
- Date and Time
- Date Formatting
- Debugging
- Decorators
- Defining functions with list arguments
- Deployment
- Deque Module
- Descriptor
- Design Patterns
- Dictionary
- Difference between Module and Package
- Distribution
- Django
- Dynamic code execution with `exec` and `eval`
- Enum
- Exceptions
- Exponentiation
- Files & Folders I/O
- Filter
- Flask
- Functional Programming in Python
- Functions
- Functools Module
- Garbage Collection
- Generators
- getting start with GZip
- graph-tool
- groupby()
- hashlib
- Heapq
- Hidden Features
- HTML Parsing
- Idioms
- ijson
- Immutable datatypes(int, float, str, tuple and frozensets)
- Importing modules
- Incompatibilities moving from Python 2 to Python 3
- Indentation
- Indexing and Slicing
- Input, Subset and Output External Data Files using Pandas
- Introduction to RabbitMQ using AMQPStorm
- IoT Programming with Python and Raspberry PI
- Iterables and Iterators
- Itertools Module
- JSON Module
- kivy - Cross-platform Python Framework for NUI Development
- Linked List Node
- Linked lists
- List
- List comprehensions
- List Comprehensions
- List destructuring (aka packing and unpacking)
- List slicing (selecting parts of lists)
- Logging
- Loops
- Manipulating XML
- Map Function
- Basic use of map, itertools.imap and future_builtins.map
- Mapping each value in an iterable
- Mapping values of different iterables
- Series and Parallel Mapping
- Transposing with Map: Using "None" as function argument (python 2.x only)
- Math Module
- Metaclasses
- Method Overriding
- Mixins
- Multidimensional arrays
- Multiprocessing
- Multithreading
- Mutable vs Immutable (and Hashable) in Python
- Neo4j and Cypher using Py2Neo
- Non-official Python implementations
- Operator module
- Operator Precedence
- Optical Character Recognition
- os.path
- Overloading
- Pandas Transform: Preform operations on groups and concatenate the results
- Parallel computation
- Parsing Command Line arguments
- Partial functions
- Performance optimization
- Pickle data serialisation
- Pillow
- pip: PyPI Package Manager
- Plotting with Matplotlib
- Plugin and Extension Classes
- Polymorphism
- PostgreSQL
- Processes and Threads
- Profiling
- Property Objects
- py.test
- pyaudio
- pyautogui module
- pygame
- Pyglet
- PyInstaller - Distributing Python Code
- Python and Excel
- Python Anti-Patterns
- Python concurrency
- Python Data Types
- Python HTTP Server
- Python Lex-Yacc
- Python Networking
- Python Persistence
- Python Requests Post
- Python Serial Communication (pyserial)
- Python Server Sent Events
- Python speed of program
- Python Virtual Environment - virtualenv
- Queue Module
- Raise Custom Errors / Exceptions
- Random module
- Reading and Writing CSV
- Recursion
- Reduce
- Regular Expressions (Regex)
- Searching
- Secure Shell Connection in Python
- Security and Cryptography
- Set
- setup.py
- shelve
- Similarities in syntax, Differences in meaning: Python vs. JavaScript
- Simple Mathematical Operators
- Sockets
- Sockets And Message Encryption/Decryption Between Client and Server
- Sorting, Minimum and Maximum
- Sqlite3 Module
- Stack
- String Formatting
- String Methods
- String representations of class instances: __str__ and __repr__ methods
- Subprocess Library
- sys
- tempfile NamedTemporaryFile
- Templates in python
- The __name__ special variable
- The base64 Module
- The dis module
- The Interpreter (Command Line Console)
- The locale Module
- The os Module
- The pass statement
- The Print Function
- tkinter
- Tuple
- Turtle Graphics
- Type Hints
- Unicode
- Unicode and bytes
- Unit Testing
- Unzipping Files
- urllib
- Usage of "pip" module: PyPI Package Manager
- User-Defined Methods
- Using loops within functions
- Variable Scope and Binding
- virtual environment with virtualenvwrapper
- Virtual environments
- Web scraping with Python
- Web Server Gateway Interface (WSGI)
- Webbrowser Module
- Websockets
- Working around the Global Interpreter Lock (GIL)
- Working with ZIP archives
- Writing extensions
- Writing to CSV from String or List
Python Language Map Function Mapping each value in an iterable
Example
For example, you can take the absolute value of each element:
list(map(abs, (1, -1, 2, -2, 3, -3))) # the call to `list` is unnecessary in 2.x
# Out: [1, 1, 2, 2, 3, 3]
Anonymous function also support for mapping a list:
map(lambda x:x*2, [1, 2, 3, 4, 5])
# Out: [2, 4, 6, 8, 10]
or converting decimal values to percentages:
def to_percent(num):
return num * 100
list(map(to_percent, [0.95, 0.75, 1.01, 0.1]))
# Out: [95.0, 75.0, 101.0, 10.0]
or converting dollars to euros (given an exchange rate):
from functools import partial
from operator import mul
rate = 0.9 # fictitious exchange rate, 1 dollar = 0.9 euros
dollars = {'under_my_bed': 1000,
'jeans': 45,
'bank': 5000}
sum(map(partial(mul, rate), dollars.values()))
# Out: 5440.5
functools.partial is a convenient way to fix parameters of functions so that they can be used with map instead of using lambda or creating customized functions.
