Python Language
- Getting started with Python Language
- Awesome Book
- Awesome Community
- Awesome Course
- Awesome Tutorial
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- *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
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- Call Python from C#
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- ChemPy - python package
- Classes
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- Code blocks, execution frames, and namespaces
- Collections module
- Comments and Documentation
- Common Pitfalls
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- Comparisons
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- configparser
- Connecting Python to SQL Server
- Context Managers (“with” Statement)
- Copying data
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- Creating a Windows service using Python
- Creating Python packages
- ctypes
- Data Serialization
- Data Visualization with Python
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- Deque Module
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- hashlib
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- 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
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- List comprehensions
- List Comprehensions
- Avoid repetitive and expensive operations using conditional clause
- Changing Types in a List
- Comprehensions involving tuples
- Counting Occurrences Using Comprehension
- Dictionary Comprehensions
- Generator Expressions
- Set Comprehensions
- List Comprehensions
- List destructuring (aka packing and unpacking)
- List slicing (selecting parts of lists)
- Logging
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- Mutable vs Immutable (and Hashable) in Python
- Neo4j and Cypher using Py2Neo
- Non-official Python implementations
- Operator module
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- Pickle data serialisation
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- String representations of class instances: __str__ and __repr__ methods
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- sys
- tempfile NamedTemporaryFile
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- The dis module
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- The os Module
- The pass statement
- The Print Function
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- Unicode and bytes
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- 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 List comprehensions Comprehensions involving tuples
Example
The for clause of a list comprehension can specify more than one variable:
[x + y for x, y in [(1, 2), (3, 4), (5, 6)]]
# Out: [3, 7, 11]
[x + y for x, y in zip([1, 3, 5], [2, 4, 6])]
# Out: [3, 7, 11]
This is just like regular for loops:
for x, y in [(1,2), (3,4), (5,6)]:
print(x+y)
# 3
# 7
# 11
Note however, if the expression that begins the comprehension is a tuple then it must be parenthesized:
[x, y for x, y in [(1, 2), (3, 4), (5, 6)]]
# SyntaxError: invalid syntax
[(x, y) for x, y in [(1, 2), (3, 4), (5, 6)]]
# Out: [(1, 2), (3, 4), (5, 6)]
