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Questions and Answers
What is the primary advantage of using modules in Python?
What is the primary advantage of using modules in Python?
How should a Python file be saved to be considered a module?
How should a Python file be saved to be considered a module?
What does a package in Python contain?
What does a package in Python contain?
Which command is NOT a valid way to import a module in Python?
Which command is NOT a valid way to import a module in Python?
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What will the command 'from module_name import *' do?
What will the command 'from module_name import *' do?
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Which built-in module can be used to check the current working directory?
Which built-in module can be used to check the current working directory?
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In Python, what typical file extension indicates a module?
In Python, what typical file extension indicates a module?
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What is the relationship between a module and a script in Python?
What is the relationship between a module and a script in Python?
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What does the platform module in Python provide?
What does the platform module in Python provide?
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What does the function platform.platform() return?
What does the function platform.platform() return?
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What is the purpose of the platform.machine() function?
What is the purpose of the platform.machine() function?
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What does the platform.processor() function return?
What does the platform.processor() function return?
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What does the platform.system() function do?
What does the platform.system() function do?
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What information is provided by platform.version()?
What information is provided by platform.version()?
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What does the platform.python_implementation() function return?
What does the platform.python_implementation() function return?
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What is returned by the platform.python_version_tuple() function?
What is returned by the platform.python_version_tuple() function?
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What type of information does platform.uname() return?
What type of information does platform.uname() return?
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What does the platform.python_build() function return?
What does the platform.python_build() function return?
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What type of information does platform.architecture() provide?
What type of information does platform.architecture() provide?
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Study Notes
Modules and Packages
- Modules are Python files (.py extension) containing functions, classes, and variables organized for logical relationships.
- Packages are collections of modules and sub-modules, providing a structured way to organize code.
- Modularity in OOPs is implemented through modules, allowing related operations to be grouped together into a single file for easy reuse and access.
Module Creation and Usage
-
Creating a module:
- A module is like any other Python file, named after the file it's saved as.
- For example, a module named
series.py
could contain functions likefactorial()
,fibonacci()
, andexponential_series()
.
-
Importing a module:
- Loading a module into another file or module is called importing.
- It allows the use of the module's functions, classes, and variables.
- There are three primary ways to import a module:
-
import statement
: Imports the entire module. -
from import statement
: Imports specific functions, classes, or variables from a module. -
from import * statement
: Imports all objects from a module (not recommended in larger projects).
-
Importing a Complete Module
- The
import
statement imports the entire module. - Example:
import series
This line imports theseries
module, allowing access to its contents usingseries.function_name()
.
Platform Module in Python
- The
platform
module provides information about the system on which the program is running. - The module provides functions to retrieve information about the device, OS, node, OS version, Python version, etc.
- The
platform
module is useful for checking compatibility and hardware specifications.
platform.platform()
Function
- Returns a detailed string describing the platform, including OS name, release, version, and identifiers.
- Example:
-
Windows-10-10.0.19041-SP0
(on a Windows 10 system)
-
platform.machine()
Function
- Returns the machine type (architecture).
- Example:
-
x86_64
(for a 64-bit architecture)
-
platform.processor()
Function
- Returns the name of the processor.
- If the information is not available, it may return an empty string.
- Example:
-
Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
-
platform.system()
Function
- Returns the name of the operating system.
- Example:
-
Windows
-
Linux
-
Darwin
(for macOS)
-
platform.version()
Function
- Returns the version information of the current operating system.
- Example:
-
10.0.19041
(for Windows 10)
-
platform.python_implementation()
Function
- Returns the name of the Python implementation being used.
- Example:
-
CPython
-
PyPy
-
IronPython
-
platform.python_version_tuple()
Function
- Returns the current Python version as a tuple, allowing access to major, minor, and patch versions.
- Example:
-
('3', '9', '7')
(for Python version 3.9.7)
-
platform.uname()
Function
- Returns a tuple storing information about the system, node, release, version, machine, and processor.
- Example:
-
uname_result(system='Windows', node='sag_', release='11', version='10.0.22631', machine='AMD64')
-
platform.python_build()
Function
- Returns a tuple storing information about the Python build date and build number as strings.
- Example:
-
('tags/v3.12.6:a4a2d2b', 'Sep 6 2024 20:11:23')
-
platform.architecture()
Function
- Returns a tuple storing information about the bit architecture and linkage format.
- The bit architecture specifies the processor's number of bits.
- The linkage format defines how names are referenced within the program.
Additional Notes
- Import the
platform
module before using its functions. - The functions might return empty strings if the information is not available.
- Use the
platform
module to gain insights into the environment your program is running in. - The module is useful for compatibility checks, hardware-specific code, and debugging.
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Description
Test your knowledge on Python modules and packages with this quiz! Explore how to create and import modules, and understand the significance of modularity in object-oriented programming. Perfect for Python enthusiasts looking to deepen their understanding of code organization.