Python Source Code Item
A Python Source Code Item is a source code item that is composed of Python statements and Python expressions (for Python programming language execution and implementation).
- Context:
- It can typically contain Python syntax elements such as Python variables, Python functions, Python classes, and Python module imports.
- It can typically follow Python coding conventions such as Python indentation rules, Python naming conventions, and Python PEP 8 guidelines.
- It can typically be processed by a Python interpreter to produce Python runtime behavior.
- It can typically utilize Python librarys and Python frameworks to extend its Python functionality.
- It can typically implement various Python programming paradigms including Python object-oriented programming, Python functional programming, and Python procedural programming.
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- It can often include Python comments and Python docstrings to document Python code purpose and Python usage instructions.
- It can often implement Python error handling through Python exception mechanisms like Python try-except blocks.
- It can often use Python data structures such as Python lists, Python dictionarys, Python sets, and Python tuples.
- It can often interact with external systems through Python file operations, Python network communication, and Python database interfaces.
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- It can range from being a Simple Python Source Code Item to being a Complex Python Source Code Item, depending on its Python code complexity.
- It can range from being a Pythonic Python Source Code Item to being a Non-Pythonic Python Source Code Item, depending on its Python idiom adherence.
- It can range from being a Procedural Python Source Code Item to being an Object-Oriented Python Source Code Item, depending on its Python programming paradigm.
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- It can be organized into Python modules, Python packages, and Python librarys for Python code reuse and Python distribution.
- It can be executed in various Python environments including Python interactive shells, Python script execution, and Python web application servers.
- It can be analyzed using Python static analysis tools, Python type checkers, and Python linters for Python code quality assurance.
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- Examples:
- Python Source Code Item Types, such as:
- Python Executable Units, such as:
- Python Program for complete Python application implementation.
- Python Script for Python automation tasks and Python utility operations.
- Python Module containing related Python functions and Python classes.
- Python Code Segments, such as:
- Python Function Definition implementing a specific Python functionality.
- Python Class Definition defining Python object structure and Python behavior.
- Python Method Definition implementing Python object functionality.
- Python Executable Units, such as:
- Python Source Code Item Purposes, such as:
- Python Data Operation Source Code Items, such as:
- Python Web Source Code Items, such as:
- Python Web Framework Code using frameworks like Python Django code or Python Flask code.
- Python API Implementation Code for creating Python web services.
- Python Language Feature Source Code Items, such as:
- Python Advanced Language Feature Codes, such as:
- Python Special Purpose Codes, such as:
- Python Regular Expression Code Segment for Python text pattern matching.
- Python Docstring for Python documentation embedded in code.
- Python Oneliner Program for concise Python task implementation.
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- Python Source Code Item Types, such as:
- Counter-Examples:
- JavaScript Source Code Item, which uses JavaScript syntax and is processed by a JavaScript engine rather than a Python interpreter.
- Java Source Code Item, which follows Java language specification and requires Java compilation rather than Python interpretation.
- R Source Code Item, which implements R programming language semantics for statistical computing rather than Python semantics.
- Scala Source Code Item, which combines object-oriented programming and functional programming in the JVM ecosystem rather than the Python ecosystem.
- See: Python Programming Language, Python-Based Process, Python Interpreter, Python Variable, Python Application Development Framework, Python Program Template, Python Development Environment.
References
2018
- (Horton & Parnin, 2018) ⇒ Eric Horton, and Chris Parnin. (2018). “Gistable: Evaluating the Executability of Python Code Snippets on GitHub.” arXiv preprint arXiv:1808.04919
- ABSTRACT: Software developers create and share code online to demonstrate programming language concepts and programming tasks. Code snippets can be a useful way to explain and demonstrate a programming concept, but may not always be directly executable. A code snippet can contain parse errors, or fail to execute if the environment contains unmet dependencies.
This paper presents an empirical analysis of the executable status of Python code snippets shared through the GitHub gist system, and the ability of developers familiar with software configuration to correctly configure and run them. We find that 75.6% of gists require non-trivial configuration to overcome missing dependencies, configuration files, reliance on a specific operating system, or some other environment configuration. Our study also suggests the natural assumption developers make about resource names when resolving configuration errors is correct less than half the time.
We also present Gistable, a database and extensible framework built on GitHub's gist system, which provides executable code snippets to enable reproducible studies in software engineering. Gistable contains 10,259 code snippets, approximately 5,000 with a Dockerfile to configure and execute them without import error. Gistable is publicly available at this https URL
- ABSTRACT: Software developers create and share code online to demonstrate programming language concepts and programming tasks. Code snippets can be a useful way to explain and demonstrate a programming concept, but may not always be directly executable. A code snippet can contain parse errors, or fail to execute if the environment contains unmet dependencies.