PEP 8
E256164
PEP 8 is the official Python style guide that defines conventions for writing readable, consistent Python code.
All labels observed (3)
| Label | Occurrences |
|---|---|
| PEP 8 canonical | 3 |
| PEP 8 style guidelines | 1 |
| PEP 8 – Style Guide for Python Code | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2321061 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PEP 8 Context triple: [PEP 572, relatedPEP, PEP 8]
-
A.
PEP 622
PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
-
B.
PEP 634
PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
-
C.
PEP 695
PEP 695 is a Python Enhancement Proposal that introduces a new, more concise syntax for type parameter declarations to improve the language’s support for generics and static typing.
-
D.
PEP 13
PEP 13 is the Python Enhancement Proposal that defines the process and rules for selecting and operating the Python Steering Council, the core governance body of the Python project.
-
E.
Python Enhancement Proposals
Python Enhancement Proposals (PEPs) are the formal design documents that propose, specify, and document new features, processes, and standards for the Python programming language.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PEP 8 Target entity description: PEP 8 is the official Python style guide that defines conventions for writing readable, consistent Python code.
-
A.
PEP 1 – PEP Purpose and Guidelines
PEP 1 – PEP Purpose and Guidelines is the foundational Python Enhancement Proposal that defines the goals, structure, and workflow for all other PEPs in the Python development process.
-
B.
PEP 635
PEP 635 is a Python Enhancement Proposal that provides a detailed rationale and motivation for the structural pattern matching feature introduced in Python 3.10.
-
C.
PEP 622
PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
-
D.
PEP 634
PEP 634 is the Python Enhancement Proposal that formally specifies the semantics of structural pattern matching introduced in Python 3.10.
-
E.
PEP 695
PEP 695 is a Python Enhancement Proposal that introduces a new, more concise syntax for type parameter declarations to improve the language’s support for generics and static typing.
- F. None of above. chosen
Statements (55)
| Predicate | Object |
|---|---|
| instanceOf |
Python Enhancement Proposal
ⓘ
style guide ⓘ |
| appliesTo | Python source code ⓘ |
| associatedWith | Python Software Foundation ⓘ |
| defines | coding style conventions for Python ⓘ |
| discourages |
extraneous whitespace before a colon
ⓘ
extraneous whitespace before a comma ⓘ extraneous whitespace before a semicolon ⓘ extraneous whitespace inside parentheses, brackets, or braces ⓘ multiple statements on one line ⓘ overly complex expressions ⓘ tab characters for indentation ⓘ trailing whitespace at the end of lines ⓘ using backslash for line continuation when parentheses can be used ⓘ using single-letter variable names except for counters ⓘ using wildcard imports ⓘ |
| influences | many Python projects' coding standards ⓘ |
| language | Python ⓘ |
| maintainer | Python core developers ⓘ |
| purpose |
to promote consistent Python code
ⓘ
to promote readable Python code ⓘ |
| recommends |
4 spaces per indentation level
ⓘ
UTF-8 as the default source encoding ⓘ grouping imports in standard library, third-party, and local order ⓘ imports at the top of the file ⓘ limiting the use of lambda expressions to simple functions ⓘ maximum line length of 72 characters for docstrings and comments ⓘ maximum line length of 79 characters for code ⓘ one import per line ⓘ using == and != for value comparisons ⓘ using CapWords (CamelCase) for class names ⓘ using English for comments and docstrings ⓘ using UPPER_CASE_WITH_UNDERSCORES for constants ⓘ using absolute imports when possible ⓘ using blank lines to separate logical sections of code ⓘ using blank lines to separate top-level function and class definitions ⓘ using cls as the first argument to class methods ⓘ using docstrings to document public modules, classes, methods, and functions ⓘ using explicit exception types instead of bare except ⓘ using explicit parentheses in complex boolean expressions ⓘ using if x is not None instead of if not x when checking for None ⓘ using is and is not for comparisons to None ⓘ using list comprehensions and generator expressions where appropriate ⓘ using lowercase_with_underscores for function names ⓘ using lowercase_with_underscores for variable names ⓘ using one space after colons in dictionaries ⓘ using one space after commas ⓘ using self as the first argument to instance methods ⓘ using spaces around binary operators ⓘ using with statements for resource management ⓘ |
| relatedTo |
Python code consistency
ⓘ
Python code readability ⓘ |
| status | Active ⓘ |
| title |
PEP 8 – Style Guide for Python Code
ⓘ
linked to:
PEP 8
|
| usedBy | Python developers worldwide ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: PEP 8 Description of subject: PEP 8 is the official Python style guide that defines conventions for writing readable, consistent Python code.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: PEP 8