Sample
pyint-cf52dd5e3ab4-I01
Remove comments and docstrings
Scores
| Method | Score | Scale |
|---|---|---|
| Posnett | 0 | 0–1; higher is more readable |
| Dorn | 0.094 | 0–1; higher is more readable |
| Mi | 0.328 | 0–1; higher is more readable |
| LLOC | 97 | Logical lines; fewer is more readable |
| DeepSeek V4 Pro | 15.67 | 0–20; mean of three runs |
| GPT-6.1 Sol | 16 | 0–20; mean of three runs |
| BTTF | 0.298 | 0–1; higher is more readable |
Views
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Source regions
Feature contributions
Feature contributions
| Feature | Value | Contribution (log-odds) |
|---|---|---|
| Halstead volumeHow much symbolic information the code contains. It combines the total number of operators and values with the number of distinct ones. | 7270.56 | −239.928 |
| Source linesThe number of non-empty source lines. | 196 | +78.4 |
| Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value. | 4.249 | −6.374 |
Intercept 8.87 + feature contributions = -159.032 (log-odds).
Score = sigmoid(-159.032) = 0.
Feature contributions
| Feature | Value | Contribution (log-odds) |
|---|---|---|
| Indentation frequencyHow rapidly indentation changes from line to line. | 195 | +6.008 |
| Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code. | 197 | −5.939 |
| Number layout frequencyHow rapidly the number of numeric values per line changes through the code. | 195 | −4.054 |
| Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom. | 195.909 | +2.329 |
| Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right. | 0 | −0.804 |
| Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *. | 0.082 | +0.148 |
| Identifier layout (horizontal)How rapidly the visual pattern of identifier characters changes from left to right. It measures spatial frequency, not the meaning of the names. | 86.985 | −0.019 |
Intercept 0.07 + feature contributions = -2.262 (log-odds).
Score = sigmoid(-2.262) = 0.094.
| Score | 0.328 |
|---|
| Score | 97 |
|---|
Run 1
The code is well-structured with a clear class definition, organized imports, and logical method grouping. Properties are concise and follow a consistent pattern. Nesting is generally minimal—only slices, filters, and random read fallbacks create moderate depth but remain manageable. Intent is explicit through descriptive method names, docstrings (albeit empty in places), and clean separation of concerns. Action granularity is strong: list comprehensions for field metadata, dedicated helper methods like _make_feature, and one main operation per line in most cases. Reading flow is natural—properties are grouped, methods are short, and error handling is localized. Minor deductions stem from inconsistent docstring completeness, some dense list comprehensions in fields/field_types, and slightly verbose repetitive patterns in field_widths/precisions. The spatial_filter setter has a few branches but remains readable. Overall, the code clearly expresses its purpose with structured, maintainable logic.
Run 2
The code is moderately readable, with clear class and method structure. Each method is short and focused on a single responsibility, and property names are descriptive. However, there are some areas that reduce clarity: several methods rely on low-level ctypes/capi calls with minimal abstraction, making intent less obvious. The __getitem__ method has an unusual triple-commented empty block, and _make_feature contains an implicit fallback loop with a swallowed exception, which could confuse readers. The list comprehensions in fields, field_types, etc., are compact but obscure the underlying operations. Overall, the code is organized and reasonably concise, but heavy reliance on opaque external calls and some non-obvious control flow keeps it from being highly readable.
Run 3
The code is generally well-structured and readable. It uses clear class organization with logical property definitions and method grouping. Nesting is minimal, with only small conditional blocks in indexing and spatial filter methods. Intent is mostly clear through descriptive method and property names like 'num_feat', 'geom_type', and 'test_capability'. Code length is appropriate for a GDAL wrapper, though some list comprehensions in field properties are slightly dense. Action granularity is good - most lines perform one operation, though the spatial filter tuple handling could be split further. Reading flow is natural, with properties grouped logically and docstrings explaining non-obvious sections. The main readability improvement would be consistent docstring content (some are empty) and slightly better error message context. The nested conditions in __getitem__ and _make_feature are acceptable but could be flattened with early returns.
Run 1
Code Structure: A cohesive Layer class separates feature access, metadata properties, spatial filtering, and utility methods logically. Nesting: Mostly shallow, with modest branching in indexing, feature lookup, and filter validation. Clarity of intent: Descriptive method names and explicit exceptions communicate purpose, but absent docstrings, abbreviated pointer/API names, and unexplained exception handling obscure some GDAL-specific behavior. Code length: Methods are concise, although repetitive metadata accessors and excessive blank lines inflate the presentation. Action granularity: Most statements perform one action; nested API calls and comprehensions occasionally combine several operations. Reading flow: Initialization followed by protocol methods, properties, and helpers is natural, but whitespace clutter and inconsistent use of ptr versus _ptr slightly disrupt readability.
Run 2
Code Structure: The class is logically organized into initialization, collection behavior, metadata properties, filtering, and utility methods. Nesting: Most methods are flat, with only modest nesting in feature lookup and filter validation. Clarity of intent: Descriptive method names and explicit error messages communicate purpose, but missing docstrings, abbreviated internal names, and low-level GDAL calls leave pointer ownership and lookup behavior unclear. Code length: Methods are concise, although excessive blank lines and repeated field-definition expressions add clutter. Action granularity: Statements generally perform one action per line; nested API calls and comprehensions occasionally combine several operations. Reading flow: The ordering is natural and consistent, but irregular whitespace, mixed use of ptr and _ptr, and silently caught exceptions interrupt comprehension.
Run 3
Code Structure: The class is logically organized into initialization, collection behavior, metadata properties, filtering, and utility methods. Nesting: Most methods are flat; indexing, feature retrieval, and filter validation have manageable nesting. Clarity of intent: Descriptive method names and explicit exceptions communicate purpose, but missing documentation, abbreviated native API names, and silent exception handling obscure some details. Code length: Methods are concise, although excessive blank lines and repeated field-definition lookups add visual bulk. Action granularity: Statements generally perform one action per line; nested API calls and comprehensions occasionally combine several operations. Reading flow: Consistent formatting and predictable method boundaries support natural reading, but whitespace clutter and inconsistent use of self.ptr versus self._ptr introduce minor distractions.