Spaces:
Build error
Build error
File size: 11,206 Bytes
51ff9e5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 |
import math
def total_byte_entropy_stats(python_code):
# Count the occurrence of each byte (character for simplicity)
byte_counts = {}
for byte in python_code.encode('utf-8'):
byte_counts[byte] = byte_counts.get(byte, 0) + 1
total_bytes = sum(byte_counts.values())
entropy = -sum(
(count / total_bytes) * math.log2(count / total_bytes)
for count in byte_counts.values()
)
return {'total_byte_entropy': entropy}
def average_nulls_stats(tree, num_lines):
total_nulls = 0
nulls_per_line = {} # Dictionary to count nulls per line
def traverse(node):
nonlocal total_nulls
if node.type == 'null_literal':
total_nulls += 1
line_number = node.start_point[0] # Get line number
if line_number in nulls_per_line:
nulls_per_line[line_number] += 1
else:
nulls_per_line[line_number] = 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
# Calculate average nulls per line
avg_nulls = total_nulls / num_lines if num_lines > 0 else 0
# Calculate max nulls on any line
max_nulls_on_any_line = max(nulls_per_line.values()) if nulls_per_line else 0
return {
'avg_nulls': avg_nulls,
'total_nulls': total_nulls,
'max_nulls': max_nulls_on_any_line,
'has_nulls': 1 if total_nulls > 0 else 0,
}
def arithmetic_operations_stats(tree, num_lines):
# Dictionary to hold counts of each arithmetic operation
op_counts = {'+': 0, '-': 0, '*': 0, '/': 0, '%': 0}
total_ops = 0
# Function to traverse the AST and update operation counts
def traverse(node):
nonlocal total_ops
if node.type == 'binary_expression' or node.type == 'update_expression':
for child in node.children:
if child.type == 'operator':
op = child.text.decode('utf8')
if op in op_counts:
op_counts[op] += 1
total_ops += 1
else:
for child in node.children:
traverse(child)
traverse(tree.root_node)
return {
'total_arithmetic_operations': total_ops,
'avg_arithmetic_operations': total_ops / num_lines,
}
def numbers_floats_stats(tree, num_lines):
total_numbers = 0
total_floats = 0
def traverse(node):
nonlocal total_numbers, total_floats
if node.type in ['integer_literal', 'decimal_literal']:
total_numbers += 1
if (
'.' in node.text.decode('utf8')
or 'e' in node.text.decode('utf8').lower()
):
total_floats += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
return {'total_numbers': total_numbers, 'total_floats': total_floats}
def code_stats(python_code):
lines = python_code.strip().split('\n')
total_line_length = sum(len(line) for line in lines)
max_line_length = max(len(line) for line in lines)
return {
'total_line_length': total_line_length,
'max_line_length': max_line_length,
'avg_characters': total_line_length / len(lines),
}
def assertions_stats(tree, num_lines):
total_assertions = 0
def traverse(node):
nonlocal total_assertions
if node.type == 'assert_statement':
total_assertions += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
return {
'total_assertions': total_assertions,
'total_has_assertions': 1 if total_assertions > 0 else 0,
}
def class_instances_stats(tree, num_lines):
total_class_instances = 0
def traverse(node):
nonlocal total_class_instances
if node.type == 'object_creation_expression':
total_class_instances += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
return {'total_class_instances': total_class_instances}
def has_execeptions(tree, num_lines):
total_has_exceptions = 0
def traverse(node):
nonlocal total_has_exceptions
if node.type == 'try_statement':
total_has_exceptions += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
return {'total_has_exceptions': 1 if total_has_exceptions > 0 else 0}
def distinct_methods_stats(tree, num_lines):
method_names = set()
total_nodes = 0
def traverse(node):
nonlocal total_nodes
if node.type == 'method_declaration':
for child in node.children:
if child.type == 'identifier':
method_names.add(child.text.decode('utf8'))
break
total_nodes += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
total_distinct_methods = len(method_names)
total_method_ratio = (
total_distinct_methods / (total_nodes - total_distinct_methods)
if total_nodes > total_distinct_methods
else 0
)
return {
'total_distinct_methods': total_distinct_methods,
'total_method_ratio': total_method_ratio,
}
def loops_stats(tree, num_lines):
"""
Calculate the average number of loops.
"""
total_loops = 0
def traverse(node):
nonlocal total_loops
if node.type in ['for_statement', 'while_statement', 'do_statement']:
total_loops += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
avg_loops = total_loops / num_lines
return {'avg_loops': avg_loops}
def branches_stats(tree, num_lines):
"""
Calculate the average number of branches (conditional statements).
"""
total_branches = 0
def traverse(node):
nonlocal total_branches
if node.type in ['if_statement', 'switch_statement']:
total_branches += 1
for child in node.children:
traverse(child)
traverse(tree.root_node)
# Assuming each branch is its own, this might need refinement based on definition
avg_branches = total_branches / num_lines
return {'avg_branches': avg_branches}
def string_stats(tree, num_lines):
string_literals = []
# Function to traverse the AST and collect string literals
def traverse(node):
if node.type == 'string_literal':
# Extracting the string literal, excluding the quotation marks
literal_text = node.text.decode('utf8')[1:-1]
string_literals.append(literal_text)
for child in node.children:
traverse(child)
traverse(tree.root_node)
# Calculate the average string length
total_length = sum(len(s) for s in string_literals)
avg_length = total_length / num_lines
return {'avg_str_length': avg_length}
def identifier_stats(tree, num_lines):
root_node = tree.root_node
identifier_counts = {} # Dictionary to count occurrences of each identifier
total_nodes = 0 # Counter for all nodes
# Function to recursively count identifiers and all nodes, gathering their stats
def count(node):
nonlocal identifier_counts, total_nodes
iden_count = 0
max_length = 0
total_nodes += 1 # Increment total nodes for every node visited
if node.type == 'identifier':
identifier = node.text.decode('utf8') # Assuming UTF-8 encoding
iden_count += 1
identifier_counts[identifier] = identifier_counts.get(identifier, 0) + 1
iden_length = len(identifier)
if iden_length > max_length:
max_length = iden_length
for child in node.children:
child_count, child_max_length = count(child)
iden_count += child_count
if child_max_length > max_length:
max_length = child_max_length
return iden_count, max_length
total_identifiers, max_identifier_length = count(root_node)
total_unique_identifiers = len(identifier_counts)
total_identifier_length = sum(len(k) * v for k, v in identifier_counts.items())
avg_identifier_length = total_identifier_length / num_lines
# Calculate the identifier ratio as total identifiers over total nodes
identifier_ratio = total_identifiers / total_nodes if total_nodes > 0 else 0
return {
'total_identifiers': total_identifiers,
'total_identifier_length': total_identifier_length,
'max_identifier_length': max_identifier_length,
'avg_identifier_length': avg_identifier_length,
'total_unique_identifiers': total_unique_identifiers,
'total_identifier_ratio': identifier_ratio, # Include the new ratio in the returned dictionary
'total_nodes': total_nodes, # Include total node count for reference or further calculations
}
def compute_regression(results):
components = {
'total_line_length': -0.0001,
'max_line_length': -0.0021,
'total_identifiers': 0.0076,
'total_identifier_length': -0.0004,
'max_identifier_length': -0.0067,
'avg_identifier_length': -0.005,
'avg_arithmetic_operations': 0.0225,
'avg_branches': 0.9886,
'avg_loops': 0.1572,
'total_assertions': 0.0119,
'total_has_assertions': -0.0147,
'avg_characters': 0.1242,
'total_class_instances': -0.043,
'total_distinct_methods': -0.0127,
'avg_str_length': 0.0026,
'total_has_exceptions': 0.1206,
'total_unique_identifiers': -0.019,
'max_nulls': -0.0712,
'total_numbers': -0.0078,
'avg_nulls': 0.1444,
'total_identifier_ratio': 0.334,
'total_method_ratio': 0.0406,
'total_floats': -0.0174,
'total_byte_entropy': -0.3917,
}
test_score = 0
for component in components:
test_score += components[component] * results[component]
test_score += 5.7501
return test_score
def compute_readability(python_code):
# Create parser and set up language
import tree_sitter_python
from tree_sitter import Language, Parser
parser = Parser(Language(tree_sitter_python.language()))
results = code_stats(python_code)
num_lines = len(python_code.strip().split('\n'))
results.update(total_byte_entropy_stats(python_code))
tree = parser.parse(bytes(python_code, 'utf8'))
results.update(identifier_stats(tree, num_lines))
results.update(loops_stats(tree, num_lines))
results.update(branches_stats(tree, num_lines))
results.update(distinct_methods_stats(tree, num_lines))
results.update(has_execeptions(tree, num_lines))
results.update(class_instances_stats(tree, num_lines))
results.update(assertions_stats(tree, num_lines))
results.update(numbers_floats_stats(tree, num_lines))
results.update(average_nulls_stats(tree, num_lines))
results.update(arithmetic_operations_stats(tree, num_lines))
results.update(string_stats(tree, num_lines))
score = compute_regression(results)
return score
|