Auto PR: fix/buggy_data_structures #62
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WalkthroughIntroduces new module buggy_data_structures.py with utility functions for serialization/deserialization (JSON, pickle), deep dict merging, grouping items by property, and flattening nested lists. Adds CustomClass for demos. Includes inline demo/test usage illustrating typical success and error scenarios. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
actor Caller
participant Utils as buggy_data_structures.py
participant JSON as json
participant Pickle as pickle
rect rgba(230,245,255,0.6)
Note over Caller,Utils: Serialization flow
Caller->>Utils: serialize_data(data, format_type)
alt format_type == "json"
Utils->>JSON: dumps(data, default=str)
JSON-->>Utils: json_str or error
else format_type == "pickle"
Utils->>Pickle: dumps(data)
Pickle-->>Utils: bytes or error
else unsupported
Utils-->>Caller: raise ValueError (unsupported format)
end
Utils-->>Caller: result or ValueError (wrapped)
end
rect rgba(240,255,230,0.6)
Note over Caller,Utils: Deserialization flow
Caller->>Utils: deserialize_data(data, format_type)
alt format_type == "json"
Utils->>JSON: loads(data)
JSON-->>Utils: obj or JSONDecodeError
else format_type == "pickle"
Utils->>Pickle: loads(data)
Pickle-->>Utils: obj or UnpicklingError
else unsupported
Utils-->>Caller: raise ValueError (unsupported format)
end
Utils-->>Caller: object or ValueError ("Deserialization failure")
end
sequenceDiagram
autonumber
actor Caller
participant Utils as buggy_data_structures.py
rect rgba(255,245,230,0.6)
Note over Caller,Utils: Deep merge (non-mutating)
Caller->>Utils: deep_merge_dicts(dict1, dict2)
Utils->>Utils: deepcopy(dict1)
Utils->>Utils: recursive merge of dict2 into copy
Utils-->>Caller: merged_dict
end
rect rgba(255,240,250,0.6)
Note over Caller,Utils: Grouping and Flattening
Caller->>Utils: group_by_property(items, prop, default)
Utils-->>Caller: {group_key: [items]}
Caller->>Utils: flatten_nested_list(nested, max_depth?)
Utils-->>Caller: flattened_sequence
end
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Pre-merge checks (1 passed, 1 warning, 1 inconclusive)❌ Failed checks (1 warning, 1 inconclusive)
✅ Passed checks (1 passed)
Poem
✨ Finishing Touches
🧪 Generate unit tests
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Actionable comments posted: 2
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
buggy_data_structures.py (1)
70-117: Eliminate import-time side effects; move demos under a main guard and tighten catches.Library modules shouldn’t print or run code on import. Guard demos and avoid blind
except Exception.-# Test improved scenarios -class CustomClass: - def __init__(self, value): - self.value = value - - def __str__(self): - return f"CustomClass({self.value})" - -# This will now work with JSON using default=str -custom_obj = CustomClass(42) -try: - serialized = serialize_data(custom_obj, "json") - print(f"Serialized: {serialized}") - - # Test with dict containing custom object - complex_data = {"obj": custom_obj, "number": 123} - serialized_complex = serialize_data(complex_data, "json") - print(f"Complex serialized: {serialized_complex}") -except Exception as e: - print(f"Serialization error: {e}") - -# This won't modify original dict -original_dict = {"a": 1, "nested": {"x": 1}} -other_dict = {"b": 2, "nested": {"y": 2}} -merged = deep_merge_dicts(original_dict, other_dict) -print(f"Original unchanged: {original_dict}") -print(f"Merged result: {merged}") - -# This will handle missing property gracefully -items = [{"name": "Alice", "age": 30}, {"name": "Bob"}] -try: - grouped = group_by_property(items, "age", "unknown_age") - print(f"Grouped with defaults: {grouped}") -except Exception as e: - print(f"Grouping error: {e}") - -# This will handle deep nesting properly -nested = [1, [2, [3, 4]], 5] -print(f"Fully flattened: {flatten_nested_list(nested)}") -print(f"Limited depth flattened: {flatten_nested_list(nested, max_depth=2)}") - -# Test error handling -try: - bad_json = '{"incomplete": ' - deserialize_data(bad_json, "json") -except ValueError as e: - print(f"Deserialization error handled: {e}") +if __name__ == "__main__": + # Test improved scenarios + class CustomClass: + def __init__(self, value): + self.value = value + def __str__(self): + return f"CustomClass({self.value})" + + # This will now work with JSON using default=str + custom_obj = CustomClass(42) + try: + serialized = serialize_data(custom_obj, "json") + print(f"Serialized: {serialized}") + # Test with dict containing custom object + complex_data = {"obj": custom_obj, "number": 123} + serialized_complex = serialize_data(complex_data, "json") + print(f"Complex serialized: {serialized_complex}") + except ValueError as e: + print(f"Serialization error: {e}") + + # This won't modify original dict + original_dict = {"a": 1, "nested": {"x": 1}} + other_dict = {"b": 2, "nested": {"y": 2}} + merged = deep_merge_dicts(original_dict, other_dict) + print(f"Original unchanged: {original_dict}") + print(f"Merged result: {merged}") + + # This will handle missing property gracefully + items = [{"name": "Alice", "age": 30}, {"name": "Bob"}] + grouped = group_by_property(items, "age", "unknown_age") + print(f"Grouped with defaults: {grouped}") + + # This will handle deep nesting properly + nested = [1, [2, [3, 4]], 5] + print(f"Fully flattened: {flatten_nested_list(nested)}") + print(f"Limited depth flattened: {flatten_nested_list(nested, max_depth=2)}") + + # Test error handling + try: + bad_json = '{"incomplete": ' + deserialize_data(bad_json, "json") + except ValueError as e: + print(f"Deserialization error handled: {e}")
🧹 Nitpick comments (3)
buggy_data_structures.py (3)
6-16: Chain exceptions and include PicklingError; use highest pickle protocol.Wrap PicklingError and preserve the original traceback; also prefer HIGHEST_PROTOCOL.
@@ - elif format_type == "pickle": - return pickle.dumps(data) + elif format_type == "pickle": + return pickle.dumps(data, protocol=pickle.HIGHEST_PROTOCOL) @@ - except (TypeError, ValueError) as e: - raise ValueError(f"Serialization failed: {e}") + except (TypeError, ValueError, pickle.PicklingError) as e: + raise ValueError(f"Serialization failed: {e}") from e
30-38: Avoid sharing references from dict2 during merge.If value is a dict/list (or any mutable), the merged result will alias dict2’s objects. Deepcopy on assignment to keep the result independent.
@@ - else: - result[key] = value + else: + result[key] = copy.deepcopy(value)
40-52: Handle unhashable group keys.Grouping by a property that is a list/dict raises TypeError when used as a dict key. Fallback to default group.
@@ - groups[group_key].append(item) - except (KeyError, AttributeError): + groups[group_key].append(item) + except (KeyError, AttributeError, TypeError): groups[default_group].append(item)
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📒 Files selected for processing (1)
buggy_data_structures.py(1 hunks)
🧰 Additional context used
🪛 Ruff (0.12.2)
buggy_data_structures.py
14-14: Abstract raise to an inner function
(TRY301)
14-14: Avoid specifying long messages outside the exception class
(TRY003)
16-16: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
16-16: Avoid specifying long messages outside the exception class
(TRY003)
24-24: pickle and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue
(S301)
26-26: Abstract raise to an inner function
(TRY301)
26-26: Avoid specifying long messages outside the exception class
(TRY003)
28-28: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
28-28: Avoid specifying long messages outside the exception class
(TRY003)
88-88: Do not catch blind exception: Exception
(BLE001)
103-103: Do not catch blind exception: Exception
(BLE001)
| def deserialize_data(data, format_type): | ||
| # Bug fixed: add error handling for corrupted data | ||
| try: | ||
| if format_type == "json": | ||
| return json.loads(data) | ||
| elif format_type == "pickle": | ||
| return pickle.loads(data) | ||
| else: | ||
| raise ValueError(f"Unsupported format: {format_type}") | ||
| except (json.JSONDecodeError, pickle.UnpicklingError, ValueError) as e: | ||
| raise ValueError(f"Deserialization failed: {e}") |
There was a problem hiding this comment.
Block insecure pickle deserialization by default; improve error chaining and type checks.
Unpickling untrusted data is RCE-prone. Require an explicit flag and tighten exception handling.
-def deserialize_data(data, format_type):
+def deserialize_data(data, format_type, *, allow_pickle=False):
@@
- elif format_type == "pickle":
- return pickle.loads(data)
+ elif format_type == "pickle":
+ if not allow_pickle:
+ raise ValueError("Pickle deserialization is disabled by default for security.")
+ if not isinstance(data, (bytes, bytearray, memoryview)):
+ raise TypeError("Pickle deserialization requires a bytes-like object.")
+ return pickle.loads(data)
@@
- except (json.JSONDecodeError, pickle.UnpicklingError, ValueError) as e:
- raise ValueError(f"Deserialization failed: {e}")
+ except (json.JSONDecodeError, UnicodeDecodeError, pickle.UnpicklingError, AttributeError, ValueError, TypeError) as e:
+ raise ValueError(f"Deserialization failed: {e}") from e📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def deserialize_data(data, format_type): | |
| # Bug fixed: add error handling for corrupted data | |
| try: | |
| if format_type == "json": | |
| return json.loads(data) | |
| elif format_type == "pickle": | |
| return pickle.loads(data) | |
| else: | |
| raise ValueError(f"Unsupported format: {format_type}") | |
| except (json.JSONDecodeError, pickle.UnpicklingError, ValueError) as e: | |
| raise ValueError(f"Deserialization failed: {e}") | |
| def deserialize_data(data, format_type, *, allow_pickle=False): | |
| # Bug fixed: add error handling for corrupted data | |
| try: | |
| if format_type == "json": | |
| return json.loads(data) | |
| elif format_type == "pickle": | |
| if not allow_pickle: | |
| raise ValueError("Pickle deserialization is disabled by default for security.") | |
| if not isinstance(data, (bytes, bytearray, memoryview)): | |
| raise TypeError("Pickle deserialization requires a bytes-like object.") | |
| return pickle.loads(data) | |
| else: | |
| raise ValueError(f"Unsupported format: {format_type}") | |
| except (json.JSONDecodeError, UnicodeDecodeError, pickle.UnpicklingError, AttributeError, ValueError, TypeError) as e: | |
| raise ValueError(f"Deserialization failed: {e}") from e |
🧰 Tools
🪛 Ruff (0.12.2)
24-24: pickle and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue
(S301)
26-26: Abstract raise to an inner function
(TRY301)
26-26: Avoid specifying long messages outside the exception class
(TRY003)
28-28: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
28-28: Avoid specifying long messages outside the exception class
(TRY003)
| def flatten_nested_list(nested_list, max_depth=None): | ||
| # Bug fixed: handle deeply nested structures and non-list items | ||
| def _flatten_recursive(item, current_depth=0): | ||
| if max_depth is not None and current_depth >= max_depth: | ||
| return [item] | ||
|
|
||
| if isinstance(item, (list, tuple)): | ||
| flattened = [] | ||
| for sub_item in item: | ||
| flattened.extend(_flatten_recursive(sub_item, current_depth + 1)) | ||
| return flattened | ||
| else: | ||
| return [item] | ||
|
|
||
| return _flatten_recursive(nested_list) | ||
|
|
There was a problem hiding this comment.
max_depth=0 returns an extra wrapper; fix flatten semantics.
Current implementation returns [nested_list] when max_depth=0. Adjust recursion depth and return shape.
-def flatten_nested_list(nested_list, max_depth=None):
- # Bug fixed: handle deeply nested structures and non-list items
- def _flatten_recursive(item, current_depth=0):
- if max_depth is not None and current_depth >= max_depth:
- return [item]
-
- if isinstance(item, (list, tuple)):
- flattened = []
- for sub_item in item:
- flattened.extend(_flatten_recursive(sub_item, current_depth + 1))
- return flattened
- else:
- return [item]
-
- return _flatten_recursive(nested_list)
+def flatten_nested_list(nested_list, max_depth=None):
+ # Flattens nested sequences up to max_depth levels; max_depth=0 returns a shallow copy.
+ def _flatten_recursive(item, current_depth=-1):
+ if isinstance(item, (list, tuple)) and (max_depth is None or current_depth < max_depth):
+ for sub in item:
+ yield from _flatten_recursive(sub, current_depth + 1)
+ else:
+ yield item
+ if max_depth == 0 and isinstance(nested_list, (list, tuple)):
+ return list(nested_list)
+ return list(_flatten_recursive(nested_list))📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def flatten_nested_list(nested_list, max_depth=None): | |
| # Bug fixed: handle deeply nested structures and non-list items | |
| def _flatten_recursive(item, current_depth=0): | |
| if max_depth is not None and current_depth >= max_depth: | |
| return [item] | |
| if isinstance(item, (list, tuple)): | |
| flattened = [] | |
| for sub_item in item: | |
| flattened.extend(_flatten_recursive(sub_item, current_depth + 1)) | |
| return flattened | |
| else: | |
| return [item] | |
| return _flatten_recursive(nested_list) | |
| def flatten_nested_list(nested_list, max_depth=None): | |
| # Flattens nested sequences up to max_depth levels; max_depth=0 returns a shallow copy. | |
| def _flatten_recursive(item, current_depth=-1): | |
| if isinstance(item, (list, tuple)) and (max_depth is None or current_depth < max_depth): | |
| for sub in item: | |
| yield from _flatten_recursive(sub, current_depth + 1) | |
| else: | |
| yield item | |
| if max_depth == 0 and isinstance(nested_list, (list, tuple)): | |
| return list(nested_list) | |
| return list(_flatten_recursive(nested_list)) |
Automatic draft PR for fix/buggy_data_structures (generated).
Summary by CodeRabbit
New Features
Documentation
Tests