mirror of
https://github.com/karma-riuk/crab.git
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68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
from dataclasses import dataclass, field
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from typing import Dict, List
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import json
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@dataclass
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class FileData:
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path: str
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content: str = "" # Not sure about this, maybe we should just keep the path and extract the contents dynamically (boh)
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@dataclass
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class Metadata:
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repo: str # the name of the repo, with style XXX/YYY
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pr_number: int
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merge_commit_sha: str # to checkout for the tests
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commented_files : Dict[str, str] # comment -> filename
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commented_files_coverages: Dict[str, Dict[str, float]] = field(default_factory=dict) # filename -> jacoco-report -> coverage
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successful: bool = True
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build_system: str = ""
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reason_for_failure: str = ""
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last_cmd_error_msg: str = ""
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@dataclass
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class DatasetEntry:
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metadata: Metadata
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files: Dict[str, FileData] # filename -> file data, files before the PR (before the first PR commits)
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diffs_before: Dict[str, str] # filename -> diff, diffs between the opening of the PR and the comment
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comments: List[str]
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diffs_after: Dict[str, str] # filename -> diff, changes after the comment
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@dataclass
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class Dataset:
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entries: List[DatasetEntry] = field(default_factory=list)
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def __len__(self) -> int:
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return sum(1 for entry in self.entries if entry.metadata.successful)
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def to_json(self, filename: str):
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"""Serialize the dataset to a JSON file"""
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with open(filename, "w", encoding="utf-8") as f:
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json.dump(self, f, default=lambda o: o.__dict__, indent=4)
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@staticmethod
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def from_json(filename: str, keep_still_in_progress: bool = False) -> "Dataset":
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with open(filename) as f:
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data = json.load(f)
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entries = []
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for entry_data in data["entries"]:
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metadata_data = entry_data["metadata"]
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metadata = Metadata(**metadata_data)
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if not keep_still_in_progress and metadata.reason_for_failure == "Was still being processed":
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continue
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files = {
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fname: FileData(**fdata) for fname, fdata in entry_data["files"].items()
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}
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entry = DatasetEntry(
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metadata=metadata,
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files=files,
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diffs_before=entry_data["diffs_before"],
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comments=entry_data["comments"],
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diffs_after=entry_data["diffs_after"]
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)
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entries.append(entry)
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return Dataset(entries=entries)
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