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71 lines
2.1 KiB
71 lines
2.1 KiB
import neo4j, json
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# dbprep
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fsroot = '/autograder/source/'
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datasets = ['Neo4J_dataset']
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db = neo4j.GraphDatabase.driver('bolt://localhost:7687', auth = ('neo4j', '4Sfz541Lm')).session()
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def evaluate(query : str):
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query = query.strip()
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return db.run(query).data() if query else None
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while True:
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try:
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db.run('RETURN 0')
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break
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except:
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continue
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for d in datasets:
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with open(fsroot + d + '.txt', encoding = 'utf-8') as f:
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db.run(f.read())
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from solution import sols
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answers = [evaluate(s) if type(s) is str else tuple(evaluate(k) for k in s) for s in sols ]
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# grading
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from os import listdir
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from importlib.util import module_from_spec, spec_from_file_location
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subroot = '/autograder/submission/'
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feedback = ''
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submissions = [subroot + f for f in listdir(subroot) if f.strip().lower().endswith('.py')]
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grade = 0
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n_queries = len(sols)
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if submissions:
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submission = submissions[0]
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for i in range(n_queries):
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feedback += f'Query {i + 1}: '
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try:
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spec = spec_from_file_location('curr', submission)
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module = module_from_spec(spec)
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spec.loader.exec_module(module)
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q = getattr(module, f'query{i + 1}')()
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def eq(a: list, b):
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if a is None: return False
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if type(b) is tuple:
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return any(eq(a, bb) for bb in b)
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if len(a) != len(b): return False
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return all(aa == bb for aa, bb in zip(a, b))
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if eq(evaluate(q), answers[i]):
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grade += 1
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feedback += 'Correct.\n'
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else:
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feedback += 'Wrong Answer.\n'
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except Exception:
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feedback += 'Runtime Error.\n'
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else:
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feedback += 'No python file in submission.\n'
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# output
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results = {
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'output': feedback,
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'score': round(grade * 100 / n_queries, 1),
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'max_score': 100,
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}
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with open('/autograder/results/results.json', 'w') as res:
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json.dump(results, res)
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