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119 lines
3.8 KiB
119 lines
3.8 KiB
import pymongo, json
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# dbprep
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fsroot = '/autograder/source/'
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datasets = ['congress', 'bills']
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db = pymongo.MongoClient('mongodb://127.0.0.1')['test']
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def postproc_str(data : str): # relaxed str matching
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import re
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return re.sub(r'[\s|_]', '', data.lower())
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def comparator(a, b):
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cmp = lambda x, y: 1 if x < y else -1 if x > y else 0
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try:
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return cmp(a, b)
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except Exception as e:
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from collections.abc import Iterable
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def itcmp(a: Iterable, b: Iterable):
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if len(a) < len(b):
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return -1
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elif len(a) == len(b):
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for aa, bb in zip(a, b):
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cmp = comparator(aa, bb)
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if cmp != 0:
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return cmp
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else: return 1
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return 0
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match (a, b):
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case (dict(), dict()):
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return itcmp([*a.keys(), *a.values()], [*b.keys(), *b.values()])
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case (Iterable(), Iterable()):
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return itcmp(a, b)
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case _ if type(a) == type(b):
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return cmp(f'{a}', f'{b}')
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case _:
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return cmp(hash(type(a)), hash(type(b)))
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def postproc_iter(data):
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from collections.abc import Iterable
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from functools import cmp_to_key
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try:
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match data:
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case str():
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return postproc_str(data)
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case dict():
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return { postproc_iter(k):postproc_iter(v) for k, v in data.items() }
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case Iterable(): # flatten, remove order and empty iterables
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res = type(data)(
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sorted(
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[postproc_iter(d) for d in data
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if not isinstance(d, Iterable) or d]
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, key = cmp_to_key(comparator))
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)
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return res[0] if len(res) == 1 else res
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case _: # primitives
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return data
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except Exception as e: # fail proof
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print(e)
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return data
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def evaluate(query : str):
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import re
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query = re.sub(r'(\$?[\d\w_]+)\s*:', r'"\1" :', query)
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query = re.sub(r'[\r|\n]|.\s*pretty\s*\(\s*\)', '', query).strip()
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if query.endswith(';'): query = query[:-1]
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return postproc_iter(list(eval(query))) if query else None
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for d in datasets:
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with open(fsroot + d + '.json', encoding = 'utf-8') as f:
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db[d].insert_many(json.load(f))
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from solution import sols
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answers = [evaluate(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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ans = evaluate(q)
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if ans == 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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print('ans: ', ans, '\nsol: ', answers[i])
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except Exception as e:
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feedback += 'Runtime Error.\n'
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print (e)
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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': grade * 100 / n_queries,
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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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