mirror of
https://github.com/DMOJ/online-judge.git
synced 2024-11-25 16:32:37 +08:00
83 lines
3.6 KiB
Python
83 lines
3.6 KiB
Python
from collections import namedtuple
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from django.conf import settings
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from django.db import connection
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from judge.models import Submission
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from judge.timezone import from_database_time
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PP_WEIGHT_TABLE = [pow(settings.DMOJ_PP_STEP, i) for i in range(settings.DMOJ_PP_ENTRIES)]
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PPBreakdown = namedtuple('PPBreakdown', 'points weight scaled_points problem_name problem_code '
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'sub_id sub_date sub_points sub_total sub_result_class '
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'sub_short_status sub_long_status sub_lang')
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def get_pp_breakdown(user, start=0, end=settings.DMOJ_PP_ENTRIES):
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join_type = 'STRAIGHT_JOIN' if connection.vendor == 'mysql' else 'INNER JOIN'
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with connection.cursor() as cursor:
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cursor.execute(f"""
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SELECT max_points_table.problem_code,
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max_points_table.problem_name,
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max_points_table.max_points,
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judge_submission.id,
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judge_submission.date,
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judge_submission.case_points,
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judge_submission.case_total,
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judge_submission.result,
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judge_language.short_name,
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judge_language.key
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FROM (
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SELECT judge_problem.id problem_id,
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judge_problem.name problem_name,
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judge_problem.code problem_code,
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MAX(judge_submission.points) AS max_points
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FROM judge_problem
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INNER JOIN judge_submission ON (judge_problem.id = judge_submission.problem_id)
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WHERE (judge_problem.is_public AND
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NOT judge_problem.is_organization_private AND
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judge_submission.points IS NOT NULL AND
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judge_submission.user_id = %s)
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GROUP BY judge_problem.id
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HAVING MAX(judge_submission.points) > 0.0
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) AS max_points_table
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{join_type} judge_submission ON (
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judge_submission.problem_id = max_points_table.problem_id AND
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judge_submission.points = max_points_table.max_points AND
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judge_submission.user_id = %s
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)
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{join_type} judge_language ON (judge_submission.language_id = judge_language.id)
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GROUP BY max_points_table.problem_id
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ORDER BY max_points DESC, judge_submission.date DESC
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LIMIT %s OFFSET %s
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""", (user.id, user.id, end - start + 1, start))
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data = cursor.fetchall()
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breakdown = []
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for weight, contrib in zip(PP_WEIGHT_TABLE[start:end], data):
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code, name, points, id, date, case_points, case_total, result, lang_short_name, lang_key = contrib
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# Replicates a lot of the logic usually done on Submission objects
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lang_short_display_name = lang_short_name or lang_key
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result_class = Submission.result_class_from_code(result, case_points, case_total)
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long_status = Submission.USER_DISPLAY_CODES.get(result, '')
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breakdown.append(PPBreakdown(
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points=points,
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weight=weight * 100,
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scaled_points=points * weight,
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problem_name=name,
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problem_code=code,
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sub_id=id,
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sub_date=from_database_time(date),
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sub_points=case_points,
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sub_total=case_total,
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sub_short_status=result,
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sub_long_status=long_status,
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sub_result_class=result_class,
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sub_lang=lang_short_display_name,
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))
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has_more = end < min(len(PP_WEIGHT_TABLE), start + len(data))
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return breakdown, has_more
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