James McCool
commited on
Commit
·
a31482b
1
Parent(s):
9d65b2e
Refine database queries to restrict 'Team_count' to a maximum of 2 for valid showdown lineups
Browse files- database_queries.py +7 -7
database_queries.py
CHANGED
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@@ -246,18 +246,18 @@ def init_DK_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
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| 246 |
# Combine all player conditions with $or
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| 247 |
if query_conditions:
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| 248 |
filter_query = {'$or': query_conditions}
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| 249 |
-
cursor1 = collection.find(filter_query, {'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 250 |
-
cursor2 = collection.find(filter_query, {'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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| 251 |
else:
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| 252 |
-
cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 253 |
-
cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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| 254 |
raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
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| 255 |
else:
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| 256 |
-
cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 257 |
-
cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
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else:
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-
cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1}}).sort(prio_var, -1).limit(lineup_num)
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raw_display = pd.DataFrame(list(cursor))
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raw_display = raw_display.drop_duplicates(subset=['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'])
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| 246 |
# Combine all player conditions with $or
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| 247 |
if query_conditions:
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| 248 |
filter_query = {'$or': query_conditions}
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| 249 |
+
cursor1 = collection.find(filter_query, {'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 250 |
+
cursor2 = collection.find(filter_query, {'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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| 251 |
else:
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| 252 |
+
cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 253 |
+
cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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| 254 |
raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
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else:
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| 256 |
+
cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
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| 257 |
+
cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
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raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
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else:
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+
cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}}, {'Team_count': {'$gte': 1, '$lte': 2}}).sort(prio_var, -1).limit(lineup_num)
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raw_display = pd.DataFrame(list(cursor))
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raw_display = raw_display.drop_duplicates(subset=['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5'])
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