def cotes_combine_reduit_all_sites(*matches):
"""
Calcule les cotes combinées de matches dont on connait les cotes sur plusieurs
bookmakers
"""
sites = set(matches[0]["odds"].keys())
for match in matches:
sites = sites.intersection(match["odds"].keys())
combine_dict = [{
"date": max([match["date"] for match in matches]),
"odds": {}
} for _ in range(6)]
for i in range(6):
for site in sites:
combine_dict[i]["odds"][site] = cotes_combine_optimise(
[match["odds"][site] for match in matches])[0][i]
return combine_dict
def best_matches_combine2(site,
minimum_odd,
bet,
sport,
minimum_odd_selection,
date_max=None,
time_max=None,
date_min=None,
time_min=None):
nb_matches = 2
all_odds = filter_dict_dates(sb.ODDS[sport], date_max, time_max, date_min,
time_min)
all_odds = filter_dict_minimum_odd(all_odds, minimum_odd_selection, site)
odds_combine_opt = [{} for _ in range(6)]
nb_combine = binomial(len(all_odds), nb_matches)
sb.PROGRESS = 0
combis = cotes_combine_optimise([[1 for _ in range(3)]
for i in range(nb_matches)])[1]
print(combis)
def compute_all_odds_combine_optimise(nb_combine, combine,
odds_combine_opt):
sb.PROGRESS += 100 / nb_combine
try:
cotes_combination = cotes_combine_reduit_all_sites(
*[match[1] for match in combine])
for i in range(6):
odds_combine_opt[i][" / ".join([match[0] for match in combine
])] = cotes_combination[i]
# combis[i] = cotes_combination[i][1]
except KeyError:
pass
ThreadPool(4).map(
lambda x: compute_all_odds_combine_optimise(nb_combine, x,
odds_combine_opt),
combinations(all_odds.items(), nb_matches))
sb.PROGRESS = 0
odds_function = get_best_odds(False)
profit_function = get_profit(bet, False)
criteria = lambda odds_to_check, i: all(odd >= minimum_odd
for odd in odds_to_check)
for i, combination in enumerate(combis):
sb.ALL_ODDS_COMBINE = odds_combine_opt[i]
# display_function = lambda odds_to_check, i: mises_combine_optimise(odds_to_check, combination, bet, minimum_odd, True)
# result_function = lambda odds_to_check, i: mises_combine_optimise(odds_to_check, combination, bet, minimum_odd, False)
display_function = lambda best_overall_odds, best_rank: mises2(
best_overall_odds, bet, best_rank, True)
result_function = lambda best_overall_odds, best_rank: mises2(
best_overall_odds, bet, best_rank, False)
best_match_base(odds_function,
profit_function,
criteria,
display_function,
result_function,
site,
sport,
date_max,
time_max,
date_min,
time_min,
True,
nb_matches,
combine_opt=True)
def best_match_stakes_to_bet2(stakes,
nb_matches=2,
sport="football",
date_max=None,
time_max=None,
identical_stakes=False):
second_sites = {stake[1] for stake in stakes}
main_sites = sb.BOOKMAKERS
all_odds = get_matches_with_best_trj(sport, 20)
all_odds = filter_dict_dates(all_odds, date_max, time_max)
best_profit = -sum(stake[0] for stake in stakes)
n = 5 #get_nb_outcomes(sport) ** nb_matches
nb_stakes = len(stakes)
all_odds_combine = [{} for _ in range(6)]
combis = list(combinations(all_odds.items(), nb_matches))
nb_combis = len(combis)
best_combine = None
best_bets = None
main_site_odds = []
main_sites_distribution = []
sb.PROGRESS = 0
list_combinations = cotes_combine_optimise([[1 for _ in range(3)]
for i in range(nb_matches)])[1]
for k in range(6):
for i, combine in enumerate(combis):
sb.PROGRESS += 100 / nb_combis
match_combine = " / ".join([match[0] for match in combine])
cotes_combination = cotes_combine_reduit_all_sites(
*[match[1] for match in combine])
# print(cotes_combination[k])
all_odds_combine[k][match_combine] = cotes_combination[k]
for main0 in main_sites:
try:
main_sites_distribution = [main0 for _ in range(n)]
main_site_odds = copy.deepcopy(
all_odds_combine[k][match_combine]["odds"][main0])
break
except KeyError:
pass
for main in main_sites[:i] + main_sites[i + 1:]:
try:
potential_odds = all_odds_combine[k][match_combine][
"odds"][main]
for j, odd in enumerate(potential_odds):
if odd > main_site_odds[j]:
main_site_odds[j] = odd
main_sites_distribution[j] = main
except KeyError:
pass
second_odds = {
second_site:
all_odds_combine[k][match_combine]["odds"][second_site]
for second_site in second_sites
if second_site in all_odds_combine[k][match_combine]["odds"]
}
if not second_odds:
continue
dict_combine_odds = copy.deepcopy(second_odds)
for perm in permutations(range(n), nb_stakes):
valid_perm = True
defined_second_sites = [[perm[j], stake[0], stake[1]]
for j, stake in enumerate(stakes)]
for j, stake in enumerate(stakes):
if dict_combine_odds[defined_second_sites[j][2]][
defined_second_sites[j][0]] < stake[2]:
valid_perm = False
break
if not valid_perm:
if identical_stakes:
break
continue
defined_bets_temp = defined_bets(main_site_odds,
dict_combine_odds,
main_sites_distribution,
defined_second_sites)
profit = defined_bets_temp[0] - np.sum(defined_bets_temp[1])
if profit > best_profit:
best_profit = profit
best_combine = combine
best_bets = defined_bets_temp
best_combination = k
if identical_stakes:
break
if best_combine:
best_match_combine = " / ".join([match[0] for match in best_combine])
odds_best_match = copy.deepcopy(
all_odds_combine[best_combination][best_match_combine])
all_sites = main_sites + list(second_sites)
for site in all_odds_combine[best_combination][best_match_combine][
"odds"]:
if site not in all_sites:
del odds_best_match["odds"][site]
print(best_match_combine)
pprint(odds_best_match, compact=1)
print("Plus-value =", round(best_profit, 2))
print("Gain référence =", round(best_bets[0], 2))
print("Somme des mises =", round(np.sum(best_bets[1]), 2))
afficher_mises_combine(
[x[0] for x in best_combine],
best_bets[2],
best_bets[1],
all_odds_combine[best_combination][best_match_combine]["odds"],
sport,
combinaisons=convert_indices_to_opponents(
list_combinations[best_combination],
[x[0] for x in best_combine], sport))
else:
print("No match found")