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superscript.py v 0.0.1.002
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@ -3,14 +3,13 @@ import pymongo
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import pandas as pd
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import time
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def pull_new_tba_matches(apikey, competition, cutoff = time_last_upd):
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def pull_new_tba_matches(apikey, competition, cutoff):
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api_key= apikey
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x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth_Key":api_key})
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out = []
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for i in x.json():
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if (i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm"):
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out.append({"match" : i['match_number'], "blue" : list(map(lambda x: int(x[3:]), i['alliances']['blue']['team_keys'])), "red" : list(map(lambda x: int(x[3:]), i['alliances']['red']['team_keys'])), "winner": i["winning_alliance"]})
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time_last_upd = time.time()
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return out
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def get_team_match_data(apikey, competition, team_num):
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@ -22,14 +21,11 @@ def get_team_match_data(apikey, competition, team_num):
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out[i['match']] = i['data']
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return pd.DataFrame(out)
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def get_team_pit_data(apikey, competition, team_num):
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def get_team_metrics_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.pitdata
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out = {}
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for i in mdata.find({"competition" : competition, "team_scouted": team_num}):
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out[i['match']] = i['data']
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return pd.DataFrame(out)
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db = client.data_processing
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mdata = db.team_metrics
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return mdata.find_one({"competition" : competition, "team": team_num})
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def unkeyify_2l(layered_dict):
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out = {}
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@ -3,10 +3,12 @@
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# Notes:
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# setup:
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__version__ = "0.0.1.001"
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__version__ = "0.0.1.002"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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0.0.1.002:
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- started implement of metrics
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0.0.1.001:
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- cleaned up imports
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0.0.1.000:
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@ -59,6 +61,8 @@ from analysis import analysis as an
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import data as d
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import time
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main()
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def main():
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while(True):
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current_time = time.time()
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@ -70,6 +74,7 @@ def main():
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print("loading database keys")
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apikey = an.load_csv("keys.txt")[0][0]
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tbakey = an.load_csv("keys.txt")[1][0]
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print("loaded keys")
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print("loading data")
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@ -79,6 +84,10 @@ def main():
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print("running tests")
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results = simpleloop(data, config)
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print("finished tests")
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print("running metrics")
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metrics = metricsloop(apikey, competition, current_time)
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print("finished metrics")
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print("pushing to database")
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push_to_database(apikey, competition, results, None)
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@ -138,72 +147,8 @@ def push_to_database(apikey, competition, results, metrics):
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d.push_team_tests_data(apikey, competition, team, results[team])
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def metricsloop(group_data, observations, database, tests): # listener based metrics update
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def metricsloop(apikey, competition, timestamp): # listener based metrics update
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pass
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matches = d.pull_new_tba_matches(apikey, competition, timestamp)
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"""
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class database:
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data = {}
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elo_starting_score = 1500
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N = 1500
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K = 32
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gl2_starting_score = 1500
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gl2_starting_rd = 350
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gl2_starting_vol = 0.06
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def __init__(self, team_lookup):
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super().__init__()
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for team in team_lookup:
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elo = elo_starting_score
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gl2 = {"score": gl2_starting_score, "rd": gl2_starting_rd, "vol": gl2_starting_vol}
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ts = Trueskill.Rating()
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data[str(team)] = {"elo": elo, "gl2": gl2, "ts": ts}
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def get_team(self, team):
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return data[team]
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def get_elo(self, team):
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return data[team]["elo"]
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def get_gl2(self, team):
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return data[team]["gl2"]
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def get_ts(self, team):
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return data[team]["ts"]
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def set_team(self, team, ndata):
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data[team] = ndata
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def set_elo(self, team, nelo):
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data[team]["elo"] = nelo
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def set_gl2(self, team, ngl2):
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data[team]["gl2"] = ngl2
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def set_ts(self, team, nts):
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data[team]["ts"] = nts
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def save_database(self, location):
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pickle.dump(data, open(location, "wb"))
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def load_database(self, location):
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data = pickle.load(open(location, "rb"))
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"""
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main()
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return
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