mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-12-30 19:39:09 +00:00
consolidated datraset.py into datas.py
removed unessasary time import in data.py
added missing import to processing.py
Former-commit-id: f74cfb3ae3
This commit is contained in:
parent
30641e43d8
commit
b3ab9156db
@ -1,7 +1,6 @@
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import requests
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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):
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api_key= apikey
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@ -55,7 +54,7 @@ def get_metrics_data_formatted(apikey, competition):
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out = {}
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for i in x:
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try:
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out[int(i)] = d.get_team_metrics_data(apikey, competition, int(i))
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out[int(i)] = get_team_metrics_data(apikey, competition, int(i))
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except:
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pass
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return out
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@ -127,3 +126,76 @@ def unkeyify_2l(layered_dict):
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add.sort(key = lambda x: x[0])
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out[i] = list(map(lambda x: x[1], add))
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return out
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def get_previous_time(apikey):
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previous_time = get_analysis_flags(apikey, "latest_update")
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if previous_time == None:
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set_analysis_flags(apikey, "latest_update", 0)
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previous_time = 0
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else:
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previous_time = previous_time["latest_update"]
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return previous_time
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def set_current_time(apikey, current_time):
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set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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def load_match(apikey, competition):
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return get_match_data_formatted(apikey, competition)
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def load_metric(apikey, competition, match, group_name, metrics):
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group = {}
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for team in match[group_name]:
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db_data = get_team_metrics_data(apikey, competition, team)
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if get_team_metrics_data(apikey, competition, team) == None:
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elo = {"score": metrics["elo"]["score"]}
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gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
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ts = {"mu": metrics["ts"]["mu"], "sigm+a": metrics["ts"]["sigma"]}
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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else:
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metrics = db_data["metrics"]
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elo = metrics["elo"]
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gl2 = metrics["gl2"]
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ts = metrics["ts"]
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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return group
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def load_pit(apikey, competition):
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return get_pit_data_formatted(apikey, competition)
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def push_match(apikey, competition, results):
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for team in results:
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push_team_tests_data(apikey, competition, team, results[team])
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def push_metric(apikey, competition, metric):
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for team in metric:
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push_team_metrics_data(apikey, competition, team, metric[team])
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def push_pit(apikey, competition, pit):
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for variable in pit:
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push_team_pit_data(apikey, competition, variable, pit[variable])
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@ -1,74 +0,0 @@
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import data as d
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def get_previous_time(apikey):
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previous_time = d.get_analysis_flags(apikey, "latest_update")
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if previous_time == None:
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d.set_analysis_flags(apikey, "latest_update", 0)
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previous_time = 0
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else:
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previous_time = previous_time["latest_update"]
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return previous_time
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def set_current_time(apikey, current_time):
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d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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def load_match(apikey, competition):
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return d.get_match_data_formatted(apikey, competition)
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def load_metric(apikey, competition, match, group_name, metrics):
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group = {}
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for team in match[group_name]:
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db_data = d.get_team_metrics_data(apikey, competition, team)
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if d.get_team_metrics_data(apikey, competition, team) == None:
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elo = {"score": metrics["elo"]["score"]}
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gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
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ts = {"mu": metrics["ts"]["mu"], "sigm+a": metrics["ts"]["sigma"]}
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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else:
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metrics = db_data["metrics"]
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elo = metrics["elo"]
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gl2 = metrics["gl2"]
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ts = metrics["ts"]
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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return group
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def load_pit(apikey, competition):
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return d.get_pit_data_formatted(apikey, competition)
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def push_match(apikey, competition, results):
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for team in results:
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d.push_team_tests_data(apikey, competition, team, results[team])
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def push_metric(apikey, competition, metric):
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for team in metric:
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d.push_team_metrics_data(apikey, competition, team, metric[team])
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def push_pit(apikey, competition, pit):
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for variable in pit:
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d.push_team_pit_data(apikey, competition, variable, pit[variable])
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@ -1,7 +1,7 @@
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import numpy as np
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from tra_analysis import Analysis as an
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from dataset import push_metric
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from dataset import push_metric, load_metric
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from data import pull_new_tba_matches
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import signal
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@ -2,7 +2,6 @@
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block_cipher = None
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a = Analysis(['superscript.py'],
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pathex=['/workspaces/tra-data-analysis/src'],
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binaries=[],
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