mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-11-09 22:44:44 +00:00
pull some data from API, fix some datatype compats
Former-commit-id: 03ec0dd8fd
This commit is contained in:
Dev Singh
parent
af74a69579
commit
b4c9ef22b6
@ -8,76 +8,130 @@ from interface import stderr, stdout, INF, ERR
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config_path = "config.json"
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sample_json = """{
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"persistent":{
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"key":{
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"database":"",
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"tba":""
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},
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"config-preference":"local",
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"synchronize-config":false
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},
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"variable":{
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sample_json = """
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{
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"persistent":{
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"key":{
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"database":"",
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"tba":"",
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"tra":{
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"CLIENT_ID":"",
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"CLIENT_SECRET":""
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}
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},
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"config-preference":"local",
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"synchronize-config":false
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},
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"variable":{
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"max-threads":0.5,
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"team":"",
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"event-delay":false,
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"loop-delay":0,
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"reportable":true,
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"teams":[
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"max-threads":0.5,
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"competition":"",
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"team":"",
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"event-delay":false,
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"loop-delay":0,
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"reportable":true,
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"teams":[],
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"modules":{
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"match":{
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"tests":{
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"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
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}
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},
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"metric":{
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"tests":{
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"elo":{
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"score":1500,
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"N":400,
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"K":24
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},
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"gl2":{
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"score":1500,
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"rd":250,
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"vol":0.06
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},
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"ts":{
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"mu":25,
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"sigma":8.33
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}
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}
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},
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"pit":{
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"tests":{
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"wheel-mechanism":true,
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"low-balls":true,
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"high-balls":true,
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"wheel-success":true,
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"strategic-focus":true,
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"climb-mechanism":true,
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"attitude":true
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}
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}
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}
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}
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}"""
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],
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"modules":{
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"match":{
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"tests":{
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"balls-blocked":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-collected":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-lower-teleop":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-lower-auto":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-started":[
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"basic_stats",
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"historical_analyss",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-upper-teleop":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-upper-auto":[
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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]
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}
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},
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"metric":{
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"tests":{
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"elo":{
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"score":1500,
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"N":400,
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"K":24
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},
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"gl2":{
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"score":1500,
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"rd":250,
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"vol":0.06
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},
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"ts":{
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"mu":25,
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"sigma":8.33
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}
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}
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},
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"pit":{
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"tests":{
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"wheel-mechanism":true,
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"low-balls":true,
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"high-balls":true,
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"wheel-success":true,
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"strategic-focus":true,
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"climb-mechanism":true,
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"attitude":true
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}
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}
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}
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}
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}
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"""
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class ConfigurationError (Exception):
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code = None
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@ -139,23 +193,17 @@ def parse_config_variable(send, config):
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raise ConfigurationError("unable to start threads", 200)
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send(stdout, INF, "successfully initialized " + str(alloc_processes) + " threads")
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try:
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competition = config["variable"]["competition"]
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except:
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raise ConfigurationError("variable/competition field is invalid or missing", 101)
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try:
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modules = config["variable"]["modules"]
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except:
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raise ConfigurationError("variable/modules field is invalid or missing", 102)
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if competition == None or competition == "":
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raise ConfigurationError("variable/competition field is empty", 105)
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if modules == None:
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raise ConfigurationError("variable/modules field is empty", 106)
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send(stdout, INF, "found and loaded competition, match, metrics, pit from config")
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return exec_threads, competition, modules
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return exec_threads, modules
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def resolve_config_conflicts(send, client, config, preference, sync):
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@ -1,4 +1,6 @@
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import requests
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import pull
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import pandas as pd
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def pull_new_tba_matches(apikey, competition, cutoff):
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api_key= apikey
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@ -13,7 +15,7 @@ def get_team_match_data(client, competition, team_num):
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db = client.data_scouting
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mdata = db.matchdata
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out = {}
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for i in mdata.find({"competition" : competition, "team_scouted": team_num}):
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for i in mdata.find({"competition" : competition, "team_scouted": str(team_num)}):
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out[i['match']] = i['data']
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return pd.DataFrame(out)
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@ -21,7 +23,7 @@ def get_team_pit_data(client, competition, team_num):
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db = client.data_scouting
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mdata = db.pitdata
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out = {}
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return mdata.find_one({"competition" : competition, "team_scouted": team_num})["data"]
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return mdata.find_one({"competition" : competition, "team_scouted": str(team_num)})["data"]
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def get_team_metrics_data(client, competition, team_num):
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db = client.data_processing
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@ -29,25 +31,21 @@ def get_team_metrics_data(client, competition, team_num):
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return mdata.find_one({"competition" : competition, "team": team_num})
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def get_match_data_formatted(client, competition):
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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teams_at_comp = pull.get_teams_at_competition(competition)
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out = {}
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for i in x:
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for team in teams_at_comp:
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try:
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out[int(i)] = unkeyify_2l(get_team_match_data(client, competition, int(i)).transpose().to_dict())
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out[int(team)] = unkeyify_2l(get_team_match_data(client, competition, team).transpose().to_dict())
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except:
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pass
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return out
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def get_metrics_data_formatted(client, competition):
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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teams_at_comp = pull.get_teams_at_competition(competition)
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out = {}
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for i in x:
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for team in teams_at_comp:
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try:
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out[int(i)] = get_team_metrics_data(client, competition, int(i))
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out[int(team)] = get_team_metrics_data(client, competition, int(team))
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except:
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pass
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return out
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5
src/cli/exceptions.py
Normal file
5
src/cli/exceptions.py
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@ -0,0 +1,5 @@
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class APIError(Exception):
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code = None
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def __init__(self, str, endpoint):
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super().__init__(str)
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self.endpoint = endpoint
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66
src/cli/pull.py
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66
src/cli/pull.py
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@ -0,0 +1,66 @@
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import requests
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import json
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from exceptions import APIError
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def load_config(path):
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with open(path, "r") as f:
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return json.load(f)
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url = "https://titanscouting.epochml.org"
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config_tra = load_config("config.json")
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trakey = config_tra['persistent']['key']['tra']
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def get_team_competition():
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endpoint = '/api/fetchTeamCompetition'
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params = {
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"CLIENT_ID": trakey['CLIENT_ID'],
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"CLIENT_SECRET": trakey['CLIENT_SECRET']
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}
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response = requests.request("GET", url + endpoint, params=params)
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json = response.json()
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if json['success']:
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return json['competition']
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else:
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raise APIError(json, endpoint)
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def get_team():
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endpoint = '/api/fetchTeamCompetition'
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params = {
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"CLIENT_ID": trakey['CLIENT_ID'],
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"CLIENT_SECRET": trakey['CLIENT_SECRET']
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}
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response = requests.request("GET", url + endpoint, params=params)
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json = response.json()
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if json['success']:
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return json['team']
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else:
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raise APIError(json, endpoint)
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def get_team_match_data(competition, team_num):
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endpoint = '/api/fetchAllTeamMatchData'
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params = {
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"competition": competition,
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"teamScouted": team_num,
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"CLIENT_ID": trakey['CLIENT_ID'],
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"CLIENT_SECRET": trakey['CLIENT_SECRET']
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}
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response = requests.request("GET", url + endpoint, params=params)
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json = response.json()
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if json['success']:
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return json['data'][team_num]
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else:
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raise APIError(json, endpoint)
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def get_teams_at_competition(competition):
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endpoint = '/api/fetchAllTeamNicknamesAtCompetition'
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params = {
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"competition": competition,
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"CLIENT_ID": trakey['CLIENT_ID'],
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"CLIENT_SECRET": trakey['CLIENT_SECRET']
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}
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response = requests.request("GET", url + endpoint, params=params)
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json = response.json()
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if json['success']:
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return list(json['data'].keys())
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else:
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raise APIError(json, endpoint)
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@ -160,7 +160,7 @@ import time
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import traceback
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import warnings
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import zmq
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import pull
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from config import parse_config_persistent, parse_config_variable, resolve_config_conflicts, load_config, save_config, ConfigurationError
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from data import get_previous_time, set_current_time, check_new_database_matches
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from interface import splash, log, ERR, INF, stdout, stderr
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@ -214,8 +214,8 @@ def main(send, verbose = False, profile = False, debug = False):
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config = resolve_config_conflicts(send, client, config, preference, sync)
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exec_threads, competition, config_modules = parse_config_variable(send, config)
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exec_threads, config_modules = parse_config_variable(send, config)
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competition = pull.get_team_competition()
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for m in config_modules:
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if m in modules:
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start = time.time()
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