Merge pull request #12 from titanscouting/superscript-v1

Merge current changes to build-superscript

Former-commit-id: 6b4de40c49
This commit is contained in:
Arthur Lu 2021-08-26 15:45:24 -07:00 committed by GitHub
commit f0ef4fea5d
14 changed files with 979 additions and 9 deletions

View File

@ -1,11 +1,11 @@
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
name: Superscript Unit Tests
name: Build Superscript Linux
on:
release:
types: [published, edited]
types: [published, created, edited]
jobs:
generate:
@ -15,3 +15,5 @@ jobs:
steps:
- name: Checkout master
uses: actions/checkout@master
- name: Echo test
run: echo "test"

4
.gitignore vendored
View File

@ -9,6 +9,10 @@
**/tra_analysis/
**/temp/*
**/*.pid
**/profile.*
**/errorlog.txt
/dist/superscript.*
/dist/superscript

View File

@ -1,4 +1,4 @@
set pathtospec="../src/superscript.spec"
set pathtospec="../src/cli/superscript.spec"
set pathtodist="../dist/"
set pathtowork="temp/"

View File

@ -1,4 +1,4 @@
pathtospec="../src/superscript.spec"
pathtospec="../src/cli/superscript.spec"
pathtodist="../dist/"
pathtowork="temp/"

188
src/cli/data.py Normal file
View File

@ -0,0 +1,188 @@
import requests
import pandas as pd
def pull_new_tba_matches(apikey, competition, cutoff):
api_key= apikey
x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth_Key":api_key}, verify=False)
out = []
for i in x.json():
if i["actual_time"] != None and i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm":
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"]})
return out
def get_team_match_data(client, competition, team_num):
db = client.data_scouting
mdata = db.matchdata
out = {}
for i in mdata.find({"competition" : competition, "team_scouted": team_num}):
out[i['match']] = i['data']
return pd.DataFrame(out)
def get_team_pit_data(client, competition, team_num):
db = client.data_scouting
mdata = db.pitdata
out = {}
return mdata.find_one({"competition" : competition, "team_scouted": team_num})["data"]
def get_team_metrics_data(client, competition, team_num):
db = client.data_processing
mdata = db.team_metrics
return mdata.find_one({"competition" : competition, "team": team_num})
def get_match_data_formatted(client, competition):
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = unkeyify_2l(get_team_match_data(client, competition, int(i)).transpose().to_dict())
except:
pass
return out
def get_metrics_data_formatted(client, competition):
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = get_team_metrics_data(client, competition, int(i))
except:
pass
return out
def get_pit_data_formatted(client, competition):
db = client.data_scouting
mdata = db.teamlist
x=mdata.find_one({"competition":competition})
out = {}
for i in x:
try:
out[int(i)] = get_team_pit_data(client, competition, int(i))
except:
pass
return out
def get_pit_variable_data(client, competition):
db = client.data_processing
mdata = db.team_pit
out = {}
return mdata.find()
def get_pit_variable_formatted(client, competition):
temp = get_pit_variable_data(client, competition)
out = {}
for i in temp:
out[i["variable"]] = i["data"]
return out
def push_team_tests_data(client, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "data" : data}, True)
def push_team_metrics_data(client, competition, team_num, data, dbname = "data_processing", colname = "team_metrics"):
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "metrics" : data}, True)
def push_team_pit_data(client, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
db = client[dbname]
mdata = db[colname]
mdata.replace_one({"competition" : competition, "variable": variable}, {"competition" : competition, "variable" : variable, "data" : data}, True)
def get_analysis_flags(client, flag):
db = client.data_processing
mdata = db.flags
return mdata.find_one({flag:{"$exists":True}})
def set_analysis_flags(client, flag, data):
db = client.data_processing
mdata = db.flags
return mdata.replace_one({flag:{"$exists":True}}, data, True)
def unkeyify_2l(layered_dict):
out = {}
for i in layered_dict.keys():
add = []
sortkey = []
for j in layered_dict[i].keys():
add.append([j,layered_dict[i][j]])
add.sort(key = lambda x: x[0])
out[i] = list(map(lambda x: x[1], add))
return out
def get_previous_time(apikey):
previous_time = get_analysis_flags(apikey, "latest_update")
if previous_time == None:
set_analysis_flags(apikey, "latest_update", 0)
previous_time = 0
else:
previous_time = previous_time["latest_update"]
return previous_time
def set_current_time(apikey, current_time):
set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
def load_match(apikey, competition):
return get_match_data_formatted(apikey, competition)
def load_metric(apikey, competition, match, group_name, metrics):
group = {}
for team in match[group_name]:
db_data = get_team_metrics_data(apikey, competition, team)
if db_data == None:
elo = {"score": metrics["elo"]["score"]}
gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
ts = {"mu": metrics["ts"]["mu"], "sigm+a": metrics["ts"]["sigma"]}
group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
else:
metrics = db_data["metrics"]
elo = metrics["elo"]
gl2 = metrics["gl2"]
ts = metrics["ts"]
group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
return group
def load_pit(apikey, competition):
return get_pit_data_formatted(apikey, competition)
def push_match(apikey, competition, results):
for team in results:
push_team_tests_data(apikey, competition, team, results[team])
def push_metric(apikey, competition, metric):
for team in metric:
push_team_metrics_data(apikey, competition, team, metric[team])
def push_pit(apikey, competition, pit):
for variable in pit:
push_team_pit_data(apikey, competition, variable, pit[variable])

44
src/cli/interface.py Normal file
View File

@ -0,0 +1,44 @@
import sys
import time
from os import system, name
import platform
empty_delim = " "
hard_divided_delim = "|"
soft_divided_delim = "|"
l_brack = "["
r_brack = "]"
ERR = "[ERR]"
INF = "[INF]"
stdout = sys.stdout
stderr = sys.stderr
def log(target, level, message, code = 0):
message = time.ctime() + empty_delim + str(level) + l_brack + f"{code:+05}" + r_brack + empty_delim + soft_divided_delim + empty_delim + message
print(message, file = target)
def clear():
if name == "nt":
system("cls")
else:
system("clear")
def splash(version):
def hrule():
print("#"+38*"-"+"#")
def box(s):
temp = "|"
temp += s
temp += (40-len(s)-2)*" "
temp += "|"
print(temp)
hrule()
box(" superscript version: " + version)
box(" os: " + platform.system())
box(" python: " + platform.python_version())
hrule()

194
src/cli/processing.py Normal file
View File

@ -0,0 +1,194 @@
import numpy as np
from tra_analysis import Analysis as an
from data import pull_new_tba_matches, push_metric, load_metric
import signal
def simplestats(data_test):
signal.signal(signal.SIGINT, signal.SIG_IGN)
data = np.array(data_test[0])
data = data[np.isfinite(data)]
ranges = list(range(len(data)))
test = data_test[1]
if test == "basic_stats":
return an.basic_stats(data)
if test == "historical_analysis":
return an.histo_analysis([ranges, data])
if test == "regression_linear":
return an.regression(ranges, data, ['lin'])
if test == "regression_logarithmic":
return an.regression(ranges, data, ['log'])
if test == "regression_exponential":
return an.regression(ranges, data, ['exp'])
if test == "regression_polynomial":
return an.regression(ranges, data, ['ply'])
if test == "regression_sigmoidal":
return an.regression(ranges, data, ['sig'])
def matchloop(client, competition, data, tests, exec_threads):
short_mapping = {"regression_linear": "lin", "regression_logarithmic": "log", "regression_exponential": "exp", "regression_polynomial": "ply", "regression_sigmoidal": "sig"}
class AutoVivification(dict):
def __getitem__(self, item):
try:
return dict.__getitem__(self, item)
except KeyError:
value = self[item] = type(self)()
return value
return_vector = {}
team_filtered = []
variable_filtered = []
variable_data = []
test_filtered = []
result_filtered = []
return_vector = AutoVivification()
for team in data:
for variable in data[team]:
if variable in tests:
for test in tests[variable]:
team_filtered.append(team)
variable_filtered.append(variable)
variable_data.append((data[team][variable], test))
test_filtered.append(test)
result_filtered = exec_threads.map(simplestats, variable_data)
i = 0
result_filtered = list(result_filtered)
for result in result_filtered:
filtered = test_filtered[i]
try:
short = short_mapping[filtered]
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result[short]
except KeyError: # not in mapping
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result
i += 1
return return_vector
def metricloop(tbakey, client, competition, timestamp, metrics): # listener based metrics update
elo_N = metrics["elo"]["N"]
elo_K = metrics["elo"]["K"]
matches = pull_new_tba_matches(tbakey, competition, timestamp)
red = {}
blu = {}
for match in matches:
red = load_metric(client, competition, match, "red", metrics)
blu = load_metric(client, competition, match, "blue", metrics)
elo_red_total = 0
elo_blu_total = 0
gl2_red_score_total = 0
gl2_blu_score_total = 0
gl2_red_rd_total = 0
gl2_blu_rd_total = 0
gl2_red_vol_total = 0
gl2_blu_vol_total = 0
for team in red:
elo_red_total += red[team]["elo"]["score"]
gl2_red_score_total += red[team]["gl2"]["score"]
gl2_red_rd_total += red[team]["gl2"]["rd"]
gl2_red_vol_total += red[team]["gl2"]["vol"]
for team in blu:
elo_blu_total += blu[team]["elo"]["score"]
gl2_blu_score_total += blu[team]["gl2"]["score"]
gl2_blu_rd_total += blu[team]["gl2"]["rd"]
gl2_blu_vol_total += blu[team]["gl2"]["vol"]
red_elo = {"score": elo_red_total / len(red)}
blu_elo = {"score": elo_blu_total / len(blu)}
red_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)}
blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)}
if match["winner"] == "red":
observations = {"red": 1, "blu": 0}
elif match["winner"] == "blue":
observations = {"red": 0, "blu": 1}
else:
observations = {"red": 0.5, "blu": 0.5}
red_elo_delta = an.Metric().elo(red_elo["score"], blu_elo["score"], observations["red"], elo_N, elo_K) - red_elo["score"]
blu_elo_delta = an.Metric().elo(blu_elo["score"], red_elo["score"], observations["blu"], elo_N, elo_K) - blu_elo["score"]
new_red_gl2_score, new_red_gl2_rd, new_red_gl2_vol = an.Metric().glicko2(red_gl2["score"], red_gl2["rd"], red_gl2["vol"], [blu_gl2["score"]], [blu_gl2["rd"]], [observations["red"], observations["blu"]])
new_blu_gl2_score, new_blu_gl2_rd, new_blu_gl2_vol = an.Metric().glicko2(blu_gl2["score"], blu_gl2["rd"], blu_gl2["vol"], [red_gl2["score"]], [red_gl2["rd"]], [observations["blu"], observations["red"]])
red_gl2_delta = {"score": new_red_gl2_score - red_gl2["score"], "rd": new_red_gl2_rd - red_gl2["rd"], "vol": new_red_gl2_vol - red_gl2["vol"]}
blu_gl2_delta = {"score": new_blu_gl2_score - blu_gl2["score"], "rd": new_blu_gl2_rd - blu_gl2["rd"], "vol": new_blu_gl2_vol - blu_gl2["vol"]}
for team in red:
red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
red[team]["gl2"]["score"] = red[team]["gl2"]["score"] + red_gl2_delta["score"]
red[team]["gl2"]["rd"] = red[team]["gl2"]["rd"] + red_gl2_delta["rd"]
red[team]["gl2"]["vol"] = red[team]["gl2"]["vol"] + red_gl2_delta["vol"]
for team in blu:
blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
blu[team]["gl2"]["score"] = blu[team]["gl2"]["score"] + blu_gl2_delta["score"]
blu[team]["gl2"]["rd"] = blu[team]["gl2"]["rd"] + blu_gl2_delta["rd"]
blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
temp_vector = {}
temp_vector.update(red)
temp_vector.update(blu)
push_metric(client, competition, temp_vector)
def pitloop(client, competition, pit, tests):
return_vector = {}
for team in pit:
for variable in pit[team]:
if variable in tests:
if not variable in return_vector:
return_vector[variable] = []
return_vector[variable].append(pit[team][variable])
return return_vector

536
src/cli/superscript.py Normal file
View File

@ -0,0 +1,536 @@
# Titan Robotics Team 2022: Superscript Script
# Written by Arthur Lu, Jacob Levine, and Dev Singh
# Notes:
# setup:
__version__ = "1.0.0"
# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
1.0.0:
- superscript now runs in PEP 3143 compliant well behaved daemon on Linux systems
- linux superscript daemon has integrated websocket output to monitor progress/status remotely
- linux daemon now sends stderr to errorlog.txt
- added verbose option to linux superscript to allow for interactive output
- moved pymongo import to superscript.py
- added profile option to linux superscript to profile runtime of script
0.9.3:
- improved data loading performance by removing redundant PyMongo client creation (120s to 14s)
- passed singular instance of PyMongo client as standin for apikey parameter in all data.py functions
0.9.2:
- removed unessasary imports from data
- minor changes to interface
0.9.1:
- fixed bugs in configuration item loading exception handling
0.9.0:
- moved printing and logging related functions to interface.py (changelog will stay in this file)
- changed function return files for load_config and save_config to standard C values (0 for success, 1 for error)
- added local variables for config location
- moved dataset getting and setting functions to dataset.py (changelog will stay in this file)
- moved matchloop, metricloop, pitloop and helper functions (simplestats) to processing.py
0.8.6:
- added proper main function
0.8.5:
- added more gradeful KeyboardInterrupt exiting
- redirected stderr to errorlog.txt
0.8.4:
- added better error message for missing config.json
- added automatic config.json creation
- added splash text with version and system info
0.8.3:
- updated matchloop with new regression format (requires tra_analysis 3.x)
0.8.2:
- readded while true to main function
- added more thread config options
0.8.1:
- optimized matchloop further by bypassing GIL
0.8.0:
- added multithreading to matchloop
- tweaked user log
0.7.0:
- finished implementing main function
0.6.2:
- integrated get_team_rankings.py as get_team_metrics() function
- integrated visualize_pit.py as graph_pit_histogram() function
0.6.1:
- bug fixes with analysis.Metric() calls
- modified metric functions to use config.json defined default values
0.6.0:
- removed main function
- changed load_config function
- added save_config function
- added load_match function
- renamed simpleloop to matchloop
- moved simplestats function inside matchloop
- renamed load_metrics to load_metric
- renamed metricsloop to metricloop
- split push to database functions amon push_match, push_metric, push_pit
- moved
0.5.2:
- made changes due to refactoring of analysis
0.5.1:
- text fixes
- removed matplotlib requirement
0.5.0:
- improved user interface
0.4.2:
- removed unessasary code
0.4.1:
- fixed bug where X range for regression was determined before sanitization
- better sanitized data
0.4.0:
- fixed spelling issue in __changelog__
- addressed nan bug in regression
- fixed errors on line 335 with metrics calling incorrect key "glicko2"
- fixed errors in metrics computing
0.3.0:
- added analysis to pit data
0.2.1:
- minor stability patches
- implemented db syncing for timestamps
- fixed bugs
0.2.0:
- finalized testing and small fixes
0.1.4:
- finished metrics implement, trueskill is bugged
0.1.3:
- working
0.1.2:
- started implement of metrics
0.1.1:
- cleaned up imports
0.1.0:
- tested working, can push to database
0.0.9:
- tested working
- prints out stats for the time being, will push to database later
0.0.8:
- added data import
- removed tba import
- finished main method
0.0.7:
- added load_config
- optimized simpleloop for readibility
- added __all__ entries
- added simplestats engine
- pending testing
0.0.6:
- fixes
0.0.5:
- imported pickle
- created custom database object
0.0.4:
- fixed simpleloop to actually return a vector
0.0.3:
- added metricsloop which is unfinished
0.0.2:
- added simpleloop which is untested until data is provided
0.0.1:
- created script
- added analysis, numba, numpy imports
"""
__author__ = (
"Arthur Lu <learthurgo@gmail.com>",
"Jacob Levine <jlevine@imsa.edu>",
)
__all__ = [
"load_config",
"save_config",
]
# imports:
import asyncio
import json
import math
from multiprocessing import Pool, freeze_support
import os
import pymongo
import sys
import threading
import time
import warnings
import websockets
from interface import splash, log, ERR, INF, stdout, stderr
from data import get_previous_time, set_current_time, load_match, push_match, load_pit, push_pit
from processing import matchloop, metricloop, pitloop
config_path = "config.json"
sample_json = """{
"max-threads": 0.5,
"team": "",
"competition": "2020ilch",
"key":{
"database":"",
"tba":""
},
"statistics":{
"match":{
"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
},
"metric":{
"elo":{
"score":1500,
"N":400,
"K":24
},
"gl2":{
"score":1500,
"rd":250,
"vol":0.06
},
"ts":{
"mu":25,
"sigma":8.33
}
},
"pit":{
"wheel-mechanism":true,
"low-balls":true,
"high-balls":true,
"wheel-success":true,
"strategic-focus":true,
"climb-mechanism":true,
"attitude":true
}
}
}"""
def main(send, verbose = False, profile = False):
warnings.filterwarnings("ignore")
sys.stderr = open("errorlog.txt", "w")
loop_exit_code = 0
loop_stored_exception = None
if verbose:
splash(__version__)
while True:
try:
loop_start = time.time()
current_time = time.time()
send(stdout, INF, "current time: " + str(current_time))
send(stdout, INF, "loading config at <" + config_path + ">", code = 0)
config = {}
if load_config(config_path, config) == 1:
send(stderr, ERR, "could not find config at <" + config_path + ">, generating blank config and exiting", code = 100)
sys.exit(1)
send(stdout, INF, "found and opened config at <" + config_path + ">", code = 0)
error_flag = False
try:
competition = config["competition"]
except:
send(stderr, ERR, "could not find competition field in config", code = 101)
error_flag = True
try:
match_tests = config["statistics"]["match"]
except:
send(stderr, ERR, "could not find match_tests field in config", code = 102)
error_flag = True
try:
metrics_tests = config["statistics"]["metric"]
except:
send(stderr, ERR, "could not find metrics_tests field in config", code = 103)
error_flag = True
try:
pit_tests = config["statistics"]["pit"]
except:
send(stderr, ERR, "could not find pit_tests field in config", code = 104)
error_flag = True
if error_flag:
sys.exit(1)
error_flag = False
if competition == None or competition == "":
send(stderr, ERR, "competition field in config must not be empty", code = 105)
error_flag = True
if match_tests == None:
send(stderr, ERR, "match_tests field in config must not be empty", code = 106)
error_flag = True
if metrics_tests == None:
send(stderr, ERR, "metrics_tests field in config must not be empty", code = 107)
error_flag = True
if pit_tests == None:
send(stderr, ERR, "pit_tests field in config must not be empty", code = 108)
error_flag = True
if error_flag:
sys.exit(1)
send(stdout, INF, "found and loaded competition, match_tests, metrics_tests, pit_tests from config")
sys_max_threads = os.cpu_count()
try:
cfg_max_threads = config["max-threads"]
except:
send(stderr, ERR, "max-threads field in config must not be empty, refer to documentation for configuration options", code = 109)
sys.exit(1)
if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
alloc_processes = sys_max_threads + cfg_max_threads
elif cfg_max_threads > 0 and cfg_max_threads < 1:
alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
alloc_processes = cfg_max_threads
elif cfg_max_threads == 0:
alloc_processes = sys_max_threads
else:
send(stderr, ERR, "max-threads must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads) + ", but got " + cfg_max_threads, code = 110)
sys.exit(1)
send(stdout, INF, "found and loaded max-threads from config")
send(stdout, INF, "attempting to start " + str(alloc_processes) + " threads")
try:
exec_threads = Pool(processes = alloc_processes)
except Exception as e:
send(stderr, ERR, "unable to start threads", code = 200)
send(stderr, INF, e)
sys.exit(1)
send(stdout, INF, "successfully initialized " + str(alloc_processes) + " threads")
exit_flag = False
try:
apikey = config["key"]["database"]
except:
send(stderr, ERR, "database key field in config must be present", code = 111)
exit_flag = True
try:
tbakey = config["key"]["tba"]
except:
send(stderr, ERR, "tba key field in config must be present", code = 112)
exit_flag = True
if apikey == None or apikey == "":
send(stderr, ERR, "database key field in config must not be empty, please populate the database key")
exit_flag = True
if tbakey == None or tbakey == "":
send(stderr, ERR, "tba key field in config must not be empty, please populate the tba key")
exit_flag = True
if exit_flag:
sys.exit(1)
send(stdout, INF, "found and loaded database and tba keys")
client = pymongo.MongoClient(apikey)
previous_time = get_previous_time(client)
send(stdout, INF, "analysis backtimed to: " + str(previous_time))
start = time.time()
send(stdout, INF, "loading match data")
match_data = load_match(client, competition)
send(stdout, INF, "finished loading match data in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "performing analysis on match data")
results = matchloop(client, competition, match_data, match_tests, exec_threads)
send(stdout, INF, "finished match analysis in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "uploading match results to database")
push_match(client, competition, results)
send(stdout, INF, "finished uploading match results in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "performing analysis on team metrics")
results = metricloop(tbakey, client, competition, current_time, metrics_tests)
send(stdout, INF, "finished metric analysis and pushed to database in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "loading pit data")
pit_data = load_pit(client, competition)
send(stdout, INF, "finished loading pit data in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "performing analysis on pit data")
results = pitloop(client, competition, pit_data, pit_tests)
send(stdout, INF, "finished pit analysis in " + str(time.time() - start) + " seconds")
start = time.time()
send(stdout, INF, "uploading pit results to database")
push_pit(client, competition, results)
send(stdout, INF, "finished uploading pit results in " + str(time.time() - start) + " seconds")
client.close()
set_current_time(client, current_time)
send(stdout, INF, "finished all tests in " + str(time.time() - loop_start) + " seconds, looping")
except KeyboardInterrupt:
send(stdout, INF, "detected KeyboardInterrupt, killing threads")
if "exec_threads" in locals():
exec_threads.terminate()
exec_threads.join()
exec_threads.close()
send(stdout, INF, "terminated threads, exiting")
loop_stored_exception = sys.exc_info()
loop_exit_code = 0
break
except Exception as e:
send(stderr, ERR, "encountered an exception while running")
print(e, file = stderr)
loop_exit_code = 1
break
if profile:
return
sys.exit(loop_exit_code)
def load_config(path, config_vector):
try:
f = open(path, "r")
config_vector.update(json.load(f))
f.close()
return 0
except:
f = open(path, "w")
f.write(sample_json)
f.close()
return 1
def save_config(path, config_vector):
try:
f = open(path)
json.dump(config_vector)
f.close()
return 0
except:
return 1
def start(pid_path, verbose = False, profile = False):
if profile:
def send(target, level, message, code = 0):
pass
import cProfile, pstats, io
profile = cProfile.Profile()
profile.enable()
main(send, profile = True)
profile.disable()
f = open("profile.txt", 'w+')
ps = pstats.Stats(profile, stream = f).sort_stats('cumtime')
ps.print_stats()
elif verbose:
main(log, verbose = verbose)
else:
f = open('errorlog.txt', 'w+')
with daemon.DaemonContext(
working_directory=os.getcwd(),
pidfile=pidfile.TimeoutPIDLockFile(pid_path),
stderr=f
):
async def handler(client, path):
clients.append(client)
while True:
try:
pong_waiter = await client.ping()
await pong_waiter
time.sleep(3)
except Exception as e:
clients.remove(client)
break
async def send_one(client, data):
await client.send(data)
def send(target, level, message, code = 0):
message_clients = clients.copy()
for client in message_clients:
try:
asyncio.run(send_one(client, message))
except:
pass
clients = []
start_server = websockets.serve(handler, "0.0.0.0", 5678)
asyncio.get_event_loop().run_until_complete(start_server)
threading.Thread(target = asyncio.get_event_loop().run_forever).start()
main(send)
def stop(pid_path):
try:
pf = open(pid_path, 'r')
pid = int(pf.read().strip())
pf.close()
except IOError:
sys.stderr.write("pidfile at <" + pid_path + "> does not exist. Daemon not running?\n")
return
try:
while True:
os.kill(pid, SIGTERM)
time.sleep(0.01)
except OSError as err:
err = str(err)
if err.find("No such process") > 0:
if os.path.exists(pid_path):
os.remove(pid_path)
else:
print(str(err))
sys.exit(1)
def restart(pid_path):
stop(pid_path)
start(pid_path)
if __name__ == "__main__":
if sys.platform.startswith("win"):
freeze_support()
start(None, verbose = True)
else:
import daemon
from daemon import pidfile
from signal import SIGTERM
pid_path = "tra-daemon.pid"
if len(sys.argv) == 2:
if 'start' == sys.argv[1]:
start(pid_path)
elif 'stop' == sys.argv[1]:
stop(pid_path)
elif 'restart' == sys.argv[1]:
restart(pid_path)
elif 'verbose' == sys.argv[1]:
start(None, verbose = True)
elif 'profile' == sys.argv[1]:
start(None, profile=True)
else:
print("usage: %s start|stop|restart|verbose|profile" % sys.argv[0])
sys.exit(2)
sys.exit(0)
else:
print("usage: %s start|stop|restart|verbose|profile" % sys.argv[0])
sys.exit(2)

View File

@ -2,7 +2,6 @@
block_cipher = None
a = Analysis(['superscript.py'],
pathex=['/workspaces/tra-data-analysis/src'],
binaries=[],
@ -11,6 +10,8 @@ a = Analysis(['superscript.py'],
"dnspython",
"sklearn.utils._weight_vector",
"requests",
"websockets.legacy",
"websockets.legacy.server",
],
hookspath=[],
runtime_hooks=[],

View File

@ -5,8 +5,6 @@ tra-analysis
dnspython
pyinstaller
requests
pymongo
numpy
scipy
@ -16,3 +14,6 @@ pyparsing
pandas
kivy==2.0.0rc2
websockets
python-daemon