pyinstaller onedir workaround for requests issue,

moved spec file to build folder


Former-commit-id: 4427eba5c993222cd2ebfdfc76a4685e25e18b0c

.devcontainer/Dockerfile

@@ -1,7 +1,6 @@
-FROM ubuntu:20.04
+FROM python:slim
 WORKDIR /
-RUN apt-get -y update
-RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends tzdata
-RUN apt-get install -y python3 python3-dev git python3-pip python3-kivy python-is-python3 libgl1-mesa-dev build-essential
-RUN ln -s $(which pip3) /usr/bin/pip
-RUN pip install pymongo pandas numpy scipy scikit-learn matplotlib pylint kivy
+RUN apt-get -y update; apt-get -y upgrade
+RUN apt-get -y install git binutils
+COPY requirements.txt .
+RUN pip install -r requirements.txt

.devcontainer/dev-dockerfile

@@ -1,2 +0,0 @@
-FROM titanscout2022/tra-analysis-base:latest
-WORKDIR /

.devcontainer/devcontainer.json

@@ -1,28 +1,22 @@
 {
     "name": "TRA Analysis Development Environment",
     "build": {
-		"dockerfile": "dev-dockerfile",
+		"dockerfile": "Dockerfile",
     },
     "settings": { 
 		"terminal.integrated.shell.linux": "/bin/bash",
 		"python.pythonPath": "/usr/local/bin/python",
 		"python.linting.enabled": true,
 		"python.linting.pylintEnabled": true,
-		"python.formatting.autopep8Path": "/usr/local/py-utils/bin/autopep8",
-		"python.formatting.blackPath": "/usr/local/py-utils/bin/black",
-		"python.formatting.yapfPath": "/usr/local/py-utils/bin/yapf",
-		"python.linting.banditPath": "/usr/local/py-utils/bin/bandit",
-		"python.linting.flake8Path": "/usr/local/py-utils/bin/flake8",
-		"python.linting.mypyPath": "/usr/local/py-utils/bin/mypy",
-		"python.linting.pycodestylePath": "/usr/local/py-utils/bin/pycodestyle",
-		"python.linting.pydocstylePath": "/usr/local/py-utils/bin/pydocstyle",
-		"python.linting.pylintPath": "/usr/local/py-utils/bin/pylint",
-		"python.testing.pytestPath": "/usr/local/py-utils/bin/pytest"
+		"python.linting.pylintPath": "/usr/local/bin/pylint",
+		"python.testing.pytestPath": "/usr/local/bin/pytest",
+    "editor.tabSize": 4,
+    "editor.insertSpaces": false
 	},
 	"extensions": [
 		"mhutchie.git-graph",
 		"ms-python.python",
 		"waderyan.gitblame"
 	],
-		"postCreateCommand": "/usr/bin/pip3 install -r ${containerWorkspaceFolder}/src/requirements.txt && /usr/bin/pip3 install --no-cache-dir pylint && /usr/bin/pip3 install pytest"
+		"postCreateCommand": ""
 	}

.devcontainer/requirements.txt

@@ -0,0 +1,15 @@
+cerberus
+dnspython
+numpy
+pyinstaller
+pylint
+pymongo
+pyparsing
+pytest
+python-daemon
+pyzmq
+requests
+scikit-learn
+scipy
+six
+tra-analysis

.github/workflows/build-cli.yml

@@ -1,7 +1,7 @@
 # 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:
@@ -11,7 +11,25 @@ jobs:
   generate:
     name: Build Linux
     runs-on: ubuntu-latest
-
     steps: 
       - name: Checkout master
         uses: actions/checkout@master
+      - name: Install Dependencies
+        run: pip install -r requirements.txt
+        working-directory: src/
+      - name: Give Execute Permission
+        run: chmod +x build-CLI.sh
+        working-directory: build/
+      - name: Build Binary
+        run: ./build-CLI.sh
+        working-directory: build/
+      - name: Copy Binary to Root Dir
+        run: cp superscript ..
+        working-directory: dist/
+      - name: Upload Release Asset
+        uses: svenstaro/upload-release-action@v2
+        with:
+          repo_token: ${{ secrets.GITHUB_TOKEN }}
+          file: superscript
+          asset_name: superscript
+          tag: ${{ github.ref }}

.gitignore

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

README.md

@@ -1,4 +1,4 @@
-# Red Alliance Analysis · ![GitHub release (latest by date)](https://img.shields.io/github/v/release/titanscouting/tra-superscript)
+# Red Alliance Analysis · ![GitHub release (latest by date)](https://img.shields.io/github/v/release/titanscout2022/red-alliance-analysis)
 
 Titan Robotics 2022 Strategy Team Repository for Data Analysis Tools. Included with these tools are the backend data analysis engine formatted as a python package, associated binaries for the analysis package, and premade scripts that can be pulled directly from this repository and will integrate with other Red Alliance applications to quickly deploy FRC scouting tools.
 

build/build-CLI.bat

@@ -2,4 +2,4 @@ set pathtospec="../src/superscript.spec"
 set pathtodist="../dist/"
 set pathtowork="temp/"
 
-pyinstaller --onefile --clean --distpath %pathtodist% --workpath %pathtowork% %pathtospec%
+pyinstaller --clean --distpath %pathtodist% --workpath %pathtowork% %pathtospec%

build/build-CLI.sh

@@ -1,5 +1,5 @@
-pathtospec="../src/superscript.spec"
+pathtospec="superscript.spec"
 pathtodist="../dist/"
 pathtowork="temp/"
 
-pyinstaller --onefile --clean --distpath ${pathtodist} --workpath ${pathtowork} ${pathtospec}
+pyinstaller --clean --distpath ${pathtodist} --workpath ${pathtowork} ${pathtospec}

build/superscript.spec

@@ -0,0 +1,50 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+block_cipher = None
+
+a = Analysis(
+    ['../src/superscript.py'],
+    pathex=[],
+    binaries=[],
+    datas=[],
+    hiddenimports=['dnspython', 'sklearn.utils._weight_vector', 'sklearn.utils._typedefs', 'sklearn.neighbors._partition_nodes', 'requests'],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=['matplotlib'],
+    win_no_prefer_redirects=False,
+    win_private_assemblies=False,
+    cipher=block_cipher,
+    noarchive=False
+)
+pyz = PYZ(
+    a.pure, 
+    a.zipped_data, 
+    cipher=block_cipher
+)
+exe = EXE(
+    pyz,
+    a.scripts, 
+    [],
+    exclude_binaries=True,
+    name='superscript',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    console=True,
+    disable_windowed_traceback=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None
+)
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.zipfiles,
+    a.datas, 
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    name='superscript'
+)

src/config.py

@@ -0,0 +1,251 @@
+import json
+from exceptions import ConfigurationError
+from cerberus import Validator
+
+from data import set_database_config, get_database_config
+
+class Configuration:
+
+	path = None
+	config = {}
+
+	_sample_config = {
+		"persistent":{
+			"key":{
+				"database":"",
+				"tba":"",
+				"tra":{
+					"CLIENT_ID":"",
+					"CLIENT_SECRET":"",
+					"url": ""
+				}
+			},
+			"config-preference":"local",
+			"synchronize-config":False
+		},
+		"variable":{
+			"event-delay":False,
+			"loop-delay":0,
+			"competition": "2020ilch",
+			"modules":{
+				"match":{
+					"tests":{
+						"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":{
+					"tests":{
+						"elo":{
+							"score":1500,
+							"N":400,
+							"K":24
+						},
+						"gl2":{
+							"score":1500,
+							"rd":250,
+							"vol":0.06
+						},
+						"ts":{
+							"mu":25,
+							"sigma":8.33
+						}
+					}
+				},
+				"pit":{
+					"tests":{
+						"wheel-mechanism":True,
+						"low-balls":True,
+						"high-balls":True,
+						"wheel-success":True,
+						"strategic-focus":True,
+						"climb-mechanism":True,
+						"attitude":True
+					}
+				}
+			}
+		}
+	}
+
+	_validation_schema = {
+		"persistent": {
+			"type": "dict",
+			"required": True,
+			"require_all": True,
+			"schema": {
+				"key": {
+					"type": "dict",
+					"require_all":True,
+					"schema": {
+						"database": {"type":"string"},
+						"tba": {"type": "string"},
+						"tra": {
+							"type": "dict",
+							"require_all": True,
+							"schema": {
+								"CLIENT_ID": {"type": "string"},
+								"CLIENT_SECRET": {"type": "string"},
+								"url": {"type": "string"}
+							}
+						}
+					}
+				},
+				"config-preference": {"type": "string", "required": True},
+				"synchronize-config": {"type": "boolean", "required": True}
+			}
+		}
+	}	
+
+	def __init__(self, path):
+		self.path = path
+		self.load_config()
+		self.validate_config()
+
+	def load_config(self):
+		try:
+			f = open(self.path, "r")
+			self.config.update(json.load(f))
+			f.close()
+		except:
+			self.config = self._sample_config
+			self.save_config()
+			f.close()
+			raise ConfigurationError("could not find config file at <" + self.path + ">, created new sample config file at that path")
+
+	def save_config(self):
+		f = open(self.path, "w+")
+		json.dump(self.config, f, ensure_ascii=False, indent=4)
+		f.close()
+
+	def validate_config(self):
+		v = Validator(self._validation_schema, allow_unknown = True)
+		isValidated = v.validate(self.config)
+
+		if not isValidated:
+			raise ConfigurationError("config validation error: " + v.errors)
+
+	def __getattr__(self, name): # simple linear lookup method for common multikey-value paths, TYPE UNSAFE
+		if name == "persistent":
+			return self.config["persistent"]
+		elif name == "key":
+			return self.config["persistent"]["key"]
+		elif name == "database":
+			# soon to be deprecated
+			return self.config["persistent"]["key"]["database"]
+		elif name == "tba":
+			return self.config["persistent"]["key"]["tba"]
+		elif name == "tra":
+			return self.config["persistent"]["key"]["tra"]
+		elif name == "priority":
+			return self.config["persistent"]["config-preference"]
+		elif name == "sync":
+			return self.config["persistent"]["synchronize-config"]
+		elif name == "variable":
+			return self.config["variable"]
+		elif name == "event_delay":
+			return self.config["variable"]["event-delay"]
+		elif name == "loop_delay":
+			return self.config["variable"]["loop-delay"]
+		elif name == "competition":
+			return self.config["variable"]["competition"]
+		elif name == "modules":
+			return self.config["variable"]["modules"]
+		else:
+			return None
+
+	def __getitem__(self, key):
+		return self.config[key]
+
+	def resolve_config_conflicts(self, logger, client): # needs improvement with new localization scheme
+		sync = self.sync
+		priority = self.priority
+
+		if sync:
+			if priority == "local" or priority == "client":
+				logger.info("config-preference set to local/client, loading local config information")
+				remote_config = get_database_config(client)
+				if remote_config != self.config["variable"]:
+					set_database_config(client, self.config["variable"])
+					logger.info("database config was different and was updated")
+				# no change to config
+			elif priority == "remote" or priority == "database":
+				logger.info("config-preference set to remote/database, loading remote config information")
+				remote_config = get_database_config(client)
+				if remote_config != self.config["variable"]:
+					self.config["variable"] = remote_config
+					self.save_config()
+					# change variable to match remote
+					logger.info("local config was different and was updated")
+			else:
+				raise ConfigurationError("persistent/config-preference field must be \"local\"/\"client\" or \"remote\"/\"database\"")
+		else:
+			if priority == "local" or priority == "client":
+				logger.info("config-preference set to local/client, loading local config information")
+				# no change to config
+			elif priority == "remote" or priority == "database":
+				logger.info("config-preference set to remote/database, loading database config information")
+				self.config["variable"] = get_database_config(client)
+				# change variable to match remote without updating local version
+			else:
+				raise ConfigurationError("persistent/config-preference field must be \"local\"/\"client\" or \"remote\"/\"database\"")

src/data.py

@@ -1,118 +1,102 @@
 import requests
-import pymongo
+import pull
 import pandas as pd
-import time
 
 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})
+	x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth-Key":api_key})
 	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(apikey, competition, team_num):
-	client = pymongo.MongoClient(apikey)
+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}):
+	for i in mdata.find({"competition" : competition, "team_scouted": str(team_num)}):
 		out[i['match']] = i['data']
 	return pd.DataFrame(out)
 
-def get_team_pit_data(apikey, competition, team_num):
-	client = pymongo.MongoClient(apikey)
+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"]
+	return mdata.find_one({"competition" : competition, "team_scouted": str(team_num)})["data"]
 
-def get_team_metrics_data(apikey, competition, team_num):
-	client = pymongo.MongoClient(apikey)
+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(apikey, competition):
-	client = pymongo.MongoClient(apikey)
-	db = client.data_scouting
-	mdata = db.teamlist
-	x=mdata.find_one({"competition":competition})
+def get_match_data_formatted(client, competition):
+	teams_at_comp = pull.get_teams_at_competition(competition)
 	out = {}
-	for i in x:
+	for team in teams_at_comp:
 		try:
-			out[int(i)] = unkeyify_2l(get_team_match_data(apikey, competition, int(i)).transpose().to_dict())
+			out[int(team)] = unkeyify_2l(get_team_match_data(client, competition, team).transpose().to_dict())
 		except:
 			pass
 	return out
 
-def get_metrics_data_formatted(apikey, competition):
-	client = pymongo.MongoClient(apikey)
-	db = client.data_scouting
-	mdata = db.teamlist
-	x=mdata.find_one({"competition":competition})
+def get_metrics_data_formatted(client, competition):
+	teams_at_comp = pull.get_teams_at_competition(competition)
 	out = {}
-	for i in x:
+	for team in teams_at_comp:
 		try:
-			out[int(i)] = d.get_team_metrics_data(apikey, competition, int(i))
+			out[int(team)] = get_team_metrics_data(client, competition, int(team))
 		except:
 			pass
 	return out
 
-def get_pit_data_formatted(apikey, competition):
-	client = pymongo.MongoClient(apikey)
-	db = client.data_scouting
-	mdata = db.teamlist
-	x=mdata.find_one({"competition":competition})
+def get_pit_data_formatted(client, competition):
+	x=requests.get("https://titanscouting.epochml.org/api/fetchAllTeamNicknamesAtCompetition?competition="+competition)
+	x = x.json()
+	x = x['data']
+	x = x.keys()
 	out = {}
 	for i in x:
 		try:
-			out[int(i)] = get_team_pit_data(apikey, competition, int(i))
+			out[int(i)] = get_team_pit_data(client, competition, int(i))
 		except:
 			pass
 	return out
 
-def get_pit_variable_data(apikey, competition):
-	client = pymongo.MongoClient(apikey)
+def get_pit_variable_data(client, competition):
 	db = client.data_processing
 	mdata = db.team_pit
 	out = {}
 	return mdata.find()
 
-def get_pit_variable_formatted(apikey, competition):
-	temp = get_pit_variable_data(apikey, competition)
+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(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
-	client = pymongo.MongoClient(apikey)
+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(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_metrics"):
-	client = pymongo.MongoClient(apikey)
+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(apikey, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
-	client = pymongo.MongoClient(apikey)
+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(apikey, flag):
-	client = pymongo.MongoClient(apikey)
+def get_analysis_flags(client, flag):
 	db = client.data_processing
 	mdata = db.flags
 	return mdata.find_one({flag:{"$exists":True}})
 
-def set_analysis_flags(apikey, flag, data):
-	client = pymongo.MongoClient(apikey)
+def set_analysis_flags(client, flag, data):
 	db = client.data_processing
 	mdata = db.flags
 	return mdata.replace_one({flag:{"$exists":True}}, data, True)
@@ -127,3 +111,89 @@ def unkeyify_2l(layered_dict):
 		add.sort(key = lambda x: x[0])
 		out[i] = list(map(lambda x: x[1], add))
 	return out
+
+def get_previous_time(client):
+
+	previous_time = get_analysis_flags(client, "latest_update")
+
+	if previous_time == None:
+
+		set_analysis_flags(client, "latest_update", 0)
+		previous_time = 0
+
+	else:
+
+		previous_time = previous_time["latest_update"]
+
+	return previous_time
+
+def set_current_time(client, current_time):
+
+	set_analysis_flags(client, "latest_update", {"latest_update":current_time})
+
+def get_database_config(client):
+
+	remote_config = get_analysis_flags(client, "config")
+	return remote_config["config"] if remote_config != None else None
+
+def set_database_config(client, config):
+
+	set_analysis_flags(client, "config", {"config": config})
+
+def load_match(client, competition):
+
+	return get_match_data_formatted(client, competition)
+
+def load_metric(client, competition, match, group_name, metrics):
+
+	group = {}
+
+	for team in match[group_name]:
+
+		db_data = get_team_metrics_data(client, 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"], "sigma": 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(client, competition):
+
+	return get_pit_data_formatted(client, competition)
+
+def push_match(client, competition, results):
+
+	for team in results:
+
+		push_team_tests_data(client, competition, team, results[team])
+
+def push_metric(client, competition, metric):
+
+	for team in metric:
+
+		push_team_metrics_data(client, competition, team, metric[team])
+
+def push_pit(client, competition, pit):
+
+	for variable in pit:
+	
+		push_team_pit_data(client, competition, variable, pit[variable])
+
+def check_new_database_matches(client, competition):
+
+	return True

src/dep.py

@@ -0,0 +1,141 @@
+# contains deprecated functions, not to be used unless nessasary!
+
+import json
+
+sample_json = """
+{
+   "persistent":{
+      "key":{
+         "database":"",
+         "tba":"",
+         "tra":{
+            "CLIENT_ID":"",
+            "CLIENT_SECRET":"",
+			"url": ""
+         }
+      },
+      "config-preference":"local",
+      "synchronize-config":false
+   },
+   "variable":{
+      "max-threads":0.5,
+      "team":"",
+      "event-delay":false,
+      "loop-delay":0,
+      "reportable":true,
+      "teams":[
+         
+      ],
+      "modules":{
+         "match":{
+            "tests":{
+               "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":{
+            "tests":{
+               "elo":{
+                  "score":1500,
+                  "N":400,
+                  "K":24
+               },
+               "gl2":{
+                  "score":1500,
+                  "rd":250,
+                  "vol":0.06
+               },
+               "ts":{
+                  "mu":25,
+                  "sigma":8.33
+               }
+            }
+         },
+         "pit":{
+            "tests":{
+               "wheel-mechanism":true,
+               "low-balls":true,
+               "high-balls":true,
+               "wheel-success":true,
+               "strategic-focus":true,
+               "climb-mechanism":true,
+               "attitude":true
+            }
+         }
+      }
+   }
+}
+"""
+
+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

src/design.kv

@@ -1,151 +0,0 @@
-<Launch>:
-	orientation: "vertical"
-	
-	NavigationLayout:
-		ScreenManager:
-			id: screen_manager
-			HomeScreen:
-				name: "Home"
-				BoxLayout:
-					orientation: "vertical"
-					MDToolbar:
-						title: screen_manager.current
-						elevation: 10
-						left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
-
-					GridLayout:
-						cols: 1
-						padding: 15, 15
-						spacing: 20, 20
-						MDTextFieldRect:
-							hint_text: "Console Log"
-							# size_hint: .8, None
-							# align: 'center'
-					# Widget:
-			SettingsScreen:
-				name: "Settings"
-				BoxLayout:
-					orientation: 'vertical' 
-					MDToolbar:
-						title: screen_manager.current
-						elevation: 10
-						left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
-					Widget:
-			InfoScreen:
-				name: "Info"
-				BoxLayout:
-					orientation: 'vertical' 
-					MDToolbar:
-						title: screen_manager.current
-						elevation: 10
-						left_action_items: [['menu', lambda x: nav_drawer.toggle_nav_drawer()]]
-					# GridLayout:
-					#     cols: 2
-					#     padding: 15, 15
-					#     spacing: 20, 20
-					BoxLayout:
-						orientation: "horizontal"
-						MDLabel:
-							text: "DB Key:"
-							halign: 'center'
-						MDTextField:
-							hint_text: "placeholder"
-							pos_hint: {"center_y": .5}
-						
-					BoxLayout:
-						orientation: "horizontal"
-						MDLabel:
-							text: "TBA Key:"
-							halign: 'center'
-						MDTextField:
-							hint_text: "placeholder"
-							pos_hint: {"center_y": .5}
-					BoxLayout:
-						orientation: "horizontal"
-						MDLabel:
-							text: "CPU Use:"
-							halign: 'center'
-						MDLabel:
-							text: "placeholder"
-							halign: 'center'
-					BoxLayout:
-						orientation: "horizontal"
-						MDLabel:
-							text: "Network:"
-							halign: 'center'
-						MDLabel:
-							text: "placeholder"
-							halign: 'center'
-					Widget:
-					BoxLayout:
-						orientation: "horizontal"
-						MDLabel:
-							text: "Progress"
-							halign: 'center'
-						MDProgressBar:
-							id: progress
-							value: 50
-			StatsScreen:
-				name: "Stats"
-				MDCheckbox:
-					size_hint: None, None
-					size: "48dp", "48dp"
-					pos_hint: {'center_x': .5, 'center_y': .5}
-					on_active: Screen.test()
-							
-#Navigation Drawer ------------------------- 
-		MDNavigationDrawer:
-			id: nav_drawer
-			BoxLayout:
-				orientation: "vertical"
-				padding: "8dp"
-				spacing: "8dp"
-				MDLabel:
-					text: "Titan Scouting"
-					font_style: "Button"
-					size_hint_y: None
-					height: self.texture_size[1]
-
-				MDLabel:
-					text: "Data Analysis"
-					font_style: "Caption"
-					size_hint_y: None
-					height: self.texture_size[1]
-				ScrollView:
-					MDList:
-						OneLineAvatarListItem:
-							text: "Home"
-							on_press:
-								# nav_drawer.set_state("close")
-								# screen_manager.transition.direction = "left"
-								screen_manager.current = "Home"
-							IconLeftWidget:
-								icon: "home"
-							
-						OneLineAvatarListItem:
-							text: "Settings"
-							on_press:
-								# nav_drawer.set_state("close")
-								# screen_manager.transition.direction = "right"
-								# screen_manager.fade
-								screen_manager.current = "Settings"
-							IconLeftWidget:
-								icon: "cog"
-						OneLineAvatarListItem:
-							text: "Info"
-							on_press:
-								# nav_drawer.set_state("close")
-								# screen_manager.transition.direction = "right"
-								# screen_manager.fade
-								screen_manager.current = "Info"
-							IconLeftWidget:
-								icon: "cog"
-						OneLineAvatarListItem:
-							text: "Stats"
-							on_press:
-								# nav_drawer.set_state("close")
-								# screen_manager.transition.direction = "right"
-								# screen_manager.fade
-								screen_manager.current = "Stats"
-							IconLeftWidget:
-								icon: "cog"

src/exceptions.py

@@ -0,0 +1,7 @@
+class APIError(Exception):
+	def __init__(self, str):
+		super().__init__(str)
+
+class ConfigurationError (Exception):
+	def __init__(self, str):
+		super().__init__(str)

src/interface.py

@@ -0,0 +1,91 @@
+from logging import Logger as L
+import datetime
+import platform
+import json
+
+class Logger(L):
+
+	file = None
+
+	levels = {
+		0: "",
+		10:"[DEBUG]   ",
+		20:"[INFO]    ",
+		30:"[WARNING] ",
+		40:"[ERROR]   ",
+		50:"[CRITICAL]",
+	}
+
+	targets = []
+
+	def __init__(self, verbose, profile, debug, file = None):
+		super().__init__("tra_logger")
+
+		self.file = file
+
+		if file != None:
+			self.targets.append(self._send_file)
+
+		if profile:
+			self.targets.append(self._send_null)
+		elif verbose:
+			self.targets.append(self._send_scli)
+		elif debug:
+			self.targets.append(self._send_scli)
+		else:
+			self.targets.append(self._send_null)
+
+	def _send_null(self, msg):
+		pass
+
+	def _send_scli(self, msg):
+		print(msg)
+
+	def _send_file(self, msg):
+		f = open(self.file, 'a')
+		f.write(msg + "\n")
+		f.close()
+
+	def get_time_formatted(self):
+		return datetime.datetime.now().strftime("%Y/%m/%d %H:%M:%S %Z")
+
+	def log(self, level, msg):
+		for t in self.targets:
+			t(self.get_time_formatted() + "| " + self.levels[level] + ": " + msg)
+
+	def debug(self, msg):
+		self.log(10, msg)
+
+	def info(self, msg):
+		self.log(20, msg)
+
+	def warning(self, msg):
+		self.log(30, msg)
+
+	def error(self, msg):
+		self.log(40, msg)
+
+	def critical(self, msg):
+		self.log(50, msg)
+
+	def splash(self, version):
+
+		def hrule():
+			self.log(0, "#"+38*"-"+"#")
+		def box(s):
+			temp = "|"
+			temp += s
+			temp += (40-len(s)-2)*" "
+			temp += "|"
+			self.log(0, temp)
+		
+		hrule()
+		box(" superscript version: " + version)
+		box(" os: " + platform.system())
+		box(" python: " + platform.python_version())
+		hrule()
+
+	def save_module_to_file(self, module, data, results):
+		f = open(module + ".log", "w")
+		json.dump({"data": data, "results":results}, f, ensure_ascii=False, indent=4)
+		f.close()

src/main.py

@@ -1,58 +0,0 @@
-from kivy.lang import Builder
-
-from kivymd.uix.screen import Screen
-from kivymd.uix.list import OneLineListItem, MDList, TwoLineListItem, ThreeLineListItem
-from kivymd.uix.list import OneLineIconListItem, IconLeftWidget
-from kivy.uix.scrollview import ScrollView
-
-
-from kivy.uix.boxlayout import BoxLayout
-from kivy.uix.screenmanager import ScreenManager, Screen
-from kivy.uix.dropdown import DropDown
-from kivy.uix.button import Button
-from kivy.base import runTouchApp
-from kivymd.uix.menu import MDDropdownMenu, MDMenuItem
-
-from kivymd.app import MDApp
-# import superscript as ss
-
-# from tra_analysis import analysis as an
-import data as d
-from collections import defaultdict
-import json
-import math
-import numpy as np
-import os
-from os import system, name
-from pathlib import Path
-from multiprocessing import Pool
-import matplotlib.pyplot as plt
-from concurrent.futures import ThreadPoolExecutor
-import time
-import warnings
-
-# global exec_threads
-
-
-# Screens
-class HomeScreen(Screen):
-	pass
-class SettingsScreen(Screen):
-	pass
-class InfoScreen(Screen):
-	pass
-
-class StatsScreen(Screen):
-	pass
-
-
-class MyApp(MDApp):
-	def build(self):
-		self.theme_cls.primary_palette = "Red"
-		return Builder.load_file("design.kv")
-	def test():
-		print("test")
-
-
-if __name__ == "__main__":
-	MyApp().run()

src/module.py

@@ -0,0 +1,321 @@
+import abc
+import data as d
+import signal
+import numpy as np
+from tra_analysis import Analysis as an
+
+class Module(metaclass = abc.ABCMeta):
+
+	@classmethod
+	def __subclasshook__(cls, subclass):
+		return (hasattr(subclass, '__init__') and 
+				callable(subclass.__init__) and 
+				hasattr(subclass, 'validate_config') and 
+				callable(subclass.validate_config) and
+				hasattr(subclass, 'run') and 
+				callable(subclass.run)
+				)
+	@abc.abstractmethod
+	def __init__(self, config, apikey, tbakey, timestamp, competition, *args, **kwargs):
+		raise NotImplementedError
+	@abc.abstractmethod
+	def validate_config(self, *args, **kwargs):
+		raise NotImplementedError
+	@abc.abstractmethod
+	def run(self, *args, **kwargs):
+		raise NotImplementedError
+
+class Match (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.load_match(self.apikey, self.competition)
+
+	def _simplestats(self, data_test):
+
+		signal.signal(signal.SIGINT, signal.SIG_IGN)
+
+		data = np.array(data_test[3])
+		data = data[np.isfinite(data)]
+		ranges = list(range(len(data)))
+
+		test = data_test[2]
+
+		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 _process_data(self):
+
+		tests = self.config["tests"]
+		data = self.data
+
+		input_vector = []
+
+		for team in data:
+
+			for variable in data[team]:
+
+				if variable in tests:
+
+					for test in tests[variable]:
+
+						input_vector.append((team, variable, test, data[team][variable]))
+
+		self.data = input_vector
+		self.results = []
+		for test_var_data in self.data:
+			self.results.append(self._simplestats(test_var_data))
+
+	def _push_results(self):
+
+		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
+
+		result_filtered = self.results
+		input_vector = self.data
+
+		return_vector = AutoVivification()
+
+		i = 0
+
+		for result in result_filtered:
+
+			filtered = input_vector[i][2]
+
+			try:
+				short = short_mapping[filtered]
+				return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result[short]
+			except KeyError: # not in mapping
+				return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result
+
+			i += 1
+
+		self.results = return_vector
+
+		d.push_match(self.apikey, self.competition, self.results)
+
+class Metric (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.pull_new_tba_matches(self.tbakey, self.competition, self.timestamp)
+
+	def _process_data(self):
+
+		elo_N = self.config["tests"]["elo"]["N"]
+		elo_K = self.config["tests"]["elo"]["K"]
+
+		matches = self.data
+
+		red = {}
+		blu = {}
+
+		for match in matches:
+
+			red = d.load_metric(self.apikey, self.competition, match, "red", self.config["tests"])
+			blu = d.load_metric(self.apikey, self.competition, match, "blue", self.config["tests"])
+	
+			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)
+
+			d.push_metric(self.apikey, self.competition, temp_vector)
+
+	def _push_results(self):
+		pass
+
+class Pit (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+	
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.load_pit(self.apikey, self.competition)
+
+	def _process_data(self):
+		tests = self.config["tests"]
+		return_vector = {}
+		for team in self.data:
+			for variable in self.data[team]:
+				if variable in tests:
+					if not variable in return_vector:
+						return_vector[variable] = []
+					return_vector[variable].append(self.data[team][variable])
+
+		self.results = return_vector
+
+	def _push_results(self):
+		d.push_pit(self.apikey, self.competition, self.results)
+
+class Rating (Module):
+	pass
+
+class Heatmap (Module):
+	pass
+
+class Sentiment (Module):
+	pass

src/pull.py

@@ -0,0 +1,63 @@
+import requests 
+from exceptions import APIError
+from dep import load_config
+
+url = "https://titanscouting.epochml.org"
+config_tra = {}
+load_config("config.json", config_tra)
+trakey = config_tra['persistent']['key']['tra']
+
+def get_team_competition():
+	endpoint = '/api/fetchTeamCompetition'
+	params = {
+		"CLIENT_ID": trakey['CLIENT_ID'],
+		"CLIENT_SECRET": trakey['CLIENT_SECRET']
+	}
+	response = requests.request("GET", url + endpoint, params=params)
+	json = response.json()
+	if json['success']:
+		return json['competition']
+	else:
+		raise APIError(json)
+
+def get_team():
+	endpoint = '/api/fetchTeamCompetition'
+	params = {
+		"CLIENT_ID": trakey['CLIENT_ID'],
+		"CLIENT_SECRET": trakey['CLIENT_SECRET']
+	}
+	response = requests.request("GET", url + endpoint, params=params)
+	json = response.json()
+	if json['success']:
+		return json['team']
+	else:
+		raise APIError(json)
+
+def get_team_match_data(competition, team_num):
+	endpoint = '/api/fetchAllTeamMatchData'
+	params = {
+		"competition": competition,
+		"teamScouted": team_num,
+		"CLIENT_ID": trakey['CLIENT_ID'],
+		"CLIENT_SECRET": trakey['CLIENT_SECRET']
+	}
+	response = requests.request("GET", url + endpoint, params=params)
+	json = response.json()
+	if json['success']:
+		return json['data'][team_num]
+	else:
+		raise APIError(json)
+
+def get_teams_at_competition(competition):
+	endpoint = '/api/fetchAllTeamNicknamesAtCompetition'
+	params = {
+		"competition": competition,
+		"CLIENT_ID": trakey['CLIENT_ID'],
+		"CLIENT_SECRET": trakey['CLIENT_SECRET']
+	}
+	response = requests.request("GET", url + endpoint, params=params)
+	json = response.json()
+	if json['success']:
+		return list(json['data'].keys())
+	else:
+		raise APIError(json)

src/requirements.txt

@@ -1,19 +0,0 @@
-requests
-pymongo
-pandas
-tra-analysis
-
-dnspython
-pyinstaller
-requests
-pymongo
-
-numpy
-scipy
-scikit-learn
-six
-pyparsing
-pandas
-
-kivy==2.0.0rc2
-setuptools>=65.5.1 # not directly required, pinned by Snyk to avoid a vulnerability

src/superscript.py

@@ -3,10 +3,43 @@
 # Notes:
 # setup:
 
-__version__ = "0.8.6"
+__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.log
+		- 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
+		- reduced memory usage slightly by consolidating the unwrapped input data
+		- added debug option, which performs one loop of analysis and dumps results to local files
+		- added event and time delay options to config
+			- event delay pauses loop until even listener recieves an update
+			- time delay pauses loop until the time specified has elapsed since the BEGINNING of previous loop
+		- added options to pull config information from database (reatins option to use local config file)
+			- config-preference option selects between prioritizing local config and prioritizing database config
+			- synchronize-config option selects whether to update the non prioritized config with the prioritized one
+			- divided config options between persistent ones (keys), and variable ones (everything else)
+		- generalized behavior of various core components by collecting loose functions in several dependencies into classes
+			- module.py contains classes, each one represents a single data analysis routine
+			- config.py contains the Configuration class, which stores the configuration information and abstracts the getter methods
+	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:
@@ -114,514 +147,257 @@ __author__ = (
 	"Jacob Levine <jlevine@imsa.edu>",
 )
 
-__all__ = [
-	"load_config",
-	"save_config",
-	"get_previous_time",
-	"load_match",
-	"matchloop",
-	"load_metric",
-	"metricloop",
-	"load_pit",
-	"pitloop",
-	"push_match",
-	"push_metric",
-	"push_pit",
-]
-
 # imports:
 
-from tra_analysis import analysis as an
-import data as d
-from collections import defaultdict
-import json
-import math
-import numpy as np
-import os
-from os import system, name
-from pathlib import Path
-from multiprocessing import Pool
-import platform
-import sys
-import time
+import os, sys, time
+import pymongo # soon to be deprecated
+import traceback
 import warnings
+from config import Configuration, ConfigurationError
+from data import get_previous_time, set_current_time, check_new_database_matches
+from interface import Logger
+from module import Match, Metric, Pit
+import zmq
 
-global exec_threads
+config_path = "config.json"
 
-def main():
+def main(logger, verbose, profile, debug, socket_send = None):
 
-	global exec_threads
-
-	sys.stderr = open("errorlog.txt", "w")
+	def close_all():
+		if "client" in locals():
+			client.close()
 
 	warnings.filterwarnings("ignore")
 
-	splash()
+	logger.splash(__version__)
 
-	while (True):
+	modules = {"match": Match, "metric": Metric, "pit": Pit}
+
+	while True:
 
 		try:
 
-			current_time = time.time()
-			print("[OK] time: " + str(current_time))
+			loop_start = time.time()
 
-			config = load_config("config.json")
-			competition = config["competition"]
-			match_tests = config["statistics"]["match"]
-			pit_tests = config["statistics"]["pit"]
-			metrics_tests = config["statistics"]["metric"]
-			print("[OK] configs loaded")
+			logger.info("current time: " + str(loop_start))
+			socket_send("current time: " + str(loop_start))
 
-			print("[OK] starting threads")
-			cfg_max_threads = config["max-threads"]
-			sys_max_threads = os.cpu_count()
-			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
+			config = Configuration(config_path)
+			
+			logger.info("found and loaded config at <" + config_path + ">")
+			socket_send("found and loaded config at <" + config_path + ">")
+
+			apikey, tbakey = config.database, config.tba
+
+			logger.info("found and loaded database and tba keys")
+			socket_send("found and loaded database and tba keys")
+
+			client = pymongo.MongoClient(apikey)
+
+			logger.info("established connection to database")
+			socket_send("established connection to database")
+
+			previous_time = get_previous_time(client)
+
+			logger.info("analysis backtimed to: " + str(previous_time))
+			socket_send("analysis backtimed to: " + str(previous_time))
+
+			config.resolve_config_conflicts(logger, client)
+
+			config_modules, competition = config.modules, config.competition
+
+			for m in config_modules:
+				if m in modules:
+					start = time.time()
+					current_module = modules[m](config_modules[m], client, tbakey, previous_time, competition)
+					valid = current_module.validate_config()
+					if not valid:
+						continue
+					current_module.run()
+					logger.info(m + " module finished in " + str(time.time() - start) + " seconds")
+					socket_send(m + " module finished in " + str(time.time() - start) + " seconds")
+					if debug:
+						logger.save_module_to_file(m, current_module.data, current_module.results) # logging flag check done in logger
+
+			set_current_time(client, loop_start)
+			close_all()
+
+			logger.info("closed threads and database client")
+			logger.info("finished all tasks in " + str(time.time() - loop_start) + " seconds, looping")
+			socket_send("closed threads and database client")
+			socket_send("finished all tasks in " + str(time.time() - loop_start) + " seconds, looping")
+
+			if profile:
+				return 0
+
+			if debug:
+				return 0
+
+			event_delay = config["variable"]["event-delay"]
+			if event_delay:
+				logger.info("loop delayed until database returns new matches")
+				socket_send("loop delayed until database returns new matches")
+				new_match = False
+				while not new_match:
+					time.sleep(1)
+					new_match = check_new_database_matches(client, competition)
+				logger.info("database returned new matches")
+				socket_send("database returned new matches")
 			else:
-				print("[ERROR] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
-				exit()
-			exec_threads = Pool(processes = alloc_processes)
-			print("[OK] " + str(alloc_processes) + " threads started")
-
-			apikey = config["key"]["database"]
-			tbakey = config["key"]["tba"]
-			print("[OK] loaded keys")
-
-			previous_time = get_previous_time(apikey)
-			print("[OK] analysis backtimed to: " + str(previous_time))
-
-			print("[OK] loading data")
-			start = time.time()
-			match_data = load_match(apikey, competition)
-			pit_data = load_pit(apikey, competition)
-			print("[OK] loaded data in " + str(time.time() - start) + " seconds")
-
-			print("[OK] running match stats")
-			start = time.time()
-			matchloop(apikey, competition, match_data, match_tests)
-			print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
-
-			print("[OK] running team metrics")
-			start = time.time()
-			metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
-			print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
-
-			print("[OK] running pit analysis")
-			start = time.time()
-			pitloop(apikey, competition, pit_data, pit_tests)
-			print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
-			
-			set_current_time(apikey, current_time)
-			print("[OK] finished all tests, looping")
-
-			print_hrule()
+				loop_delay = float(config["variable"]["loop-delay"])
+				remaining_time = loop_delay - (time.time() - loop_start)
+				if remaining_time > 0:
+					logger.info("loop delayed by " + str(remaining_time) + " seconds")
+					socket_send("loop delayed by " + str(remaining_time) + " seconds")
+					time.sleep(remaining_time)
 
 		except KeyboardInterrupt:
-			print("\n[OK] caught KeyboardInterrupt, killing processes")
-			exec_threads.terminate()
-			print("[OK] processes killed, exiting")
-			exit()
+			close_all()
+			logger.info("detected KeyboardInterrupt, exiting")
+			socket_send("detected KeyboardInterrupt, exiting")
+			return 0
 
-		else:
+		except ConfigurationError as e:
+			str_e = "".join(traceback.format_exception(e))
+			logger.error("encountered a configuration error: " + str(e))
+			logger.error(str_e)
+			socket_send("encountered a configuration error: " + str(e))
+			socket_send(str_e)
+			close_all()
+			return 1
+
+		except Exception as e:
+			str_e = "".join(traceback.format_exception(e))
+			logger.error("encountered an exception while running")
+			logger.error(str_e)
+			socket_send("encountered an exception while running")
+			socket_send(str_e)
+			close_all()
+			return 1
+
+def start(pid_path, verbose, profile, debug):
+
+	if profile:
+
+		def send(msg):
 			pass
 
-		#clear()
+		logger = Logger(verbose, profile, debug)
 
-def clear(): 
+		import cProfile, pstats, io
+		profile = cProfile.Profile()
+		profile.enable()
+		exit_code = main(logger, verbose, profile, debug, socket_send = send)
+		profile.disable()
+		f = open("profile.txt", 'w+')
+		ps = pstats.Stats(profile, stream = f).sort_stats('cumtime')
+		ps.print_stats()
+		sys.exit(exit_code)
 
-	# for windows 
-	if name == 'nt': 
-		_ = system('cls') 
+	elif verbose:
+
+		def send(msg):
+			pass
+
+		logger = Logger(verbose, profile, debug)
+
+		exit_code = main(logger, verbose, profile, debug, socket_send = send)
+		sys.exit(exit_code)
+
+	elif debug:
+
+		def send(msg):
+			pass
+
+		logger = Logger(verbose, profile, debug)
+
+		exit_code = main(logger, verbose, profile, debug, socket_send = send)
+		sys.exit(exit_code)
 
-	# for mac and linux(here, os.name is 'posix') 
 	else:
-		_ = system('clear')
 
-def print_hrule():
+		logfile = "logfile.log"
 
-	print("#"+38*"-"+"#")
+		f = open(logfile, 'w+')
+		f.close()
 
-def print_box(s):
+		e = open('errorlog.log', 'w+')
+		with daemon.DaemonContext(
+				working_directory = os.getcwd(),
+				pidfile = pidfile.TimeoutPIDLockFile(pid_path),
+				stderr = e
+			):
 
-	temp = "|"
-	temp += s
-	temp += (40-len(s)-2)*" "
-	temp += "|"
-	print(temp)
+			context = zmq.Context()
+			socket = context.socket(zmq.PUB)
+			socket.bind("tcp://*:5678")
+			socket.send(b'status')
 
-def splash():
+			def send(msg):
+				socket.send(bytes("status: " + msg, "utf-8"))
 
-	print_hrule()
-	print_box(" superscript version: " + __version__)
-	print_box(" os: " + platform.system())
-	print_box(" python: " + platform.python_version())
-	print_hrule()
+			logger = Logger(verbose, profile, debug, file = logfile)
 
-def load_config(file):
+			exit_code = main(logger, verbose, profile, debug, socket_send = send)
 
-	config_vector = {}
+			socket.close()
+			f.close()
+			
+			sys.exit(exit_code)
+
+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:
-		f = open(file)
-	except:
-		print("[ERROR] could not locate config.json, generating blank config.json and exiting")
-		f = open(file, "w")
-		f.write(sample_json)
-		exit()
-	
-	config_vector = json.load(f)
-
-	return config_vector
-
-def save_config(file, config_vector):
-
-	with open(file) as f:
-		json.dump(config_vector, f)
-
-def get_previous_time(apikey):
-
-	previous_time = d.get_analysis_flags(apikey, "latest_update")
-
-	if previous_time == None:
-
-		d.set_analysis_flags(apikey, "latest_update", 0)
-		previous_time = 0
-
+		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:
+			traceback.print_exc(file = sys.stderr)
+			sys.exit(1)
 
-		previous_time = previous_time["latest_update"]
-
-	return previous_time
-
-def set_current_time(apikey, current_time):
-
-	d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
-
-def load_match(apikey, competition):
-
-	return d.get_match_data_formatted(apikey, competition)
-
-def simplestats(data_test):
-
-	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(apikey, competition, data, tests): # expects 3D array with [Team][Variable][Match]
-
-	global 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
-
-	push_match(apikey, competition, return_vector)
-
-def load_metric(apikey, competition, match, group_name, metrics):
-
-	group = {}
-
-	for team in match[group_name]:
-
-		db_data = d.get_team_metrics_data(apikey, competition, team)
-
-		if d.get_team_metrics_data(apikey, competition, team) == None:
-
-			elo = {"score": metrics["elo"]["score"]}
-			gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
-			ts = {"mu": metrics["ts"]["mu"], "sigma": 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 metricloop(tbakey, apikey, competition, timestamp, metrics): # listener based metrics update
-
-	elo_N = metrics["elo"]["N"]
-	elo_K = metrics["elo"]["K"]
-
-	matches = d.pull_new_tba_matches(tbakey, competition, timestamp)
-
-	red = {}
-	blu = {}
-
-	for match in matches:
-
-		red = load_metric(apikey, competition, match, "red", metrics)
-		blu = load_metric(apikey, 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(apikey, competition, temp_vector)
-
-def load_pit(apikey, competition):
-
-	return d.get_pit_data_formatted(apikey, competition)
-
-def pitloop(apikey, 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])
-
-	push_pit(apikey, competition, return_vector)
-
-def push_match(apikey, competition, results):
-
-	for team in results:
-
-		d.push_team_tests_data(apikey, competition, team, results[team])
-
-def push_metric(apikey, competition, metric):
-
-	for team in metric:
-
-			d.push_team_metrics_data(apikey, competition, team, metric[team])
-
-def push_pit(apikey, competition, pit):
-
-	for variable in pit:
-
-		d.push_team_pit_data(apikey, competition, variable, pit[variable])
-
-def get_team_metrics(apikey, tbakey, competition):
-
-	metrics = d.get_metrics_data_formatted(apikey, competition)
-
-	elo = {}
-	gl2 = {}
-
-	for team in metrics:
-
-		elo[team] = metrics[team]["metrics"]["elo"]["score"]
-		gl2[team] = metrics[team]["metrics"]["gl2"]["score"]
-
-	elo = {k: v for k, v in sorted(elo.items(), key=lambda item: item[1])}
-	gl2 = {k: v for k, v in sorted(gl2.items(), key=lambda item: item[1])}
-
-	elo_ranked = []
-
-	for team in elo:
-
-		elo_ranked.append({"team": str(team), "elo": str(elo[team])})
-
-	gl2_ranked = []
-
-	for team in gl2:
-
-		gl2_ranked.append({"team": str(team), "gl2": str(gl2[team])})
-
-	return {"elo-ranks": elo_ranked, "glicko2-ranks": gl2_ranked}
-
-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 restart(pid_path):
+	stop(pid_path)
+	start(pid_path, False, False, False)
 
 if __name__ == "__main__":
-	if sys.platform.startswith('win'):
-		multiprocessing.freeze_support()
-	main()
+
+	if sys.platform.startswith("win"):
+		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, False, False, False)
+			elif 'stop' == sys.argv[1]:
+				stop(pid_path)
+			elif 'restart' == sys.argv[1]:
+				restart(pid_path)
+			elif 'verbose' == sys.argv[1]:
+				start(None, True, False, False)
+			elif 'profile' == sys.argv[1]:
+				start(None, False, True, False)
+			elif 'debug' == sys.argv[1]:
+				start(None, False, False, True)
+			else:
+				print("usage: %s start|stop|restart|verbose|profile|debug" % sys.argv[0])
+				sys.exit(2)
+			sys.exit(0)
+		else:
+			print("usage: %s start|stop|restart|verbose|profile|debug" % sys.argv[0])
+			sys.exit(2)

src/superscript.spec

@@ -1,37 +0,0 @@
-# -*- mode: python ; coding: utf-8 -*-
-
-block_cipher = None
-
-
-a = Analysis(['superscript.py'],
-             pathex=['/workspaces/tra-data-analysis/src'],
-             binaries=[],
-             datas=[],
-             hiddenimports=[
-                 "dnspython", 
-                 "sklearn.utils._weight_vector",
-                 "requests",
-             ],
-             hookspath=[],
-             runtime_hooks=[],
-             excludes=[],
-             win_no_prefer_redirects=False,
-             win_private_assemblies=False,
-             cipher=block_cipher,
-             noarchive=False)
-pyz = PYZ(a.pure, a.zipped_data,
-             cipher=block_cipher)
-exe = EXE(pyz,
-          a.scripts,
-          a.binaries,
-          a.zipfiles,
-          a.datas,
-          [('W ignore', None, 'OPTION')],
-          name='superscript',
-          debug=False,
-          bootloader_ignore_signals=False,
-          strip=False,
-          upx=True,
-          upx_exclude=[],
-          runtime_tmpdir=None,
-          console=True )

test/test_zmq.py

@@ -0,0 +1,14 @@
+import signal
+import zmq
+
+signal.signal(signal.SIGINT, signal.SIG_DFL)
+
+context = zmq.Context()
+
+socket = context.socket(zmq.SUB)
+socket.connect('tcp://localhost:5678')
+socket.setsockopt(zmq.SUBSCRIBE, b'status')
+
+while True:
+    message = socket.recv_multipart()
+    print(f'Received: {message}')