mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-12-30 19:39:09 +00:00
deleted config.json
changed superscript config lookup to relative path added additional requirements to requirements.txt added build spec file for superscript
This commit is contained in:
Arthur Lu
parent
8ede63ed04
commit
70afd23f2c
@ -1,2 +1,7 @@
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FROM python
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FROM ubuntu:20.04
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WORKDIR ~/
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WORKDIR /
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RUN apt-get -y update
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RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends tzdata
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RUN apt-get install -y python3 python3-dev git python3-pip python3-kivy python-is-python3 libgl1-mesa-dev build-essential
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RUN ln -s $(which pip3) /usr/bin/pip
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RUN pip install pymongo pandas numpy scipy scikit-learn matplotlib pylint kivy
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2
.devcontainer/dev-dockerfile
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2
.devcontainer/dev-dockerfile
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FROM titanscout2022/tra-analysis-base:latest
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WORKDIR /
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@ -1,7 +1,7 @@
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{
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{
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"name": "TRA Analysis Development Environment",
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"name": "TRA Analysis Development Environment",
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"build": {
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"build": {
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"dockerfile": "Dockerfile",
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"dockerfile": "dev-dockerfile",
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},
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},
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"settings": {
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"settings": {
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"terminal.integrated.shell.linux": "/bin/bash",
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"terminal.integrated.shell.linux": "/bin/bash",
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@ -24,5 +24,5 @@
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"ms-python.python",
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"ms-python.python",
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"waderyan.gitblame"
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"waderyan.gitblame"
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],
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],
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"postCreateCommand": "apt install vim -y ; pip install -r src/requirements.txt ; pip install pylint ; pip install tra-analysis; pip install pytest"
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"postCreateCommand": "/usr/bin/pip3 install -r /workspaces/tra-data-analysis/src/requirements.txt && /usr/bin/pip3 install --no-cache-dir pylint && /usr/bin/pip3 install pytest"
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}
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}
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101
src/config.json
101
src/config.json
@ -1,101 +0,0 @@
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{
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"max-threads": 0.5,
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"team": "",
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"competition": "",
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"key": {
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"database": "",
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"tba": ""
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},
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"statistics": {
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"match": {
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"balls-blocked": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-collected": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-lower-teleop": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-lower-auto": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-started": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-upper-teleop": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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],
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"balls-upper-auto": [
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"basic_stats",
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"historical_analysis",
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"regression_linear",
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"regression_logarithmic",
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"regression_exponential",
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"regression_polynomial",
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"regression_sigmoidal"
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]
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},
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"metric": {
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"elo": {
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"score": 1500,
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"N": 400,
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"K": 24
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},
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"gl2": {
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"score": 1500,
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"rd": 250,
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"vol": 0.06
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},
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"ts": {
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"mu": 25,
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"sigma": 8.33
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}
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},
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"pit": {
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"wheel-mechanism": true,
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"low-balls": true,
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"high-balls": true,
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"wheel-success": true,
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"strategic-focus": true,
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"climb-mechanism": true,
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"attitude": true
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}
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}
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}
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@ -2,4 +2,18 @@ requests
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pymongo
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pymongo
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pandas
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pandas
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tra-analysis
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tra-analysis
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dnspython
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pyinstaller
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requests
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pymongo
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numpy
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scipy
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scikit-learn
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six
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matplotlib
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pyparsing
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pandas
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kivy==2.0.0rc2
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kivy==2.0.0rc2
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@ -143,67 +143,67 @@ def main():
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warnings.filterwarnings("ignore")
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warnings.filterwarnings("ignore")
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# while (True):
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while (True):
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current_time = time.time()
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current_time = time.time()
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print("[OK] time: " + str(current_time))
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print("[OK] time: " + str(current_time))
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config = load_config("red-alliance-analysis\data-analysis\config.json")
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config = load_config("config.json")
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competition = config["competition"]
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competition = config["competition"]
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match_tests = config["statistics"]["match"]
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match_tests = config["statistics"]["match"]
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pit_tests = config["statistics"]["pit"]
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pit_tests = config["statistics"]["pit"]
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metrics_tests = config["statistics"]["metric"]
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metrics_tests = config["statistics"]["metric"]
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print("[OK] configs loaded")
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print("[OK] configs loaded")
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print("[OK] starting threads")
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print("[OK] starting threads")
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cfg_max_threads = config["max-threads"]
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cfg_max_threads = config["max-threads"]
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sys_max_threads = os.cpu_count()
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sys_max_threads = os.cpu_count()
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if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
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if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
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alloc_processes = sys_max_threads + cfg_max_threads
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alloc_processes = sys_max_threads + cfg_max_threads
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elif cfg_max_threads > 0 and cfg_max_threads < 1:
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elif cfg_max_threads > 0 and cfg_max_threads < 1:
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alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
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alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
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elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
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elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
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alloc_processes = cfg_max_threads
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alloc_processes = cfg_max_threads
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elif cfg_max_threads == 0:
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elif cfg_max_threads == 0:
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alloc_processes = sys_max_threads
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alloc_processes = sys_max_threads
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else:
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else:
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print("[Err] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
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print("[Err] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
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exit()
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exit()
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# exec_threads = Pool(processes = alloc_processes)
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exec_threads = Pool(processes = alloc_processes)
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# print("[OK] " + str(alloc_processes) + " threads started")
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print("[OK] " + str(alloc_processes) + " threads started")
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apikey = config["key"]["database"]
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apikey = config["key"]["database"]
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tbakey = config["key"]["tba"]
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tbakey = config["key"]["tba"]
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print("[OK] loaded keys")
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print("[OK] loaded keys")
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previous_time = get_previous_time(apikey)
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previous_time = get_previous_time(apikey)
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print("[OK] analysis backtimed to: " + str(previous_time))
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print("[OK] analysis backtimed to: " + str(previous_time))
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print("[OK] loading data")
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print("[OK] loading data")
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start = time.time()
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start = time.time()
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match_data = load_match(apikey, competition)
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match_data = load_match(apikey, competition)
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pit_data = load_pit(apikey, competition)
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pit_data = load_pit(apikey, competition)
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print("[OK] loaded data in " + str(time.time() - start) + " seconds")
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print("[OK] loaded data in " + str(time.time() - start) + " seconds")
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print("[OK] running match stats")
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print("[OK] running match stats")
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start = time.time()
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start = time.time()
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matchloop(apikey, competition, match_data, match_tests)
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matchloop(apikey, competition, match_data, match_tests)
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print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
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print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
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print("[OK] running team metrics")
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print("[OK] running team metrics")
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start = time.time()
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start = time.time()
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metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
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metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
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print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
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print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
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print("[OK] running pit analysis")
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print("[OK] running pit analysis")
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start = time.time()
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start = time.time()
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pitloop(apikey, competition, pit_data, pit_tests)
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pitloop(apikey, competition, pit_data, pit_tests)
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print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
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print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
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set_current_time(apikey, current_time)
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set_current_time(apikey, current_time)
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print("[OK] finished all tests, looping")
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print("[OK] finished all tests, looping")
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# clear()
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# clear()
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def clear():
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def clear():
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37
src/superscript.spec
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37
src/superscript.spec
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# -*- mode: python ; coding: utf-8 -*-
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block_cipher = None
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a = Analysis(['superscript.py'],
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pathex=['/workspaces/tra-data-analysis/src'],
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binaries=[],
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datas=[],
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hiddenimports=[
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"dnspython",
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"sklearn.utils._weight_vector",
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"requests",
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],
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hookspath=[],
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runtime_hooks=[],
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excludes=[],
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win_no_prefer_redirects=False,
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win_private_assemblies=False,
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cipher=block_cipher,
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noarchive=False)
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pyz = PYZ(a.pure, a.zipped_data,
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cipher=block_cipher)
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exe = EXE(pyz,
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a.scripts,
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a.binaries,
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a.zipfiles,
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a.datas,
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[],
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name='superscript',
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debug=False,
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bootloader_ignore_signals=False,
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strip=False,
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upx=True,
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upx_exclude=[],
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runtime_tmpdir=None,
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console=True )
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