# 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