new_agenda.md

in this we want to combine all the files of this repo in the folder /trenmaster into one file by combining all the individual classes that are present in all the files

we want to have this kind of methods for the combined class

1: authenticate : here this method chekcs if the user has already saved object of the kite zeroddha type using joblib library if yes then load it and check if the authentication is valid if not then he should login using the code given in current files using zerodha and save this object locally using joblib so that it can be loaded again to get authentication when this program runs.

2 : load_data : in this the argument should be a symbol name of a stock that user can enter and then the data can be achieved by the authentication object that has zerodha access after which the data is saved locally using the symbol name of the stock using joblib library. in this it should first check if the user is logged in or not if not then run authetication method first.

3 : train_model : in this the symbol name of a stock should be enterd as argument and training transformet paramenters. after which it should check for the locally saved data of the given symbol in the save directory , if not availablle then it should run load_data function to get the data of given symbol for last 30 days. then it should start training if data found in appropriate directory of given symbol with given transformer paramenters. after the completion of training of the model it should save the model to models directory with name as symbol name of the given stock name.

4 : inferance_model : in this method the arguments shuold be the name of the symbol of the stock that we want to run the prediction model and the date time range for which we are predicting the future values of the model. here consider that the date time range should take input as upto which date and time it should run prediction as taking current date and time as from and the user entered valued as to date time. after getting this data from the arguments it should load the authentication object that is saved locally using joblib and check if alreay autheticated if not then run authentication method to authnticate. then it should load the model of given symbol from the models directiry and then run inference from given data and arguments. after this it should show appropriate graphs and tabular data to analyze the results