class pred_validation:
def __init__(self, path):
self.raw_data = Prediction_Data_validation(path)
self.dataTransform = dataTransformPredict()
self.dBOperation = dBOperation()
self.file_object = open("Prediction_Logs/Prediction_Log.txt", 'a+')
self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.log_writer.log(
self.file_object,
'Start of Validation on files for prediction!!')
#extracting values from prediction schema
column_names, noofcolumns = self.raw_data.valuesFromSchema()
#validating column length in the file
self.raw_data.validateColumnLength(noofcolumns)
#validating if any column has all values missing
self.raw_data.validateMissingValuesInWholeColumn()
self.log_writer.log(self.file_object,
"Raw Data Validation Complete!!")
self.log_writer.log(
self.file_object,
"Creating Prediction_Database and tables on the basis of given schema!!!"
)
#create database with given name, if present open the connection! Create table with columns given in schema
self.dBOperation.createTableDb('Prediction', column_names)
self.log_writer.log(self.file_object, "Table creation Completed!!")
self.log_writer.log(self.file_object,
"Insertion of Data into Table started!!!!")
#insert csv files in the table
self.dBOperation.insertIntoTableGoodData('Prediction')
self.log_writer.log(self.file_object,
"Insertion in Table completed!!!")
self.log_writer.log(self.file_object,
"Deleting Good Data Folder!!!")
#Delete the good data folder after loading files in table
self.raw_data.deleteExistingGoodDataTrainingFolder()
self.log_writer.log(self.file_object,
"Good_Data folder deleted!!!")
self.log_writer.log(
self.file_object,
"Moving bad files to Archive and deleting Bad_Data folder!!!")
#Move the bad files to archive folder
self.raw_data.moveBadFilesToArchiveBad()
self.log_writer.log(
self.file_object,
"Bad files moved to archive!! Bad folder Deleted!!")
self.log_writer.log(self.file_object,
"Validation Operation completed!!")
self.log_writer.log(self.file_object,
"Extracting csv file from table")
#export data in table to csvfile
self.dBOperation.selectingDatafromtableintocsv('Prediction')
except Exception as e:
raise e
class pred_validation:
def __init__(self, path):
self.raw_data = Prediction_Data_validation(path)
self.dataTransform = dataTransformPredict()
self.dBOperation = dBOperation()
self.file_object = open("Prediction_Logs/Prediction_Log.txt", 'a+')
self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.log_writer.log(
self.file_object,
'Start of Validation on files for prediction!!')
LengthOfDateStampInFile, LengthOfTimeStampInFile, column_names, noofcolumns = self.raw_data.valuesFromSchema(
)
regex = self.raw_data.manualRegexCreation()
self.raw_data.validationFileNameRaw(regex, LengthOfDateStampInFile,
LengthOfTimeStampInFile)
self.raw_data.validateColumnLength(noofcolumns)
self.raw_data.validateMissingValuesInWholeColumn()
self.log_writer.log(self.file_object,
"Raw Data validation complete!!")
self.log_writer.log(self.file_object,
"Starting Data transformation!!")
self.dataTransform.replaceSingleQuotesToDouble()
self.log_writer.log(self.file_object,
"DataTransformation Completed!!!")
self.log_writer.log(
self.file_object,
"Creating Prediction_Database and tables on the basis of given schema!!!"
)
self.dBOperation.createTableDb('Prediction', column_names)
self.log_writer.log(self.file_object, "Table creation Completed!!")
self.log_writer.log(self.file_object,
"Insertion of Data into Table started!!!!")
self.dBOperation.insertIntoTableGoodData('Prediction')
self.log_writer.log(self.file_object,
"Insertion in Table completed!!!")
self.log_writer.log(self.file_object, "Deleting Good Data Folder")
self.raw_data.deleteExistingGoodDataPredictingFolder()
self.log_writer.log(self.file_object,
"Good_Data folder deleted!!!")
self.log_writer.log(
self.file_object,
"Moving bad files to Archive and deleting Bad_Data folder!!!")
self.raw_data.moveBadFilesToArchiveBad()
self.log_writer.log(
self.file_object,
"Bad files moved to archive!! Bad folder Deleted!!")
self.log_writer.log(self.file_object,
"Validation Operation completed!!")
self.log_writer.log(self.file_object,
"Extracting csv file from table")
self.dBOperation.selectingDatafromtableintocsv('Prediction')
except Exception as e:
raise e
class pred_validation:
def __init__(self):
self.raw_data = Prediction_Data_validation()
self.dataTransform = dataTransformPredict()
self.dBOperation = dBOperation()
self.file_object = 'wafer_log' # open("Prediction_Logs/Prediction_Log.txt", 'a+')
self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.log_writer.log(
self.file_object,
'Start of Validation on files for prediction!!')
# extracting values from prediction schema
LengthOfDateStampInFile, LengthOfTimeStampInFile, column_names, noofcolumns = self.raw_data.valuesFromSchema(
)
# getting the regex defined to validate filename
regex = self.raw_data.manualRegexCreation()
# validating filename of prediction files
self.raw_data.validationFileNameRaw(regex, LengthOfDateStampInFile,
LengthOfTimeStampInFile)
# validating column length in the file
self.raw_data.validateColumnLength(noofcolumns)
# validating if any column has all values missing
self.raw_data.validateMissingValuesInWholeColumn()
self.log_writer.log(self.file_object,
"Prediction Raw Data Validation Complete!!")
self.log_writer.log(self.file_object,
("Starting Data Transforamtion!!"))
# replacing blanks in the csv file with "Null" values to insert in table
self.dataTransform.replaceMissingWithNull()
self.log_writer.log(self.file_object,
"DataTransformation Completed!!!")
# self.log_writer.log(self.file_object,
# "Creating Prediction_Database and tables on the basis of given schema!!!")
# # create database with given name, if present open the connection! Create table with columns given in schema
# self.dBOperation.createTableDb('Prediction', column_names)
# self.log_writer.log(self.file_object, "Table creation Completed!!")
# self.log_writer.log(self.file_object, "Insertion of Data into Table started!!!!")
# # insert csv files in the table
# self.dBOperation.insertIntoTableGoodData('Prediction')
# self.log_writer.log(self.file_object, "Insertion in Table completed!!!")
# self.log_writer.log(self.file_object, "Deleting Good Data Folder!!!")
# # Delete the good data folder after loading files in table
# self.raw_data.deleteExistingGoodDataTrainingFolder()
# self.log_writer.log(self.file_object, "Good_Data folder deleted!!!")
# self.log_writer.log(self.file_object, "Moving bad files to Archive and deleting Bad_Data folder!!!")
# # Move the bad files to archive folder
# self.raw_data.moveBadFilesToArchiveBad()
# self.log_writer.log(self.file_object, "Bad files moved to archive!! Bad folder Deleted!!")
self.log_writer.log(self.file_object,
"Validation Operation completed!!")
# self.log_writer.log(self.file_object, "Extracting csv file from table")
# # export data in table to csvfile
# self.dBOperation.selectingDatafromtableintocsv('Prediction')
except Exception as e:
raise e
class pred_validation:
def __init__(self, path):
self.raw_data = Prediction_Data_validation(path)
self.dBOperation = dBOperation()
self.file_object = open("Prediction_Logs/Prediction_Log.txt", 'a+')
self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.log_writer.log(
self.file_object,
'Start of Validation on files for prediction!!')
#extracting values from prediction schema
column_names, noofcolumns = self.raw_data.valuesFromSchema()
#getting the regex defined to validate filename
#regex = self.raw_data.manualRegexCreation()
#validating filename of prediction files
#self.raw_data.validationFileNameRaw(regex)
#validating number of columns
self.raw_data.validateColumnLength(noofcolumns)
#validating if any column has all values missing
#self.raw_data.validateMissingValuesInWholeColumn()
self.log_writer.log(self.file_object,
"Raw Data Validation Complete!!")
self.log_writer.log(
self.file_object,
"Creating Prediction_Database and collection on the basis of given schema!!!"
)
# create database with given name, if present open the connection! Create table with columns given in schema
collection = self.dBOperation.createCollection()
self.log_writer.log(self.file_object,
"collection creation Completed!!")
self.log_writer.log(
self.file_object,
"Insertion of Data into collection started!!!!")
# insert csv files in the collection
self.dBOperation.GoodDatainsertIntoCollection(collection)
self.log_writer.log(self.file_object,
"Insertion in collection completed!!!")
self.log_writer.log(self.file_object,
"Deleting Good Data Folder!!!")
# Delete the good data folder after loading files in table
self.raw_data.deleteExistingGoodDataPredictionFolder()
self.log_writer.log(self.file_object,
"Good_Data folder deleted!!!")
self.log_writer.log(
self.file_object,
"Moving bad files to Archive and deleting Bad_Data folder!!!")
# Move the bad files to archive folder
self.raw_data.moveBadFilesToArchive()
self.log_writer.log(
self.file_object,
"Bad files moved to archive!! Bad folder Deleted!!")
self.log_writer.log(self.file_object,
"Validation Operation completed!!")
self.log_writer.log(self.file_object,
"Extracting csv file from table")
# export data in table to csvfile
self.dBOperation.selectingDatafromCollectionintocsv(collection)
self.file_object.close()
except Exception as e:
raise e
class pred_validation:
def __init__(self, path, execution_id):
self.raw_data = Prediction_Data_validation(path, execution_id)
self.dataTransform = dataTransformPredict(execution_id)
self.dBOperationMongoDB = DbOperationMongoDB(execution_id)
#self.dBOperation = dBOperation(execution_id)
self.log_database = "wafer_prediction_log"
self.log_collection = "prediction_main_log"
self.execution_id = execution_id
#self.log_writer = logger.App_Logger()
self.logDB_write = App_LoggerDB(execution_id=execution_id)
self.az_blob_mgt = AzureBlobManagement()
#self.file_object = open("Prediction_Logs/Prediction_Log.txt", 'a+')
#self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.logDB_write.log(
self.log_database, self.log_collection,
'Start of Validation on files for prediction!!')
#extracting values from prediction schema
LengthOfDateStampInFile, LengthOfTimeStampInFile, column_names, noofcolumns = self.raw_data.valuesFromSchema(
)
#getting the regex defined to validate filename
regex = self.raw_data.manualRegexCreation()
#validating filename of prediction files
self.raw_data.validationFileNameRaw(regex, LengthOfDateStampInFile,
LengthOfTimeStampInFile)
#validating column length in the file
self.raw_data.validateColumnLength(noofcolumns)
#validating if any column has all values missing
self.raw_data.validateMissingValuesInWholeColumn()
self.logDB_write.log(self.log_database, self.log_collection,
"Raw Data Validation Complete!!")
self.logDB_write.log(self.log_database, self.log_collection,
("Starting Data Transforamtion!!"))
#replacing blanks in the csv file with "Null" values to insert in table
self.dataTransform.replaceMissingWithNull()
self.logDB_write.log(self.log_database, self.log_collection,
"DataTransformation Completed!!!")
self.logDB_write.log(
self.log_database, self.log_collection,
"Creating Prediction_Database and tables on the basis of given schema!!!"
)
#create database with given name, if present open the connection! Create table with columns given in schema
self.logDB_write.log(
self.log_database, self.log_collection,
"Creating database and collection if not exist then insert record"
)
#insert csv files in the table
self.dBOperationMongoDB.insertIntoTableGoodData(column_names)
self.logDB_write.log(self.log_database, self.log_collection,
"Insertion in Table completed!!!")
#self.logDB_write.log(self.log_database, self.log_collection,"Deleting Good Data Folder!!!")
#Delete the good data folder after loading files in table
#self.raw_data.deleteExistingGoodDataTrainingFolder()
#self.logDB_write.log(self.log_database, self.log_collection,"Good_Data folder deleted!!!")
self.logDB_write.log(
self.log_database, self.log_collection,
"Moving bad files to Archive and deleting Bad_Data folder!!!")
#Move the bad files to archive folder
print("moving bad files to archieve")
self.raw_data.moveBadFilesToArchiveBad()
self.logDB_write.log(
self.log_database, self.log_collection,
"Bad files moved to archive!! Bad folder Deleted!!")
self.logDB_write.log(self.log_database, self.log_collection,
"Validation Operation completed!!")
self.logDB_write.log(self.log_database, self.log_collection,
"Extracting csv file from table")
#export data in table to csvfile
self.dBOperationMongoDB.selectingDatafromtableintocsv()
except Exception as e:
raise e
class pred_validation:
def __init__(self,path):
self.raw_data = Prediction_Data_validation(path)
self.dataTransform = dataTransformPredict()
self.dBOperation = dBOperation()
self.file_object = open("Prediction_Logs/Prediction_Log.txt", 'a+')
self.log_writer = logger.App_Logger()
def prediction_validation(self):
try:
self.log_writer.log(self.file_object,'Start of Validation on files for prediction!!')
#extracting values from prediction schema
column_names,noofcolumns = self.raw_data.valuesFromSchema()
#getting the regex defined to validate filename
regex = self.raw_data.manualRegexCreation()
#validating filename of prediction files
self.raw_data.validationFileNameRaw(regex)
#validating column length in the file
self.raw_data.validateColumnLength(noofcolumns)
#validating if any column has all values missing
self.raw_data.validateMissingValuesInWholeColumn()
self.log_writer.log(self.file_object,"Raw Data Validation Complete!!")
self.log_writer.log(self.file_object,"Affan here")
self.log_writer.log(self.file_object,("Starting Data Transforamtion!!"))
#self.dataTransform.addQuotesToStringValuesInColumn()
#replacing blanks in the csv file with "Null" values to insert in table
self.dataTransform.EDA()
self.log_writer.log(self.file_object,"EDA Completed!!!")
self.log_writer.log(self.file_object,"DataTransformation Completed!!!")
column_names_Updated,noofcolumns = self.raw_data.valuesFromSchema_updated()
self.log_writer.log(self.file_object,"Creating Prediction_Database and tables on the basis of given schema!!!")
#create database with given name, if present open the connection! Create table with columns given in schema
#self.dBOperation.dataBaseConnection('Prediction')
#column_names_updated_after_EDA = ['PassengerId','Pclass','Sex','Age','SibSp','Parch','Fare','Embarked','Title']
#self.log_writer.log(self.file_object,"DB Conn Chk")
self.dBOperation.createTableDb('Prediction',column_names_Updated)
self.log_writer.log(self.file_object,"Table creation Completed!!")
self.log_writer.log(self.file_object,"Insertion of Data into Table started!!!!")
#insert csv files in the table
self.dBOperation.insertIntoTableGoodData('Prediction')
self.log_writer.log(self.file_object,"Insertion in Table completed!!!")
self.log_writer.log(self.file_object,"Deleting Good Data Folder!!!")
#Delete the good data folder after loading files in table
self.raw_data.deleteExistingGoodDataTrainingFolder()
self.log_writer.log(self.file_object,"Good_Data folder deleted!!!")
self.log_writer.log(self.file_object,"Moving bad files to Archive and deleting Bad_Data folder!!!")
#Move the bad files to archive folder
self.raw_data.moveBadFilesToArchiveBad()
self.log_writer.log(self.file_object,"Bad files moved to archive!! Bad folder Deletedaffan1!!")
self.log_writer.log(self.file_object,"Validation Operation completedaffan2!!")
self.log_writer.log(self.file_object,"Extracting csv file from table affan3")
#export data in table to csvfile
self.dBOperation.selectingDatafromtableintocsv('Prediction')
self.log_writer.log(self.file_object,"Selected data from table into csv affan")
except Exception as e:
raise e