def automateImageProcessing(self, eachAction):
try:
path = self.openPathFile()
eachActionValue = GeneralExceptionHandling.getJsonData(GeneralExceptionHandling, 'open', eachAction)
if eachActionValue:
if len(eachActionValue)>1:
pathValue = GeneralExceptionHandling.getJsonData(GeneralExceptionHandling
, eachActionValue[0], path)
if pathValue:
if MainRPA.imageProcessing(MainRPA, pathValue, eachActionValue[1]):
print('image processing complete')
return True
else:
print('image processing faild')
return False
else:
print('json error in automateImageProcessing')
return False
else:
print('error in array size in automateImageProcessing greater than 1', eachActionValue)
else:
print('json error in automateImageProcessing')
return False
except Exception as e:
print('error in automateImageProcessing', e)
return False
def loadValidtionLocatorToDb(self, layer_name):
try:
validationFile = self.LocatorDirectory + layer_name + '_validation.json'
generalExceptionHandling = GeneralExceptionHandling()
validation = generalExceptionHandling.readFileAndReturnJson(
validationFile)
# print(validation.keys())
df = pd.DataFrame()
for eachKey in validation.keys():
# print(validation[eachKey])
locatorData = validation[eachKey]
for locatorId, locator in locatorData.items():
if len(df.columns) > 0:
temDataFrame = pd.DataFrame({
'locatorData': locator,
'locator_id': locatorId
})
df = df.append(temDataFrame)
else:
df['locatorData'] = locator
df.loc[df['locatorData'] == locator,
'locator_id'] = locatorId
df.loc[df['locatorData'] == locator, 'flag'] = eachKey
# print(df)
if self.dataFrameToDb(df, layer_name + '_validation'):
return True
else:
return False
except Exception as e:
print('error in loadValidationLocatorToDb in LocatorFromDB', e)
return False
def __init__(self, path):
self.path = path
self.dbOption = GeneralExceptionHandling.getJsonDataRecurssive(
GeneralExceptionHandling, 'DB', self.path)
self.LocatorDirectory = GeneralExceptionHandling.getJsonDataRecurssive(
GeneralExceptionHandling, 'DataFetching,filesPath', self.path)
self.getConnection()
self.layerConnectorName = 'datafeth_locator_'
self.layerConnect = self.getLocatorFromDb('layer_connect')
if self.layerConnect.empty:
print('not data in layer_connect')
exit()
def __init__(self, path):
CsvHandling.__init__(self)
GeneralExceptionHandling.__init__(self)
self.path = path
self.locatorValidationArray = dict()
self.dataFetchingValidationLocatorPath = self.getJsonDataRecurssive(
'DataFetching,validationLocator', self.path)
self.dataFetchingFilesPath = self.getJsonDataRecurssive(
'DataFetching,filesPath', self.path)
self.sqlConnect = SqlConnect(path)
self.validationDebug = False
def reSelect(self, patternBuild, sourceDataProcessed, sourceData) -> str:
""":returns regualr expression out put of :var patternBuild
:argument patternBuild is a regular expression
:argument sourceDataProcessed is regular expression applying data
:argument sourceData is original data
:returns matched string if not :returns False"""
try:
import re
patternBuild = re.sub(r'\d', '\d', patternBuild)
searhcObj = re.search(patternBuild, sourceDataProcessed)
# print('pattern:', patternBuild)
if searhcObj:
patternMatch = searhcObj.group()
patternMatch = self.regularExpressionHandling(patternMatch, 0)
sourceData = sourceData.replace('\n', ' ')
sourceFileMatch = re.search(patternMatch, sourceData, re.IGNORECASE)
if sourceFileMatch:
sourceFileMatchString = GeneralExceptionHandling.regularExpressionHandling(GeneralExceptionHandling, patternMatch, 1)
return sourceFileMatchString
else:
return False
else:
return False
except Exception as e:
print('error in searchDataInFuzzySearch\n', e)
print(patternBuild)
print('patter: ', patternMatch)
print('patter other: ', sourceData)
def imageProcessing(self, options, imageName):
try:
from imageProcessing.imageProcessing import ImageProcessing
imageProcessingObj = ImageProcessing()
imageLocation = GeneralExceptionHandling.getJsonData(
GeneralExceptionHandling, 'imageLocation', options)
if imageLocation:
openCvImage = imageProcessingObj.openCVReadImage(
imageLocation, imageName)
contors = imageProcessingObj.getContours(
imageProcessingObj.openCVReadImage(imageLocation,
imageName))
if imageProcessingObj.drawContours(openCvImage, contors):
return True
else:
return False
else:
print('json error image location')
return False
except Exception as e:
print('error from imageProcessing', e)
return False
def setUp(self) -> None:
# initial run
pathFile = open('path.json', 'r')
path = json.loads(pathFile.read())
pathFile.close()
path = GeneralExceptionHandling.getJsonData(GeneralExceptionHandling, 'linux', path)
print('begin')
self.locatorValidation = LocatorValidation(path)
def ocrImage(self, imageName, imageExtension, ocrDocumentName,
imageFilePath, ocrFilePath):
try:
print('saving ocr: ', ocrFilePath + ocrDocumentName + '.txt')
DrectoryHandling.createDirectory(DrectoryHandling, ocrFilePath)
fp = open(ocrFilePath + ocrDocumentName + '.txt', 'w')
tesseract = GeneralExceptionHandling.getJsonData(
GeneralExceptionHandling, 'imagProcessing', self.path)
tesseract = GeneralExceptionHandling.getJsonData(
GeneralExceptionHandling, 'tesseract', tesseract)
if tesseract:
if tesseract == 'None':
ocrData = self.getOcr(imageFilePath + imageName + '.' +
imageExtension)
if ocrData:
fp.write(ocrData)
fp.write(
pytesseract.image_to_string(imageFilePath +
imageName + '.' +
imageExtension))
fp.close()
return True
else:
ocrData = self.getOcr(
imageFilePath + imageName + '.' + imageExtension,
tesseract)
if ocrData:
fp.write(ocrData)
fp.close()
else:
print('ocr handling failed')
fp.close()
return False
else:
return False
return True
except Exception as e:
print('Error in ocrImage', e)
return False
def automate(self, option):
try:
processFile = open('process.json', 'r')
# process = json.loads(processFile.read())[option]
process = GeneralExceptionHandling.getJsonData(GeneralExceptionHandling, option, json.loads(processFile.read()))
processFile.close()
if process:
for eachProcessLine in process:
if not self.processLine(eachProcessLine):
return False
return True
else:
print('json error in automate in automation')
return False
except Exception as e:
print('error in automate', e)
return False
def automateFirefox(self, values):
try:
path = self.openPathFile()
openValue = GeneralExceptionHandling.getJsonData(GeneralExceptionHandling, 'open', values)
if openValue:
if len(openValue) >3:
if MainRPA.run(MainRPA, openValue[0], openValue[1], path, openValue[2], openValue[3]):
print('image processing complete')
return True
else:
print('image processing faild')
return False
else:
print('open array size should be 4', values)
return False
else:
print('json error in automateFirefox in automation')
return False
except Exception as e:
print('error in auromatefirefox')
def __init__(self, path):
GeneralExceptionHandling.__init__(self)
self.path = path
self.stringMatchConfidence = 90
self.fuzzySearchOptimumLength = 6
""" threshold will set to 90 and l_dist will be 0 for precision while less than fuzzySearchOptimumLength """
try:
pathFile = open('path.json', 'r')
path = json.loads(pathFile.read())
pathFile.close()
if len(sys.argv) == 4:
if sys.argv[3] == 'rpa':
if MainRPA.run(MainRPA, sys.argv[1], sys.argv[2], path):
print('Process complete')
else:
print('Process exit with error')
elif len(sys.argv) == 3:
if sys.argv[2] == 'imageProcessing':
print('imageProcessing', sys.argv)
# path = path[sys.argv[1]]
path = GeneralExceptionHandling.getJsonData(
GeneralExceptionHandling, sys.argv[1], path)
if path:
if MainRPA.imageProcessing(MainRPA, path, 'geek'):
print('image processing complete')
else:
print('image processing faild')
else:
exit()
elif sys.argv[2] == 'dataFetching':
try:
from DataFetching.DataFetching import DataFetchingMain
pathValues = GeneralExceptionHandling.getJsonData(
GeneralExceptionHandling, sys.argv[1], path)
if pathValues: