def splitGeneExpressionCSV(GENE_NAME, nprocs):
filename = getGeneFileName(GENE_NAME)
ave, res = divmod(countLinesCSV(filename), int(nprocs))
print 'Splitting file %s ' % filename
csv_splitter.split(filehandler=open(filename),
output_name_template=GENE_NAME + '_part_%s.csv',
output_path=WORKING_DIR,
row_limit=ave)
def split_table_files(self, split_file):
if os.path.isdir("../data_store/"):
shutil.rmtree("../data_store/")
os.mkdir("../data_store/")
for table_def in table_data.table_data.values():
print("Creating " + table_def["name"]) + " data store files..."
if not os.path.isdir("../data_store/" + table_def["name"]):
os.mkdir("../data_store/" + table_def["name"])
if split_file:
csv_splitter.split(
open("../data/" + table_def["data_loc"],
"r"), ",", 100, table_def["name"] + "_%s.csv",
"../data_store/" + table_def["name"], False)
else:
shutil.copy2("../data/" + table_def["data_loc"],
"../data_store/" + table_def["name"])
table_def[
"data_store"] = "../data_store/" + table_def["name"] + "/"
table_def["data_files"] = os.listdir("../data_store/" +
table_def["name"] + "/")
import csv_splitter
csv_splitter.split(
open(
'/home/josh/python/SNLP/yelp_dataset_challenge_round9/yelp_academic_dataset_review.csv',
'r'))
#step 1 - setup (write the headers) and close the files
readFile = open('../datafiles/SFPermitData/Building_Permits.csv', 'r')
reader = csv.DictReader(readFile)
newFilePath = '../datafiles/SFPermitData/Building_Permits_Extended.csv'
if os.path.isfile(newFilePath):
os.remove(newFilePath) #prevents us from re-editing same file
writeFile = open(newFilePath, 'w')
headerWriter = csv.writer(writeFile, lineterminator='\n')
headerWriter.writerow(columnHeaders)
readFile.close()
writeFile.close()
#after initial setup, split the files
csv_splitter.split(open('../datafiles/SFPermitData/Building_Permits.csv',
'r'),
output_path='../datafiles/SFPermitData/Split/')
#get housing data for all the split files
pool.map(get_housing_data,
[f for f in os.listdir('../datafiles/SFPermitData/Split/')])
#now, write them back to the original
writeFile = open(newFilePath, 'w')
writer = csv.DictWriter(writeFile,
lineterminator='\n',
fieldnames=columnHeaders)
for fileName in os.listdir('../datafiles/SFPermitData/SplitExtended/'):
readFile = open('../datafiles/SFPermitData/SplitExtended/' + fileName)
reader = csv.DictReader(readFile)
for row in reader:
toWrite = {}
def main(path):
filePath = path
csv_splitter.split(open(filePath, 'r'), ',', 300000, 'youtube_%s.csv',
'./output/', True)
def split(args):
file_to_split = args.file
with open(file_to_split, 'r') as f:
csv_splitter.split(f);
return split
conn.cursor().execute('USE ROLE ACCOUNTADMIN')
sql = "remove @DDB_STG01/customer pattern ='.*.csv.gz'"
conn.cursor().execute(sql)
conn.close()
# -- <) ===============================================================================
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# M A I N F L O W
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
log_file_setup()
connection_parameters = args_to_properties(sys.argv)
# Split LARGE files
csv_splitter.split(connection_parameters['largefile'])
DATABASE = connection_parameters["database"]
SCHEMA = connection_parameters["schema"]
STAGE = connection_parameters["stage"]
FILEFORMAT = connection_parameters["fileformat"]
LARGEFILE = connection_parameters["largefile"]
#========================================================================================
# STEP 1 - Move split files to the Stage Location in Snowflake
# Define the list of variables which determine the data that will be loaded
#========================================================================================
splittedFIles = csv_file = 'C:/Users/north/OneDrive/Documents/Snowflake/SampleData/SplitFIleFdr/*.csv'
variablesList = [{
'sourceLocation': f'{splittedFIles}',
'destinationTable': f'{STAGE}/customer/'
