def backupToZip(folder):
# Backup the entire contents of "folder" into a ZIP file.
folder = os.path.abspath(folder) # make sure folder is absolute
# Figure out the filename this code should use based
# on what files already exist.
number = 1
while True:
zipFilename = os.path.basename(folder) + '_' + str(number) + '.zip'
if not os.path.exists(zipFilename):
break
number = number + 1
# Create zip file
print('Creating %s...' % (zipFilename))
backupZip = zipfile.zipFile(zipFilename, 'w')
# Walk the entire folder tree and compress the files in each folder.
for foldername, subfolders, filenames in os.walk(folder):
print('Adding files in %s...' % (foldername))
# Add the current folder to the ZIP file.
backupZip.write(foldername)
#Add all the files in this folder to the ZIP file.
for filename in filenames:
newBase / os.path.basename(folder) + '_'
if filename.startswith(newBase) and filename.endwith('.zip'):
continue # don't backup the backup ZIP files
backupZip.write(os.path.join(foldername,filename))
backupZip.close()
print('Done')
def generateMetagenesList(self, ROOT_DIRECTORY, clusterNumber, omicList=None):
"""
This function obtains the metagenes for each pathway in KEGG based on the input values.
@param {type}
@returns
"""
# STEP 1. EXTRACT THE COMPRESSED FILE WITH THE MAPPING FILES
zipFile(self.getOutputDir() + "/mapping_results_" + self.getJobID() + ".zip").extractall(path=self.getTemporalDir())
# STEP 2. GENERATE THE DATA FOR EACH OMIC DATA TYPE
filtered_omics = self.geneBasedInputOmics
if omicList:
filtered_omics = [inputOmic for inputOmic in self.geneBasedInputOmics if inputOmic.get("omicName") in omicList]
for inputOmic in filtered_omics:
try:
# STEP 2.1 EXECUTE THE R SCRIPT
logging.info("GENERATING METAGENES INFORMATION...CALLING")
inputFile = self.getTemporalDir() + "/" + inputOmic.get("omicName") + '_matched.txt'
# Select number of clusters, default to dynamic
kClusters = str(dict(clusterNumber).get(inputOmic.get("omicName"), "dynamic"))
check_call([
ROOT_DIRECTORY + "common/bioscripts/generateMetaGenes.R",
'--specie="' + self.getOrganism() +'"',
'--input_file="' + inputFile + '"',
'--output_prefix="'+ inputOmic.get("omicName") + '"',
'--data_dir="'+ self.getTemporalDir() + '"',
'--kegg_dir="'+ KEGG_DATA_DIR + '"',
'--sources_dir="' + ROOT_DIRECTORY + '/common/bioscripts/"',
'--kclusters="' + kClusters + '"' if kClusters.isdigit() else ''], stderr=STDOUT)
# STEP 2.2 PROCESS THE RESULTING FILE
# Reset all pathways metagenes for the omic
map(lambda pathway: pathway.resetMetagenes(inputOmic.get("omicName")), self.matchedPathways.values())
with open(self.getTemporalDir() + "/" + inputOmic.get("omicName") + "_metagenes.tab", 'rU') as inputDataFile:
for line in csv_reader(inputDataFile, delimiter="\t"):
if self.matchedPathways.has_key(line[0]):
self.matchedPathways.get(line[0]).addMetagenes(inputOmic.get("omicName"), {"metagene": line[1], "cluster": line[2], "values" : line[3:] })
inputDataFile.close()
except CalledProcessError as ex:
logging.error("STEP2 - Error while generating metagenes information for " + inputOmic.get("omicName"))
os_system("mv " + self.getTemporalDir() + "/" + "*.png " + self.getOutputDir())
return self
def Archive_Controller(arg):
cwd = os.getcwd()
CSV_Write()
# Create archive directory for current time
Current_time = datetime.datetime.now()
directory = '/home/pi/datalogger/Archive/'
if not os.path.exists(directory):
os.makedirs(directory)
# Create archive
zf_name = directory + str(Current_time) + '_Archive.zip'
#zf = zipfile.ZipFile(zf_name,'w')
# Write files to zip archive and compress
try:
with zipfile.zipFile(zf_name, 'w') as zf:
for folder, subfolders, files in os.walk(cwd):
for file in files:
if file.endswith('.log') or file.endswith(
'.db') or file.endswith('.csv'):
zf.write(os.path.join(folder, file),
directory,
compress_type=zipfile.ZIP_DEFLATED)
#zf.write('UPS_DB.sql', zipfile.ZIP_STORED)# Write sql database to zip file
#zf.write('UPS_Messages.log', zipfile.ZIP_STORED)# Write log to zip file
#zf.write('UPS_DB.csv', zipfile.ZIP_STORED)# Write csv file to zip file
zf.close()
except:
logger.error('Could not write files to zip archive')
try:
os.remove('UPS_Messages.log') # Delete log file
os.remove('UPS_DB.csv') # Delete csv file
except:
logger.error('Could not delete log and csv files')
try:
conn = sqlite3.connect('UPS_DB.db')
c = conn.cursor()
c.execute("DELETE FROM UPS_DB WHERE Date <= date('now','-1 day')"
) # Delete sql database older than one week
conn.close()
except:
logger.error('Could not update SQL database')
import zipfile
import os
# Definir la ruta de carpeta a analizar
carpeta = "c:\Users\juansebastian\Documents\Tareas"
# Crear un objeto zipFile y agreegar la ruta donde se guardara
zip = zipfile.zipFile('compress.zip', 'w')
# Definir las extensiones de los archivos a comprimir
matchList = ['.png', '.txt', 'wmv', '.py']
# Recorrer los archivos de la carpeta
for archivo in os.listdir(carpeta):
for ext in matchList:
# Si la extension conicide la agrega al zip
if archivo.endswith(ext):
zip.write(os.path.join(carpeta, archivo))
# Cerrar el archivo para guardarlo
zip.close()
def main():
# Set variables that are global (mostly for writing not neded for reading)
global timeStart
# Get user input
try:
inputArray = getInputJSON()
inputKey = inputArray[0]
inputData = json.loads(inputArray[1])
inputValue = inputData.get(inputKey)
except KeyboardInterrupt:
print("")
exit(0)
# Imput conformation
conf = getConformation(f'\nThe key "{inputKey}" will be set to '+str(inputValue).replace("'",'"')+'. This will result in:\n'+str(inputData).replace("'",'"')+'\n\nAre you sure this is what you want?')
if conf == False:
print('Exiting...')
exit(0)
print("\n")
# Start timer
timeStart = time.time()
# Get zips in current and lower dirs
allZips = searchDirFor('./', '', '.zip')
lenAllZips = len(allZips)
displayArray(allZips, f'Found {lenAllZips} zip'+ ('s' if lenAllZips != 1 else ''))
# Gets temporary directory
tempDir = './temp'
while os.path.isdir(tempDir) == 1:
print(f'{timeStamp(timeStart)} Diractory "{tempDir}/" already exists, looking for new temp directory')
tempDir += str(random.randint(0,9))
# Processes all the zip files if found
failed = [['Operation', 'File', 'Error type', 'Error value']]
if lenAllZips > 0:
print(f'{timeStamp(timeStart)} Using temporary directory: "{tempDir}/"')
for i in range(lenAllZips):
# Get temporary current directory
tempCurrentDir = os.path.join(tempDir, getFileName(allZips[i]))
# Extract currently processing zip file
print(f'\n{timeStamp(timeStart)} Extracting zip {i+1}: "{allZips[i]}" -> "{tempCurrentDir}/"', end=printEnd())
with zipFile(allZips[i], 'r') as zip:
try:
zip.extractall(tempCurrentDir)
except Exception as e:
failed.append(["extracting", allZips[i], type(e).__name__, str(e)])
finally:
zip.close()
print('done!')
# Get JSON files of extracted zip
allJsons = searchDirFor(tempCurrentDir, '', '.json')
lenAllJsons = len(allJsons)
displayArray(allJsons, f'Found {lenAllJsons} json'+ ('s' if lenAllJsons != 1 else ''))
if lenAllJsons > 0:
# Look threw all JSONs and replace specefied thing
didJsonsChange = 0
for j in range(lenAllJsons):
try:
hasJsonChanged = jsonChangeValue(allJsons[j], inputKey, inputValue)
if hasJsonChanged == 1:
didJsonsChange = 1
except Exception as e:
print("failed!")
failed.append(["changing json", allJsons[j], type(e).__name__, str(e)])
# Rezip extracted zip if something changed
if didJsonsChange == 1:
print(f'{timeStamp(timeStart)} Writing: "{tempCurrentDir}/*" -> "{allZips[i]}"', end=printEnd())
with zipFile(allZips[i], 'w') as zip:
try:
for j in os.listdir(tempCurrentDir):
zip.write(os.path.join(tempCurrentDir, j), arcname=j)
except Exception as e:
failed.append(["zipping", os.path.join(tempCurrentDir, j), type(e).__name__, str(e)])
finally:
zip.close()
print('done!')
# Remove temp dir for zip
print(f'{timeStamp(timeStart)} Removing: "{tempCurrentDir}"', end=printEnd())
shutil.rmtree(tempCurrentDir)
print('done!')
# Remove temp dir fully
print(f'\n{timeStamp(timeStart)} Removing the temp directory: "{tempDir}"', end=printEnd())
try:
os.rmdir(tempDir)
print('done!')
except OSError as e:
if e.errno == 41:
# Direcory not empty. Removing it with remaining tree
shutil.rmtree(tempDir)
else:
print('failed!')
failed.append(["removing", tempDir, type(e).__name__, str(e)])
print('\n'*2+'-='*5, 'SCRIPT FINISHED', '=-'*5+'\n')
lenFailed = len(failed)
if lenFailed > 1:
temp = 'S' if lenFailed == 1 else ''
print(f'WITH ERROR{temp}'+'=-'*4)
for i in range(lenFailed-1):
print(f'\tGot {failed[i+1][2]} error "{failed[i+1][3]}" while {failed[i+1][0]} file "{failed[i+1][1]}"\n')
print(f'\nExecution of script took: {round(time.time()-timeStart, 6)} seconds\n')
x = layers.Dropout(0.2)(x)
#输出层
x = layers.Dense(1, activation='sigmoid')(x)
model = Model(pre_trained_model.input, x) #创建模型
model.compile(optimizer=RMSprop(lr=0.0001),
loss='binary_crossentropy',
metrics=['acc']) #设置优化算法，损失函数，评价指标
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import os
import zipfile
local_zip = '//tmp/cats_and_dogs_filtered.zip'
zip_ref = zipfile.zipFile(local_zip, 'r')
zip_ref.extractall('tmp')
zip_ref.close()
#数据文件
base_dir = '/tmp/cats_and_dogs_filtered'
train_dir = os.path.join(base_dir, 'train')
validation_dir = os.path.join(base_dir, 'validation')
train_cats_dir = os.path.join(train_dir, 'cats') #训练集-猫目录
train_dogs_dir = os.path.join(train_dir, 'dogs') #训练集-狗目录
validation_cats_dir = os.path.join(validation_dir, 'cats') #开发集-猫目录
validation_dogs_dir = os.path.join(validation_dir, 'dogs') #开发集-狗目录
train_cat_fnames = os.listdir(train_cats_dir)