def onThermostatValueWork(msg):
try:
msg.payload = msg.payload.decode("utf-8")
value = utils.parseFloat(msg.payload)
tags = utils.getTags(msg.topic)
except:
logger.error(
f'The message: "{msg.payload}" cannot be processed. Topic: "{msg.topic}" is malformed. Ignoring data'
)
return
try:
fields = {tags["endpoint"]: value}
tagsToSave = ["locationId", "sensorId"]
measurement = "thermostatData"
influxDb.writeData(
measurement,
utils.selectTags(tagsToSave, tags),
fields,
retentionPolicy="3years",
)
except:
logger.error(
f"onThermostatValueWork message failed. message: {msg.payload}. Exception: ",
exc_info=True,
)
def onStatusWork(msg):
try:
msg.payload = msg.payload.decode("utf-8")
status = utils.decodeStatus(msg.payload)
tags = utils.getTags(msg.topic)
except:
logger.error(
f'The message: "{msg.payload}" cannot be processed. Topic: "{msg.topic}" is malformed. Ignoring data',
extra={"area": "status"},
)
return
try:
fields = {"status": status}
tagsToSave = ["locationId", "deviceId"]
measurement = "sensorsData"
influxDb.writeData(
measurement,
utils.selectTags(tagsToSave, tags),
fields,
retentionPolicy="3years",
)
except:
logger.error(
f"onStatusWork message failed. message: {msg.payload}. Exception: ",
exc_info=True,
extra={"area": "status"},
)
def onValueWork(msg):
# Avoid string values as mathematical operations cant
# be made afterwards
try:
msg.payload = msg.payload.decode("utf-8")
value = utils.parseFloat(msg.payload)
tags = utils.getTags(msg.topic)
except:
logger.error(
f'The message: "{msg.payload}" cannot be processed. Topic: "{msg.topic}" is malformed. Ignoring data',
extra={"area": "value"},
)
return
try:
fields = {"value": value}
tagsToSave = ["locationId", "sensorId"]
measurement = "sensorsData"
influxDb.writeData(
measurement,
utils.selectTags(tagsToSave, tags),
fields,
retentionPolicy="raw",
)
except:
logger.error(
f"onValueWork message failed. message: {msg.payload}. Exception: ",
exc_info=True,
extra={"area": "value"},
)
def local():
file = request.files['file']
if file and checkFile(file.filename):
fn = request.form['filename']
name = stripPunctuation(fn)
ext = file.filename.rsplit('.',1)[1]
filename = secure_filename(name+"."+ext)
filename = repeatedName(filename,0,False)
file.save(os.path.join(path,filename))
uid = user.get_UID(session['username'])
link = utils.uploadPic (os.path.join(path,filename))
tags = utils.getTags(link, Access_token)
stringTags=",".join(tags)
user.add_pic(os.path.join(path,filename),uid,fn,stringTags)
return render_template("index.html",username=session['username'],message="Image Uploaded!",category="success")
return render_template("upload.html",upload="True",message="Invalid File",category="danger")
def preprocess(filename, genre=None):
workbook = xlrd.open_workbook(filename) # 读取excel文件
sheet_names = workbook.sheet_names() # 获取表格名
sheet = workbook.sheet_by_name(sheet_names[0]) # 获取第i-1张表格数据
clean_train_reviews = []
for i in range(1, sheet.nrows):
if ((i + 1) % 100 == 0):
print("Review %d of %d\n" % (i + 1, sheet.nrows))
clean_train_reviews.append(plotToWords(sheet.row_values(i)[1]))
tagVector = getTags(genre, sheet)
data = {'plot': clean_train_reviews, 'tags': tagVector}
df = pd.DataFrame(data)
return df
def web():
if checkFile(request.form['link']):
ext = request.form['link'].rsplit('.',1)[1]
response = urllib.urlopen(request.form['link'])
image = response.read()
filename = stripPunctuation(request.form['filename'])+"."+ext
filename = secure_filename(filename)
filename = repeatedName(filename,0,False)
uid = user.get_UID(session['username'])
with open(path+"/"+filename,"wb") as out:
out.write(image)
link = utils.uploadPic (os.path.join(path,filename))
tags = utils.getTags(link, Access_token)
stringTags=",".join(tags)
user.add_pic(os.path.join(path,filename),uid,request.form['filename'],stringTags)
return render_template("index.html",username=session['username'],message="Image Uploaded!", category="succe\
ss")
return render_template("upload.html",upload="True",message="Invalid File",category="danger")
def preprocess(filename):
train = pd.read_csv(filename)
# counts = train.Genre1.value_counts()
# counts.plot(kind='bar')
# plt.show()
# print counts
num_reviews = train["Plot"].size
clean_train_reviews = []
for i in range(0, num_reviews):
if ((i + 1) % 100 == 0):
print ("Review %d of %d\n" % (i + 1, num_reviews))
clean_train_reviews.append(plotToWords(train["Plot"][i]))
tagVector = getTags('Comedy', train)
data = {'plot': clean_train_reviews, 'tags': tagVector}
df = pd.DataFrame(data)
return df
def onDeviceDataWork(msg):
try:
msg.payload = msg.payload.decode("utf-8")
data = msg.payload
assert data
tags = utils.getTags(msg.topic)
except:
logger.error(
f'The message: "{msg.payload}" cannot be processed. Topic: "{msg.topic}" is malformed. Ignoring data',
extra={"area": "IP"},
)
return
match tags["endpoint"]:
case "ip":
fields = {"ip": data}
case "model":
fields = {"model": data}
case "version":
fields = {"version": data}
case _:
logger.error(
f"Endpoint: '{tags['endpoint']}' not recognized. Topic: {msg.topic}. Ignoring data")
return
try:
tagsToSave = ["locationId", "deviceId"]
measurement = "devicesData"
influxDb.writeData(
measurement,
utils.selectTags(tagsToSave, tags),
fields,
retentionPolicy="raw",
)
except:
logger.error(
f"onIPWork message failed. message: {msg.payload}. Exception: ",
exc_info=True
)