def get_all():
client = datastore.Client()
query = client.query(kind='Account')
data = list(query.fetch())
for entity in data:
entity['id'] = entity.key.id
return data
def _collect_metric_data(self):
client = InfluxDBClient('188.166.238.158', 32485, 'root', 'root', 'k8s')
result = client.query('SELECT sum("value") FROM "memory/usage" WHERE "type" = \'node\' AND time > now() - 1d GROUP BY time(1d), "nodename" fill(null);')
# ('memory/usage', {'nodename': '128.199.242.5'}) - - [{'sum': 1275429384192, 'time': '2017-02-25T00:00:00Z'},
# {'sum': 1038484692992, 'time': '2017-02-26T00:00:00Z'}]
return
def get_all():
client = datastore.Client()
query = client.query(kind='Greeting')
query.order = '-created'
greetings = list(query.fetch())
for entity in greetings:
entity['id'] = entity.key.id
return greetings
def get_comments(parent_id):
client = datastore.Client()
ancestor = client.key('Greeting', int(parent_id))
query = client.query(kind='Comment', ancestor=ancestor)
entities = list(query.fetch())
for entity in entities:
entity['id'] = entity.key.id
return entities
def get_data(parent_id):
client = datastore.Client()
ancestor = client.key('ScrapingDataSummary', int(parent_id))
query = client.query(kind='ScrapingDataDetails', ancestor=ancestor)
entities = list(query.fetch())
for entity in entities:
entity['id'] = entity.key.id
return entities
def get_all():
client = datastore.Client()
query = client.query(kind='TodoList')
query.order = '-created'
data = list(query.fetch())
for entity in data:
entity['id'] = entity.key.id
return data
def get_cpu_usage(container_name):
"""Return cpu usage of container_name
@param string container_name container name
"""
query = "select DERIVATIVE(cpu_cumulative_usage) as cpu_usage from stats where container_name = '" + container_name + "' and time > now()-5m group by time(10s) "
result = client.query(query)
points = result[0]["points"]
return points[0][1] / 1000000000 / 4 * 100
def queryDataMax(datafield, minutes):
max = 0
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit '+str(minutes))
for p in results.get_points():
value = p[str(datafield)]
if(max < value):
max = value
print(str(datafield)+" maximum over "+str(minutes)+" min: "+str(max))
return max
def get_container_name(mesos_task_id): """Return container name mapping with mesos_task_id in messos @param string mesos_task_id """ query = "select container_name from "+INFLUXDB["ts_mapping"]+" where time>now() - 5m and mesos_task_id = '" +mesos_task_id+"' limit 1" result = client.query(query) points = result[0]["points"] return points[0][2]
def queryDataAverage(datafield, minutes):
total = 0
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit '+str(minutes))
for p in results.get_points():
value = p[str(datafield)]
total = total + value
average = total/minutes
print(str(datafield)+" average over "+str(minutes)+" min: "+str(average))
return average
def get_cpu_usage(container_name): """Return cpu usage of container_name @param string container_name container name """ query = "select DERIVATIVE(cpu_cumulative_usage) as cpu_usage from stats where container_name = '"+container_name+"' and time > now()-5m group by time(10s) " result = client.query(query) points = result[0]["points"] return points[0][1]/1000000000/4*100
def isFieldAbove(datafield, minutes, threshold):
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit '+str(minutes))
for p in results.get_points():
value = p[str(datafield)]
if value < threshold:
print(str(datafield)+" has NOT been above: "+str(threshold)+" for over "+str(minutes)+" min "+str(getLastValue(str(datafield)))[:4])
return False
print(str(datafield)+" has been above: "+str(threshold)+" for over "+str(minutes)+" min "+str(getLastValue(str(datafield)))[:4])
return True
def getContainersName(app_name): query = "select DISTINCT(mesos_task_id) from mapping where time > now() - 5m" result = client.query(query) points = result[0]["points"] containers_name = [] for point in points: mesos_task_id = point[1] if (mesos_task_id.find(app_name, 0) > -1): containers_name.append(getContainerName(point[1])) return containers_name
def get_container_name(mesos_task_id):
"""Return container name mapping with mesos_task_id in messos
@param string mesos_task_id
"""
query = "select container_name from " + INFLUXDB[
"ts_mapping"] + " where time>now() - 5m and mesos_task_id = '" + mesos_task_id + "' limit 1"
result = client.query(query)
points = result[0]["points"]
return points[0][2]
def wolfsearch(q):
app_id = 'Q77HTY-A9VGRYRKK6'
client = wolframalpha.Client(app_id)
res = client.query(q)
if res['@success'] == 'false':
return ('1')
else:
try:
return next(res.results).text
except:
return ('1')
def isFieldAbovePercentage(datafield, minutes, threshold):
countAbove = 0
#countBelow = 0
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit '+str(minutes))
for p in results.get_points():
value = p[str(datafield)]
#if value < threshold:
# countBelow = countBelow + 1
if value > threshold:
countAbove = countAbove + 1
#print(str(datafield)+" below "+str(threshold)+": "+str(countBelow/minutes)+"% of the time for the last "+str(minutes)+" min")
#print(str(datafield)+" above "+str(threshold)+": "+str(countAbove/minutes)+"% of the time for the last "+str(minutes)+" min")
print(str(datafield)+" has been below "+str(threshold)+": for over "+str(minutes)+" min "+str(countAbove/minutes)+"% of the time")
return countAbove/minutes
def DBcon(DevEUIlist):
client = InfluxDBClient(host='localhost', port=8086)
client.switch_database('op5_test')
callBefore = "SELECT value FROM temperature, humidity, light, motion, soundAvg, soundPeak, vdd, LrrLAT, LrrLON WHERE "
callDynamic = ""
for item in DevEUIlist:
print(item.get('devEUI'))
callDynamic += "DevEUI = '" + item.get('devEUI') + "' OR "
callDynamic = callDynamic[:-3]
callAfter = "ORDER BY ASC LIMIT 1"
callFinal = callBefore + callDynamic + callAfter
print(callFinal)
results = client.query(callFinal)
return results.raw
def avg_cpu_usage(containers_name):
"""Return avg cpu usage of all containers in list containers_name
@param list containers_name list containers name
@return float avg cpu usage
"""
number_container = len(containers_name)
containers_name = ["'"+x+"'" for x in containers_name]
containers_name = ",".join(containers_name)
query = "select DERIVATIVE(cpu_cumulative_usage) as cpu_usage,container_name from stats where time > now()-5m and container_name in ("+containers_name+") group by time(10s),container_name limit "+str(number_container)
result = client.query(query)
points = result[0]["points"]
return points[0][1]/1000000000/4*100
sum_cpu_usage = 0
for point in points:
sum_cpu_usage += points[0][1]/1000000000/4*100
return sum_cpu_usage / number_container
def avg_cpu_usage(containers_name):
"""Return avg cpu usage of all containers in list containers_name
@param list containers_name list containers name
@return float avg cpu usage
"""
number_container = len(containers_name)
containers_name = ["'" + x + "'" for x in containers_name]
containers_name = ",".join(containers_name)
query = "select DERIVATIVE(cpu_cumulative_usage) as cpu_usage,container_name from stats where time > now()-5m and container_name in (" + containers_name + ") group by time(10s),container_name limit " + str(
number_container)
result = client.query(query)
points = result[0]["points"]
return points[0][1] / 1000000000 / 4 * 100
sum_cpu_usage = 0
for point in points:
sum_cpu_usage += points[0][1] / 1000000000 / 4 * 100
return sum_cpu_usage / number_container
def queryDataField(datafield, minutes):
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit '+str(minutes))
return results
def queryDataMinutes(minutes):
results = client.query('select * from data ORDER BY "time" DESC limit '+str(minutes))
return results
def queryWaterCount(datafield, minutes):
value = 0
results = client.query('select sum('+str(datafield)+') from water limit '+str(minutes))
for p in results.get_points():
value = p["sum"]
return value
# Establishing connec
client = InfluxDBClient(host='localhost',
port=8086,
username='******',
password='******',
database='_internal')
# The list of databases in influxDB
result = client.get_list_database()
print("Result: {0}".format(result))
client.create_database('telegraf')
client.switch_database('telegraf')
rs = client.query("SELECT * from cpu;")
cpu_points = list(rs.get_points(measurement='cpu'))
cpuu = psutil.cpu_times(percpu=True)
print(cpuu)
# Convert each namedTuple to a json string
cpuu = [json.dumps(stats._asdict()) for stats in cpuu]
print("Result: {0}".format(cpuu))
print(cpuu)
now = datetime.datetime.today()
timeinterval_min = 5 # create an event every x minutes
series = []
for i in range(0, len(cpuu)):
past_date = now - datetime.timedelta(minutes=1 * timeinterval_min)
async def askTure(ctx, *, arg):
# init client
client = wolframalpha.Client(wolframKey)
# send first message to user
await ctx.channel.send(askTureMessages[random.randint(
0,
len(askTureMessages) - 1)])
# query wolfram alpha
result = client.query(arg)
# get the main pod of data
resultPods = result.get("pod")
message = []
titleAmount = 0
images = []
try:
# for each pod add pod title and images from its sub pods
for pod in resultPods:
message.append(pod.get("@title"))
titleAmount += 1
subpod = pod.get("subpod")
if (type(subpod) == list):
for childpod in subpod:
response = requests.get(childpod.get("img").get("@src"))
img = Image.open(BytesIO(response.content))
images.append(img)
message.append(img)
elif (type(subpod) == dict):
response = requests.get(subpod.get("img").get("@src"))
img = Image.open(BytesIO(response.content))
images.append(img)
message.append(img)
# adjust final image height and width
widths, heights = zip(*(i.size for i in images))
totalHeight = sum(heights) + titleAmount * 18
maxWidth = max(widths)
newImage = Image.new('RGB', (maxWidth, totalHeight), color="white")
yOffset = 0
imageDraw = ImageDraw.Draw(newImage)
# Create font and add titles to final images
font = ImageFont.truetype("Verdana.ttf", 14)
for field in message:
if type(field) == str:
imageDraw.text((5, yOffset), field, font=font, fill="black")
yOffset += 18
else:
newImage.paste(field, (0, yOffset))
yOffset += field.size[1]
# create temp file name
tempFileName = "{}.png".format(random.randint(1, 10000))
# save temp file
newImage.save(tempFileName, 'PNG')
imagePath = "{}/{}".format(str(pathlib.Path().absolute()),
tempFileName)
# create embed and set file & image
embed = discord.Embed(title="Här har du, lämna mig ifred nu",
color=0x00ff00) #creates embed
f = discord.File(imagePath, filename=tempFileName)
embed.set_image(url="attachment://{}".format(tempFileName))
# send image and remove temp file
await ctx.send(file=f, embed=embed)
os.remove(imagePath)
except:
await ctx.channel.send(askTureInfoNotFoundMessages[random.randint(
0,
len(askTureInfoNotFoundMessages) - 1)])
def getLastValue(datafield):
results = client.query('select '+str(datafield)+' from data ORDER BY "time" DESC limit 1')
for p in results.get_points():
value = p[str(datafield)]
#print(str(datafield)+" last value: "+str(value))
return value
def getContainerName(mesos_task_id): query = "select container_name from mapping where time>now() - 5m and mesos_task_id = '" +mesos_task_id+"' limit 1" result = client.query(query) points = result[0]["points"] return points[0][2]
