def list():
try:
request = ml.projects().models().list(parent=projectID)
response = request.execute()
if response:
models = "<h4>Models</h4><ul>"
for i, v in enumerate(response['models']):
models = models + v['name'] + " " + v[
'description'] + '<br> '
models = models + "</ul>"
else:
models = "<h4>No models</h4><br/>"
request = storage.objects().list(
bucket=storageBinding.get("bucket_name"))
response = request.execute()
if response:
items = "<h4>Items</h4><ul>"
for i, v in enumerate(response['items']):
items = items + v['name'] + " " + v[
'contentType'] + '<br> '
items = items + "</ul>"
else:
items = "<h4>No files</h4><br/>"
result = models + items
return result
except errors.HttpError, err:
# Something went wrong, print out some information.
return 'There was an error creating the model. Check the details:' + err._get_reason(
)
def selecttime():
if current_user.connected:
storage = Storage('credentials/'+current_user.username)
credentials = storage.get()
http = httplib2.Http()
http = credentials.authorize(http)
service = build(serviceName='calendar', version='v3', http=http,
developerKey=DEVELOPER_KEY)
try:
request = service.events().list(calendarId='primary',
singleEvents=True,orderBy='startTime',
timeMin="2013-01-19T23:20:50.52Z")
response = request.execute()
current_event = session['current_event']
interval = timedelta(minutes=current_event.intervalMinutes)
latestendtime = datetime.now()
for event in response.get('items', []):
if rfc(event['start']['dateTime']) - interval > latestendtime:
current_event.startTime = latestendtime
current_event.endTime = latestendtime + interval
current_event.save()
break
if rfc(event['end']['dateTime']) > latestendtime:
latestendtime = event.get('end').get('dateTime')
body = {'summary':current_event.name,'start':{'timeZone': 'America/Los_Angeles','dateTime':anti(current_event.startTime)},'end':{'timeZone': 'America/Los_Angeles','dateTime':anti(current_event.endTime)}}
print ('yes way')
test = service.events().insert(calendarId='primary',body=body)
print('inter')
print test
test.execute()
print('success')
except Exception, e:
print e
print ('The credentials have been revoked or expired, please re-runthe application to re-authorize')
def searchForVideo(searchstr):
# print("Search for:", searchstr)
try:
youtube = googleapiclient.discovery.build(
youtube_api_service_name,
youtube_api_version,
developerKey=youtube_DEVELOPER_KEY)
request = youtube.search().list(
order="viewCount",
q=searchstr,
part="id,snippet",
)
response = request.execute()
# pprint(response['items'][0])
youtube_link = "https://youtu.be/" + response['items'][0]['id'][
'videoId']
youtube_title = html.unescape(response['items'][0]['snippet']['title'])
youtube_title = youtube_title.split("feat.")[0].split("ft.")[0]
# print("Youtube title:", youtube_title)
artist, title = get_artist_title(youtube_title)
return {
'link': {
"youtube": youtube_link
},
'title': title,
'artist': artist
}
except:
return
def run_dataflow_job(name):
from googleapiclient.discovery import build
from oauth2client.client import GoogleCredentials
credentials = GoogleCredentials.get_application_default()
service = build('dataflow', 'v1b3', credentials=credentials)
# Set the following variables to your values.
PROJECT = settings.GCP_PROJECT_ID
BUCKET = settings.CLOUD_STORAGE_BUCKET
TEMPLATE = 'dataflowtemplates'
GCSPATH = "gs://{bucket}/templates/{template}".format(bucket=BUCKET,
template=TEMPLATE)
BODY = {
"jobName": "{jobname}".format(jobname=name),
"parameters": {
# "inputFile": "gs://{bucket}/input/my_input.txt",
# "outputFile": "gs://{bucket}/output/my_output".format(bucket=BUCKET)
},
"environment": {
# "tempLocation": "gs://{bucket}/temp".format(bucket=BUCKET),
"zone": "us-central1-f"
}
}
request = service.projects().templates().launch(projectId=PROJECT,
gcsPath=GCSPATH,
body=BODY)
response = request.execute()
print(response)
def update_database():
try:
scope = [
'https://spreadsheets.google.com/feeds',
'https://www.googleapis.com/auth/drive'
]
credentials = ServiceAccountCredentials.from_json_keyfile_name(
'credentials.json', scope)
service = discovery.build('sheets', 'v4', credentials=credentials)
sheet_id = '1R6_1r9WYXs3hrgwabZDXLlk_f9Z7KAgxjjXFAzAoFt4'
range_ = '13thNov.Balance!C3:F'
request = service.spreadsheets().values().get(spreadsheetId=sheet_id,
range=range_)
response = request.execute()
connection = mysql.connect()
cur = connection.cursor()
records_to_insert = []
for i in range(len(response['values'])):
records_to_insert.append(tuple(response['values'][i]))
cur.execute("TRUNCATE TABLE balance")
mysql_insert = """INSERT INTO balance (name, pref_realm, paid, balance) VALUES (%s,%s,%s,%s)"""
cur.executemany(mysql_insert, records_to_insert)
connection.commit()
resp = jsonify("Inserted " + str(cur.rowcount) +
" rows in the database!")
resp.status_code = 200
return resp
except Exception as e:
print(e)
finally:
cur.close()
connection.close()
def list():
# [START requests_start]
try:
compute = build('compute', 'v1', cache_discovery=False)
params = {
'project': os.getenv('GOOGLE_CLOUD_PROJECT'),
'fields': 'items/*/instances(id,name,status,labels,networkInterfaces/accessConfigs/natIP)'
}
instances = []
request = compute.instances().aggregatedList(**params) # pylint: disable=E1101
while request is not None:
response = request.execute()
for name, instances_scoped_list in response['items'].items():
logging.debug("{}\n{}".format(name,instances_scoped_list))
for i in instances_scoped_list['instances']:
i['zone'] = name.split('/')[-1]
try:
i['IP'] = i['networkInterfaces'][0]['accessConfigs'][0]['natIP']
except Exception as ex:
i['IP'] = '-'
try:
i['function'] = i['labels']['function']
except Exception as ex:
i['function'] = '-'
instances = instances + instances_scoped_list.get('instances', [])
request = compute.instances().aggregatedList_next(previous_request=request, previous_response=response) # pylint: disable=E1101
return render_template("index.html", instances=instances)
except ValueError:
return "Cannot get servers info"
except HTTPError as ex:
logging.exception(ex)
return "Request error", 500
def googleLogin():
# Google login
if 'credentials' not in session:
return redirect(url_for('goauth2redirect'))
credentials = client.OAuth2Credentials.from_json(session['credentials'])
if credentials.access_token_expired:
return redirect(url_for('goauth2redirect'))
else:
http_auth = credentials.authorize(httplib2.Http())
service = discovery.build('oauth2', 'v2', http=http_auth)
request = service.userinfo().v2().me().get()
response = request.execute()
session['provider'] = 'google'
session['username'] = response['name']
session['google_id'] = response['id']
session['picture'] = response['picture']
session['email'] = response['email']
# Check if user exist
user_id = getUserID(session['email'])
if not user_id:
user_id = createUser(session)
session['user_id'] = user_id
return redirect(url_for('index'))
def detect_automl_labels(bucket_id, object_id):
"""Detects labels from image using AutoML Vision."""
try:
# Read image file contents from GCS
filename = '/{}/{}'.format(bucket_id, object_id)
gcs_file = cloudstorage.open(filename)
encoded_contents = base64.b64encode(gcs_file.read())
gcs_file.close()
# Build request payload dict for label detection
request_dict = {
'payload': {
'image': {
'imageBytes': encoded_contents
}
},
'params': {
'score_threshold': "0.5"
}
}
# Get predictions from the AutoML Vision model
automl_svc = get_automl_svc()
parent = 'projects/{}/locations/us-central1/models/{}'.format(
app_identity.get_application_id(),
current_app.config['AUTOML_MODEL_ID'])
request = automl_svc.projects().locations().models().predict(
name=parent, body=request_dict)
response = request.execute()
return response['payload']
except DeadlineExceededError:
logging.exception('Exceeded deadline in detect_automl_labels()')
def d():
service = createDriveService()
activities_resource = service.activities()
request = activities_resource.list( userId='108250612542617275436' , collection='public' , maxResults=20 )
L = []
returnD = {}
while request != None:
activities_document = request.execute()
if 'items' in activities_document:
returnD['nextPageToken'] = activities_document['nextPageToken']
for activity in activities_document['items']:
L.append(activity)
request = None #"""request = service.activities().list_next(request, activities_document)"""
returnD['items'] = L
response = make_response( json.dumps(returnD) , 200)
response.headers['Content-Type'] = 'application/json'
return response
def read_events(calendarId):
my_calendarId = calendarId
service = init_google_service_call()
print("Reading events")
#read all calendars from the authorized user
try:
# The Calendar API's events().list method returns paginated results, so we
# have to execute the request in a paging loop. First, build the
# request object. The arguments provided are:
# primary calendar for user
request = service.events().list(calendarId=my_calendarId)
# Loop until all pages have been processed.
while request != None:
# Get the next page.
response = request.execute()
# Accessing the response like a dict object with an 'items' key
# returns a list of item objects (events).
for event in response.get('items', []):
# The event object is a dict object with a 'summary' key.
this_event_item = event_item(event)
this_event_item.show_event()
print('---------------------------------------')
# Get the next request object by passing the previous request object to
# the list_next method.
request = service.events().list_next(request, response)
except AccessTokenRefreshError:
# The AccessTokenRefreshError exception is raised if the credentials
# have been revoked by the user or they have expired.
print('The credentials have been revoked or expired, please re-run'
'the application to re-authorize')
def glogin():
"""Handles Goolge login.
Redirects to '/goauth2redirect' if user is not logged in.
Retrieves user data and redirects to '/' if user is logged in.
"""
# If not logged in, redirect to Google login
if 'credentials' not in session:
return redirect(url_for('goauth2redirect'))
credentials = client.OAuth2Credentials.from_json(session['credentials'])
if credentials.access_token_expired:
return redirect(url_for('goauth2redirect'))
else:
# Authorize and build a service object to retrieve user data
http_auth = credentials.authorize(httplib2.Http())
service = discovery.build('oauth2', 'v2', http=http_auth)
request = service.userinfo().v2().me().get()
response = request.execute()
session['provider'] = 'google'
session['username'] = response['name']
session['google_id'] = response['id']
session['picture'] = response['picture']
session['email'] = response['email']
# See if user exists
user_id = getUserID(session['email'])
if not user_id:
user_id = createUser(session)
session['user_id'] = user_id
return redirect(url_for('index'))
def glogin():
"""Handles Goolge login.
Redirects to '/goauth2redirect' if user is not logged in.
Retrieves user data and redirects to '/' if user is logged in.
"""
# If not logged in, redirect to Google login
if 'credentials' not in session:
return redirect(url_for('goauth2redirect'))
credentials = client.OAuth2Credentials.from_json(session['credentials'])
if credentials.access_token_expired:
return redirect(url_for('goauth2redirect'))
else:
# Authorize and build a service object to retrieve user data
http_auth = credentials.authorize(httplib2.Http())
service = discovery.build('oauth2', 'v2', http=http_auth)
request = service.userinfo().v2().me().get()
response = request.execute()
session['provider'] = 'google'
session['username'] = response['name']
session['google_id'] = response['id']
session['picture'] = response['picture']
session['email'] = response['email']
# See if user exists
user_id = getUserID(session['email'])
if not user_id:
user_id = createUser(session)
session['user_id'] = user_id
return redirect(url_for('index'))
def get_all_data(query):
request = service.column().list(tableId=TABLE_ID)
response = request.execute()
response = service.query().sql(sql=query).execute()
logging.info(response['columns'])
logging.info(response['rows'])
return response
def submit_job(project_id, job_id):
# Store your full project ID in a variable in the format the API needs.
parent_project = 'projects/{}'.format(project_id)
# Build a representation of the Cloud ML API.
ml = discovery.build('ml', 'v1')
# Create a dictionary with the fields from the request body.
training_input = {
'scaleTier':
'BASIC',
'packageUris':
['gs://models.stufff.review/packages/default-1/default-1.tar.gz'],
'pythonModule':
'model.task',
'args': ['--model-id', '26144595808e', '--model-rev', '1'],
'region':
'europe-west1',
"jobDir":
'gs://models.stufff.review/26144595808e/26144595808e/default-1',
'runtimeVersion':
'1.12',
'pythonVersion':
'2.7'
}
request_dict = {'jobId': job_id, 'trainingInput': training_input}
# Create a request to submit a model for training
request = ml.projects().jobs().create(parent=parent_project,
body=request_dict)
# Make the call.
resp = request.execute()
return resp
def runNewModel(session):
if LoggedIn() != True:
return defaultRedirect()
project = get_current_project(session)
JOB_NAME = "a_" + str(project.id)
# Creating model
requestDict = {'name': JOB_NAME,
'description': 'Built by runNewModel()'}
request = ml.projects().models().create(parent=projectID, body=requestDict)
try:
response = request.execute()
print(response, file=sys.stderr)
operationID = response['name']
out = 'success'
return out, 200, {'ContentType':'application/json'}
except errors.HttpError as EOFError:
print('There was an error. Check the details:', file=sys.stderr)
print(EOFError._get_reason(), file=sys.stderr)
out = 'failed'
return out, 200, {'ContentType':'application/json'}
return "Success", 200
def post(self, name):
try:
# Create a dictionary with the fields from the request body.
jobId = "{0}_{1}_{2}".format(name, time.strftime('%Y%m%d'),
time.strftime('%S%M%H'))
requestBody = {
"jobId": jobId,
"trainingInput": {
"args": [
"--train_dir=gs://{0}/{1}/train".format(
storageBinding['bucket_name'], jobId)
],
"packageUris": [
"gs://fe-cdantonio-ml/mnist_crdant_20161215_0117292/454e901f09767005b057fd41cb223de84329b09d/trainer-0.0.0.tar.gz"
],
"pythonModule":
"trainer.task",
"region":
"us-central1"
}
}
# Create a request to call projects.models.create.
request = ml.projects().jobs().create(parent=projectID,
body=requestBody)
response = request.execute()
return response
except errors.HttpError, err:
# Something went wrong, print out some information.
return 'There was an error creating the job. Check the details:' + err._get_reason(
)
def runTraining(session):
if LoggedIn() != True:
return defaultRedirect()
have_error, params = training_pre_conditions(session)
if have_error:
print("have error", params, file=sys.stderr)
return json.dumps(params), 200, {'ContentType':'application/json'}
# TODO Thinking on reasonable way to "copy" a version and track changes
project = get_current_project(session)
version = get_current_version(session)
machine_learning_settings = get_ml_settings(session=session, version=version)
JOB_NAME = "train_" + machine_learning_settings.JOB_NAME
print(JOB_NAME, file=sys.stderr)
REGION="us-central1"
RUNTIME_VERSION="1.2"
root_dir = "gs://" + settings.CLOUD_STORAGE_BUCKET + "/" + str(project.id) + "/" + str(version.id) + "/ml/" + str(machine_learning_settings.ml_compute_engine_id) + "/"
JOB_DIR = root_dir + "train"
pipeline_config_path = root_dir + "faster_rcnn_resnet.config"
MAIN_TRAINER_MODULE='object_detection.train'
training_inputs = {'scaleTier': 'CUSTOM',
'masterType': 'standard_gpu',
'workerType': 'standard_gpu',
'parameterServerType': 'standard_gpu',
'workerCount': 2,
'parameterServerCount': 1,
'packageUris': ['gs://' + settings.CLOUD_STORAGE_BUCKET + '/' + settings.LIB_OBJECT_DETECTION_PYTHON,
'gs://' + settings.CLOUD_STORAGE_BUCKET + '/' + settings.LIB_SLIM_PYTHON ],
'pythonModule': MAIN_TRAINER_MODULE,
'args': ['--train_dir', JOB_DIR,
'--pipeline_config_path', pipeline_config_path],
'region': REGION,
'jobDir': JOB_DIR,
'runtimeVersion': RUNTIME_VERSION }
job_spec = {'jobId': JOB_NAME, 'trainingInput': training_inputs}
request = ml.projects().jobs().create(body=job_spec, parent=projectID)
try:
response = request.execute()
print(response, file=sys.stderr)
out = 'success'
return out, 200, {'ContentType':'application/json'}
except errors.HttpError as EOFError:
print('There was an error. Check the details:', file=sys.stderr)
print(EOFError._get_reason(), file=sys.stderr)
out = 'failed'
return out, 500, {'ContentType':'application/json'}
return "success", 200
def search_youtube_playlist(youtube, playlist_name):
request = youtube.playlists().list(part="snippet", mine=True)
search_response = request.execute()
return [
item["id"] for item in search_response["items"]
if item["snippet"]["title"] == playlist_name
]
def processRequest(req):
result = req.get("queryResult")
parameters = result.get("parameters")
username = parameters["username"]
request = youtube.channels().list(part="statistics", forUsername=username)
response = request.execute()
totalNumber = response['items'][0]['statistics']['subscriberCount']
return speech_output(totalNumber)
def activities_user(idA):
service = createDriveService()
activities_resource = service.activities()
request = activities_resource.list( userId=idA, maxResults= 23 , collection='public')
activities_document = request.execute()
response = make_response( json.dumps(activities_document) , 200)
response.headers['Content-Type'] = 'application/json'
return response
def get_playlists(self):
request = self.youtube.playlists().list(part="snippet,contentDetails",
channelId=self.id,
maxResults=50)
response = request.execute()
fields = response['items']
for field in fields:
self.text += field['snippet']['title'] + field['snippet'][
'description'] + ' '
def get_prediction(ml_service, project, model_name, input_image):
request_dict = make_request_json(input_image)
body = {'instances': [request_dict]}
# This request will use the default model version.
parent = 'projects/{}/models/{}'.format(project, model_name)
request = ml_service.projects().predict(name=parent, body=body)
result = request.execute()
return result
def get_prediction(ml_service, project, model_name, input_image):
request_dict = make_request_json(input_image)
body = {'instances': [request_dict]}
# This request will use the default model version.
parent = 'projects/{}/models/{}'.format(project, model_name)
request = ml_service.projects().predict(name=parent, body=body)
result = request.execute()
return result
def delete(self, name):
try:
request = storage.objects().delete(bucket=self.bucketName,
object=name)
response = request.execute()
return response
except errors.HttpError, err:
# Something went wrong, print out some information.
return 'There was an error deleting the object. Check the details:' + err._get_reason(
)
def videoSearch(q, salt="Explain"):
request = youtube.search().list(part="snippet", maxResults=1, q=q + salt)
response = request.execute()
try:
videoId = response['items'][0]['id']['videoId']
except:
return "https://www.youtube.com/watch?v=sDP3SDaSf4c"
return "https://www.youtube.com/watch?v=" + videoId
def test_api_request():
if 'credentials' not in flask.session:
return flask.redirect('authorize')
# Load credentials from the session.
credentials = google.oauth2.credentials.Credentials(
**flask.session['credentials'])
youtube = googleapiclient.discovery.build(API_SERVICE_NAME,
API_VERSION,
credentials=credentials)
# Search for a song
request = youtube.search().list(part="snippet",
q="Waltz in A minor",
type="video")
search_response = request.execute()
first_video_id = search_response["items"][0]["id"]["videoId"]
# Add songs to a playlist
request = youtube.playlistItems().insert(
part="snippet",
body={
"snippet": {
"playlistId": "PL3AgsfiW8ntWXfIKnARk2jyhP1xDM4-oL",
"resourceId": {
"kind": "youtube#video",
"videoId": first_video_id
}
}
})
add_song_response = request.execute()
# Save credentials back to session in case access token was refreshed.
# ACTION ITEM: In a production app, you likely want to save these
# credentials in a persistent database instead.
flask.session['credentials'] = credentials_to_dict(credentials)
return flask.jsonify(add_song_response)
def trainingFrozenRun(session):
if LoggedIn() != True:
return defaultRedirect()
project = get_current_project(session)
version = get_current_version(session)
machine_learning_settings = get_ml_settings(session=session, version=version)
#now=strftime("%Y_%m_%d_%H_%M_%S", gmtime())
JOB_NAME = "frozen_user_" + machine_learning_settings.JOB_NAME
print(JOB_NAME, file=sys.stderr)
root_dir = "gs://" + settings.CLOUD_STORAGE_BUCKET + "/" + str(project.id) + "/" + str(version.id) + "/ml/" + str(machine_learning_settings.ml_compute_engine_id) + "/"
JOB_DIR = root_dir + str(machine_learning_settings.re_train_id) + "/frozen"
REGION ="us-central1"
RUNTIME_VERSION ="1.2"
# Should be updated during training and store in db?
trained_checkpoint_prefix = configNew.check_actual_model_path_name(session=session)
pipeline_config_path = root_dir + "faster_rcnn_resnet.config"
MAIN_TRAINER_MODULE ="object_detection.export_inference_graph"
training_inputs = {'scaleTier': 'CUSTOM',
'masterType': 'large_model',
'workerCount': 0,
'packageUris': ['gs://' + settings.CLOUD_STORAGE_BUCKET + '/' + settings.LIB_OBJECT_DETECTION_PYTHON,
'gs://' + settings.CLOUD_STORAGE_BUCKET + '/' + settings.LIB_SLIM_PYTHON ],
'pythonModule': MAIN_TRAINER_MODULE,
'args': ['--trained_checkpoint_prefix', trained_checkpoint_prefix,
'--pipeline_config_path', pipeline_config_path,
'--input_type', 'encoded_image_string_tensor',
'--output_directory', JOB_DIR],
'region': REGION,
'jobDir': JOB_DIR,
'runtimeVersion': RUNTIME_VERSION }
job_spec = {'jobId': JOB_NAME, 'trainingInput': training_inputs}
request = ml.projects().jobs().create(body=job_spec, parent=projectID)
try:
response = request.execute()
print(response, file=sys.stderr)
out = 'success'
return out, 200, {'ContentType':'application/json'}
except errors.HttpError as EOFError:
print('There was an error. Check the details:', file=sys.stderr)
print(EOFError._get_reason(), file=sys.stderr)
out = 'failed'
return out, 200, {'ContentType':'application/json'}
return "Success", 200
def get_storage_bucket(bucket_name, create_new=True):
_request = get_google_client("storage").buckets().get(bucket=bucket_name)
try:
resp = _request.execute()
return resp
except errors.HttpError, e:
if create_new:
request = get_google_client("storage").buckets().insert(
bucket=bucket_name)
resp = request.execute()
return resp
def get(self, name):
try:
jobName = '{0}/jobs/{1}'.format(projectID, name)
# Create a request to call projects.models.create.
request = ml.projects().jobs().get(name=jobName)
response = request.execute()
return response
except errors.HttpError, err:
# Something went wrong, print out some information.
return 'There was an error getting the job. Check the details:' + err._get_reason(
)
def delete(self, name):
try:
# Create a dictionary with the fields from the request body.
modelName = '{0}/models/{1}'.format(projectID, name)
# Create a request to call projects.models.create.
request = ml.projects().models().delete(name=modelName)
response = request.execute()
return response
except errors.HttpError, err:
# Something went wrong, print out some information.
return 'There was an error deleting the model. Check the details:' + err._get_reason(
)
def getResponseYTAPI(vid):
os.environ["OAUTHLIB_INSECURE_TRANSPORT"] = "1"
api_service_name = "youtube"
api_version = "v3"
DEVELOPER_KEY = secret.DEVELOPER_KEY
youtube = googleapiclient.discovery.build(api_service_name,
api_version,
developerKey=DEVELOPER_KEY)
request = youtube.videos().list(part="snippet,contentDetails,statistics",
id=vid)
response = request.execute()
# print("YT Response : {}".format(response),file = sys.stdout)
return response
def updateYoutube():
global ID
global youtube
if not youtube:
print(ID)
print("can not update, are you login yet?")
return
if os.path.exists("youtube_video_id.txt"):
f = open("youtube_video_id.txt", encoding="utf-8")
ID = f.readline()
else:
print("not found youtube_video_id")
return
if os.path.exists("title.txt"):
f = open("title.txt", encoding="utf-8")
CUSTOM_TITLE = f.readline()
else:
print("not found title")
return
video = youtube.videos().list(id=ID,
part='snippet, id, statistics').execute()
views = video["items"][0]["statistics"]["viewCount"]
categoryId = video["items"][0]["snippet"]["categoryId"]
description = video["items"][0]["snippet"]["description"]
tags = video["items"][0]["snippet"]["tags"]
if not "Techcast" in description:
description = description + "\n\nScript นี้สร้างโดยช่อง Techcast (กดติดตามที่ลิงค์นี้ได้เลย)\nhttps://bit.ly/3hvHVXH"
request = youtube.videos().update(part="snippet",
body={
"id": ID,
"snippet": {
"title":
CUSTOM_TITLE.format(views),
"description": description,
"categoryId": categoryId,
"tags": tags
}
})
response = request.execute()
refresh_api()
def identify_image(uri):
IMAGE = 'gs://' + bucketName + '/' + imgFolder + uri
vservice = build('vision', 'v1', developerKey=APIKEY)
request = vservice.images().annotate(
body={
'requests': [{
'image': {
'source': {
'gcs_image_uri': IMAGE
}
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 3,
}]
}],
})
responses = request.execute(num_retries=3)
try:
api_text = (
responses['responses'][0]['textAnnotations'][0]['description'])
start = api_text.find("NOMBRE") + len("NOMBRE")
end = api_text.find("DOMICILIO")
name = api_text[start:end]
name = name.replace("\n", " ")
"""
api_array = api_text.splitlines()
name_like_variable = difflib.get_close_matches('NOMBRE', api_array)
address_like_variable = difflib.get_close_matches('DOMICILIO', api_array)
name_like_variable_idx = api_array.index(''.join(name_like_variable))
address_like_variable_idx = api_array.index(''.join(address_like_variable))
name = ''
i = name_like_variable_idx + 1
while i < address_like_variable_idx:
name += api_array[i] + " "
i += 1
"""
return jsonify({'name': name}, {'error': False})
except Exception as e:
# TODO Control Messaging for errors
return jsonify({
'error':
True,
'uri':
IMAGE,
'message':
responses['responses'][0]['textAnnotations'][0]
})
def requestComment():
request = youtube.commentThreads().list(
part="snippet,replies",
maxResults=20,
videoId="m-IUcQrJYCo"
)
response = request.execute()
for item in response["items"]:
comment = item["snippet"]["topLevelComment"]
sendId = comment["id"]
author = comment["snippet"]["authorDisplayName"]
text = comment ["snippet"]["textDisplay"]
analyze(text)
print('requestComment')
def updateConfig(project_id, region, registry_id, device_id, data):
"""Push the data to the given device as configuration."""
config_data_json = json.dumps(data)
body = {
'version_to_update':
0,
'binary_data':
base64.b64encode(config_data_json.encode('utf-8')).decode('ascii')
}
device_name = ('projects/{}/locations/{}/registries/{}/'
'devices/{}'.format(project_id, region, registry_id,
device_id))
request = service.projects().locations().registries().devices(
).modifyCloudToDeviceConfig(name=device_name, body=body)
update_config_mutex.acquire()
try:
request.execute()
except HttpError as e:
print('Error executing ModifyCloudToDeviceConfig: {}'.format(e))
finally:
update_config_mutex.release()
def try_to_store_file():
mime_type = 'text/plain'
media_body = MediaFileUpload(g.file_path,
mimetype=mime_type,
resumable=True)
parent_id = app.config['GOOGLE_DRIVE_FOLDER_ID']
body = {
'title': os.path.basename(g.file_path),
'mimeType': mime_type,
'parents': [{'id': parent_id}, ]
}
try:
service = get_google_drive_service()
request = service.files().insert(body=body, media_body=media_body)
return request.execute()
except Exception as e:
app.logger.exception(e)
