def post(self, indexer: ElasticSearchIndex, room) -> dict:
"""
This wil return a location, kind of 'Camden, London'.
We need to have some data like lat/lon for that input.
"""
indexer.index({})
return room
def post(self, indexer: ElasticSearchIndex, room: dict) -> dict:
"""
This wil return a location, kind of 'Camden, London'.
We need to have some data like lat/lon for that input.
"""
if indexer.exists_by_url(room['url']):
# 409 HTTP Conflict
return room, 409
# Generates a unique ID for the room
room['id'] = str(uuid.uuid4())
if not indexer.index(room):
return {"error": "Room not saved"}, 400
return room, 201
def configure(binder: Binder) -> Binder:
binder.bind(
ElasticSearchIndex,
ElasticSearchIndex(
ElasticSearchFactory(
os.environ['ELASTICSEARCH_HOST'],
os.environ['ELASTICSEARCH_PORT'],
), 'rooms', 'room', room_mapping))
return binder
def configure(binder: Binder) -> Binder:
binder.bind(
ItemsProvider, ItemsProvider([{
"Name": "Test1"
}]), ElasticSearchIndex,
ElasticSearchIndex(
ElasticSearchFactory(os.environ['ELASTICSEARCH_HOST'],
os.environ['ELASTICSEARCH_PORT']), 'rooms',
'room', room_mapping))
return binder
def configure(binder: Binder) -> Binder:
load_dotenv(find_dotenv())
binder.bind(
Firestore,
Firestore(os.getenv('AUTOSLANCES_CREDENTIALS_PATH'),
os.getenv('AUTOSLANCES_DATABASE_NAME')))
binder.bind(Washer)
binder.bind(
ElasticSearchIndex,
ElasticSearchIndex(
ElasticSearchFactory(), {
'vehicles': vehicle_mapping,
'brands': brand_mapping,
'models': model_mapping,
'versions': version_mapping
}))
return binder
def list(self, indexer: ElasticSearchIndex) -> list:
return indexer.list(), 200
def get(self, indexer: ElasticSearchIndex, _id: str) -> list:
return indexer.get(_id), 200
def delete(self, indexer: ElasticSearchIndex, _id: str) -> dict:
if not indexer.delete(_id):
return {"error": "Room not removed"}, 400
return None, 200
import datetime
from services.elasticsearch import ElasticSearchIndex, ElasticSearchFactory
from conf.elasticsearch_mapper import daily_bucket_storageclass_size_mapping
# boto3.set_stream_logger('', 10)
sts_client = boto3.client('sts')
s3 = boto3.resource('s3')
cloudwatch = boto3.resource('cloudwatch')
pp = pprint.PrettyPrinter(indent=4)
indexer = ElasticSearchIndex(ElasticSearchFactory(
'localhost',
9200,
), 'daily_bucket_storageclass_sizes', 'daily_bucket_storageclass_size',
daily_bucket_storageclass_size_mapping)
storageTypes = [{
'StorageType': 'StandardStorage',
'StorageClass': 'STANDARD'
}, {
'StorageType': 'IntelligentTieringStorage',
'StorageClass': 'INTELLIGENT_TIERING'
}, {
'StorageType': 'StandardIAStorage',
'StorageClass': 'STANDARD_IA'
}, {
'StorageType': 'OneZoneIAStorage',
'StorageClass': 'ONEZONE_IA'
's3',
aws_access_key_id=credentials['AccessKeyId'],
aws_secret_access_key=credentials['SecretAccessKey'],
aws_session_token=credentials['SessionToken'],
)
cloudwatch = boto3.resource(
'cloudwatch',
aws_access_key_id=credentials['AccessKeyId'],
aws_secret_access_key=credentials['SecretAccessKey'],
aws_session_token=credentials['SessionToken'],
)
pp = pprint.PrettyPrinter(indent=4)
indexer = ElasticSearchIndex(
ElasticSearchFactory(
ELASTICSEARCH_HOST,
ELASTICSEARCH_PORT,
), 'daily_bucket_storageclass_sizes', 'daily_bucket_storageclass_size',
daily_bucket_storageclass_size_mapping)
storageTypes = [{
'StorageType': 'StandardStorage',
'StorageClass': 'STANDARD'
}, {
'StorageType': 'IntelligentTieringStorage',
'StorageClass': 'INTELLIGENT_TIERING'
}, {
'StorageType': 'StandardIAStorage',
'StorageClass': 'STANDARD_IA'
}, {
'StorageType': 'OneZoneIAStorage',
'StorageClass': 'ONEZONE_IA'