Commit 039c5103 authored by Lluis Gifre Renom's avatar Lluis Gifre Renom
Browse files

Forecaster component: 

- Prepared unitary tests (under debug)
- Moved unitary test data to correct folder
- Added script to launch unitary tests
- Corrected issue in type hint within KpiManager
parent c988b197

scripts/run_tests_locally-forecaster.sh

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#!/bin/bash

# Copyright 2022-2023 ETSI TeraFlowSDN - TFS OSG (https://tfs.etsi.org/)

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#      http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.





PROJECTDIR=`pwd`



cd $PROJECTDIR/src

RCFILE=$PROJECTDIR/coverage/.coveragerc



# Run unitary tests and analyze coverage of code at same time

coverage run --rcfile=$RCFILE --append -m pytest --log-level=INFO --verbose \

    forecaster/tests/test_unitary.py

src/forecaster/service/KpiManager.py

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@@ -25,10 +25,10 @@ class KpiManager: 


    def get_kpi_ids_from_link_ids(

        self, link_ids : List[LinkId]

    ) -> Dict[Tuple[LinkId, KpiSampleType], KpiId]:

    ) -> Dict[Tuple[LinkId, int], KpiId]:

        link_uuids = {link_id.link_uuid.uuid for link_id in link_ids}

        kpi_descriptors = self._monitoring_client.GetKpiDescriptorList(Empty())

        kpi_ids : Dict[Tuple[LinkId, KpiSampleType], KpiId] = {

        kpi_ids : Dict[Tuple[LinkId, int], KpiId] = {

            (kpi_descriptor.link_id, kpi_descriptor.kpi_sample_type) : kpi_descriptor.kpi_id

            for kpi_descriptor in kpi_descriptors

            if kpi_descriptor.link_id.link_uuid.uuid in link_uuids

src/forecaster/tests/Tools.py

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Original line number Diff line number Diff line 
# Copyright 2022-2023 ETSI TeraFlowSDN - TFS OSG (https://tfs.etsi.org/)

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#      http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.



import calendar, math, pandas

from datetime import datetime, timezone

from typing import Dict

from common.tools.object_factory.Context import json_context

from common.tools.object_factory.Device import (

    json_device_emulated_connect_rules, json_device_emulated_packet_router_disabled, json_device_id

)

from common.tools.object_factory.EndPoint import json_endpoint_descriptor, json_endpoint_id

from common.tools.object_factory.Link import json_link

from common.tools.object_factory.Topology import json_topology



def time_datetime_to_int(dt_time : datetime) -> int:

    return int(calendar.timegm(dt_time.timetuple()))



def time_datetime_to_float(dt_time : datetime) -> float:

    return time_datetime_to_int(dt_time) + (dt_time.microsecond / 1.e6)



def time_utc_now_to_datetime() -> datetime:

    return datetime.now(tz=timezone.utc)



def time_utc_now_to_float() -> float:

    return time_datetime_to_float(time_utc_now_to_datetime())



def read_csv(csv_file : str) -> pandas.DataFrame:

    df = pandas.read_csv(csv_file)



    if 'dataset.csv' in csv_file:

        df.rename(columns={'linkid': 'link_id', 'ds': 'timestamp', 'y': 'used_capacity_gbps'}, inplace=True)

        df[['source', 'destination']] = df['link_id'].str.split('_', expand=True)

    elif 'dataset2.csv' in csv_file:

        df.drop(columns=['Unnamed: 0'], inplace=True)

        df.rename(columns={

            'target': 'destination', 'id': 'link_id', 'ds': 'timestamp', 'demandValue': 'used_capacity_gbps'

        }, inplace=True)



    df['timestamp'] = pandas.to_datetime(df['timestamp'])

    max_timestamp = time_datetime_to_int(df['timestamp'].max())

    now_timestamp = time_datetime_to_int(datetime.now(tz=timezone.utc))

    df['timestamp'] = df['timestamp'] + pandas.offsets.Second(now_timestamp - max_timestamp)

    df.sort_values('timestamp', ascending=True, inplace=True)

    return df



def compose_descriptors(df : pandas.DataFrame) -> Dict:

    devices = dict()

    links = dict()



    #df1.groupby(['A','B']).size().reset_index().rename(columns={0:'count'})

    df_links = df[['link_id', 'source', 'destination']].drop_duplicates()

    for row in df_links.itertuples(index=False):

        #print(row)

        link_uuid = row.link_id

        src_device_uuid = row.source

        dst_device_uuid = row.destination

        src_port_uuid = row.destination

        dst_port_uuid = row.source



        if src_device_uuid not in devices:

            devices[src_device_uuid] = {'id': src_device_uuid, 'endpoints': set()}

        devices[src_device_uuid]['endpoints'].add(src_port_uuid)



        if dst_device_uuid not in devices:

            devices[dst_device_uuid] = {'id': dst_device_uuid, 'endpoints': set()}

        devices[dst_device_uuid]['endpoints'].add(dst_port_uuid)



        if link_uuid not in links:

            total_capacity_gbps = df[df.link_id==link_uuid]['used_capacity_gbps'].max()

            total_capacity_gbps = math.ceil(total_capacity_gbps / 100) * 100 # round up in steps of 100

            used_capacity_gbps  = df[df.link_id==link_uuid]['used_capacity_gbps'].tail(1)

            links[link_uuid] = {

                'id': link_uuid,

                'src_dev': src_device_uuid, 'src_port': dst_device_uuid,

                'dst_dev': dst_device_uuid, 'dst_port': src_device_uuid,

                'total_capacity_gbps': total_capacity_gbps, 'used_capacity_gbps': used_capacity_gbps,

            }



    _context  = json_context('admin', name='admin')

    _topology = json_topology('admin', name='admin', context_id=_context['context_id'])

    descriptor = {

        'contexts': [_context],

        'topologies': [_topology],

        'devices': [

            json_device_emulated_packet_router_disabled(

                device_uuid, name=device_uuid, config_rules=json_device_emulated_connect_rules([

                    json_endpoint_descriptor(endpoint_uuid, 'copper', endpoint_name=endpoint_uuid)

                    for endpoint_uuid in device_data['endpoints']

                ]))

            for device_uuid,device_data in devices.items()

        ],

        'links': [

            json_link(link_uuid, [

                json_endpoint_id(json_device_id(link_data['src_dev']), link_data['src_port']),

                json_endpoint_id(json_device_id(link_data['dst_dev']), link_data['dst_port']),

            ], name=link_uuid, total_capacity_gbps=link_data['total_capacity_gbps'],

            used_capacity_gbps=link_data['used_capacity_gbps'])

            for link_uuid,link_data in links.items()

        ],

    }

    return descriptor