def create_alert(channel, req_data):
actor_id = channel['triggers_with_actions'][0]['action']['actor_id']
logger.debug('actor_id:' + actor_id)
abaco_base_url = channel['triggers_with_actions'][0]['action'][
'abaco_base_url']
abaco_nonce = channel['triggers_with_actions'][0]['action']['nonces']
abaco_url = abaco_base_url + '/actors/v2/' + actor_id + '/messages?x-nonce=' + abaco_nonce
logger.debug('abaco_url: ' + abaco_url)
#prepare request for abaco
headers = {'accept': 'application/json'}
message_data = {}
message_data['message'] = req_data
message_data['message']['channel_id'] = channel['channel_id']
result = meta.fetch_instrument_index(
channel["triggers_with_actions"][0]['inst_ids'][0])
message_data['message']['project_id'] = result[0]['project_id']
message_data['message']['site_id'] = result[0]['site_id']
message_data['message']['inst_id'] = result[0]['instrument_id']
cond_key = channel['triggers_with_actions'][0]['condition']['key'].split(
".")
message_data['message']['var_id'] = cond_key[1]
logger.debug('message_data: ' + str(message_data))
try:
res = requests.post(abaco_url,
json=message_data,
headers=headers,
verify=False)
except Exception as e:
msg = f"Got exception trying to post message to Abaco actor: {actor_id}; exception: {e}"
raise errors.BaseTapyException(msg=msg, request=res.request)
logger.debug('abaco response:' + res.text)
logger.debug('abaco response status code:' + str(res.status_code))
if res.status_code == 200:
abaco_res = json.loads(res.text)
#TODO create alert summary and alert object with all details
execution_id = abaco_res['result']['executionId']
alert = {}
alert['alert_id'] = str(uuid.uuid4())
alert['channel_name'] = channel['channel_name']
alert['channel_id'] = channel['channel_id']
alert['actor_id'] = actor_id
alert['execution_id'] = execution_id
alert['message'] = req_data['message']
alert['create_time'] = str(datetime.datetime.utcnow())
logger.debug(alert)
alert_result, msg = meta.create_alert(alert)
logger.debug(alert_result)
result = meta.strip_meta(alert_result)
logger.debug(result)
return result, msg
else:
msg = f"Abaco Actor: {actor_id} unable to perform the execution on the message: {message_data}. Check the Actor Status and the message"
raise errors.ResourceError(msg=msg)
def post(self):
body = request.json
logger.debug(body)
if 'inst_id' in body:
result = meta.fetch_instrument_index(body['inst_id'])
logger.debug(result)
if len(result) > 0:
#check SK
logger.debug("YES")
logger.debug(result[0]['chords_inst_id'])
resp = chords.create_measurement(result[0]['chords_inst_id'],
body)
logger.debug(resp)
return resp
def convert_conditions_to_vars(req_body):
logger.debug("CONVERTING condition to vars ...")
triggers_with_actions = {}
triggers_with_actions = req_body['triggers_with_actions'][0]
inst_chords_id = {}
inst_var_chords_ids = {}
# inst_id.var_id
cond_key = []
cond_key = triggers_with_actions['condition']['key'].split(".")
# fetch chords id for the instrument
result = meta.fetch_instrument_index(cond_key[0])
logger.debug(result)
if len(result) > 0:
logger.debug(" chords instrument_ id: " +
str(result[0]['chords_inst_id']))
inst_chords_id[cond_key[0]] = result[0]['chords_inst_id']
# fetch chords id for the variable
result_var, message = meta.get_variable(result[0]['project_id'],
result[0]['site_id'],
result[0]['instrument_id'],
cond_key[1])
logger.debug("variable chords id : " + str(result_var['chords_id']))
inst_var_chords_ids[triggers_with_actions['condition']
['key']] = result_var['chords_id']
# create vars dictionary
vars = {}
vars['crit'] = {}
vars['crit']['type'] = "lambda"
# value is of the form : "value":"(\"var\" == '1') AND (\"value\" > 91.0)"
vars['crit']['value'] = "(\"var\" == '" + str(
inst_var_chords_ids[triggers_with_actions['condition']['key']]) + "') AND (\"value\"" + \
triggers_with_actions['condition']['operator'] + str(
triggers_with_actions['condition']['val']) + ")"
# channel id information is added for later processing of the alerts
vars["channel_id"] = {"type": "string", "value": req_body['channel_id']}
return vars
def post(self):
body = request.json
logger.debug(body)
instrument = {}
if 'inst_id' in body:
result = meta.fetch_instrument_index(body['inst_id'])
logger.debug(result)
if len(result) > 0:
logger.debug(result[0]['chords_inst_id'])
#get isntrument
site_result, site_msg = meta.get_site(result[0]['project_id'],
result[0]['site_id'])
if 'instruments' in site_result:
for inst in site_result['instruments']:
if inst['inst_id'] == body['inst_id']:
instrument = inst
logger.debug(site_result)
#resp = chords.create_measurement(result[0]['chords_inst_id'], body)
resp = influx.write_measurements(site_result['chords_id'],
instrument, body)
logger.debug(resp)
return utils.ok(result=[], msg="Measurements Saved")
def get(self, instrument_id):
result = []
msg = ""
logger.debug("top of GET /measurements")
#inst_result = meta.get_instrument(project_id,site_id,instrument_id)
inst_index = meta.fetch_instrument_index(instrument_id)
logger.debug(inst_index)
if len(inst_index[0]) > 0:
site, msg = meta.get_site(inst_index[0]['project_id'],
inst_index[0]['site_id'])
logger.debug("in IF")
js = influx.query_measurments([{
"inst":
str(inst_index[0]['chords_inst_id'])
}, {
"start_date":
request.args.get('start_date')
}, {
"end_date":
request.args.get('end_date')
}])
logger.debug(js)
if len(js) > 1 and len(js['series']) > 0:
df = pd.DataFrame(js['series'][0]['values'],
columns=js['series'][0]['columns'])
pv = df.pivot(index='time', columns='var', values=['value'])
df1 = pv
df1.columns = df1.columns.droplevel(0)
df1 = df1.reset_index().rename_axis(None, axis=1)
replace_cols = {}
logger.debug(site)
for inst in site['instruments']:
logger.debug(inst)
if inst['inst_id'] == instrument_id:
instrument = inst
logger.debug(inst)
for v in inst['variables']:
logger.debug(v)
replace_cols[str(v['chords_id'])] = v['var_id']
logger.debug(replace_cols)
df1.rename(columns=replace_cols, inplace=True)
df1.set_index('time', inplace=True)
if request.args.get('format') == "csv":
logger.debug("CSV")
# csv_response = Response(result, mimetype="text/csv")
# si = StringIO.StringIO()
#cw = csv.write(si)
# cw.writerows(csvList)
output = make_response(df1.to_csv())
output.headers[
"Content-Disposition"] = "attachment; filename=export.csv"
output.headers["Content-type"] = "text/csv"
return output
else:
result = json.loads(df1.to_json())
result['measurements_in_file'] = len(df1.index)
result['instrument'] = instrument
site.pop('instruments', None)
result['site'] = meta.strip_meta(site)
return utils.ok(result=result, msg="Measurements Found")
else:
return utils.ok(result=[], msg="No Measurements Founds")