diff --git a/devices/util/archiver.py b/devices/util/archiver.py
index 1045634a3dba6f9a82b0d1eb0795fe4e4e877659..f70d5b11f49eed950fa3486d176c03a1bc80242f 100644
--- a/devices/util/archiver.py
+++ b/devices/util/archiver.py
@@ -4,7 +4,12 @@ from logging import error
from .lofar2_config import configure_logging
from tango import DeviceProxy
from datetime import datetime, timedelta
-import mysql.connector as sql
+
+import mysql.connector
+from sqlalchemy import create_engine, and_
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy.orm.session import Session
+from util.archiver_base import *
def add_attribute_to_archiver(attribute: str, polling_period: float, event_period: float, archive_manager: str = 'archiving/hdbpp/confmanager01', archiver: str = 'archiving/hdbpp/eventsubscriber01'):
"""
@@ -20,124 +25,113 @@ def add_attribute_to_archiver(attribute: str, polling_period: float, event_perio
am.write_attribute('SetPollingPeriod', int(polling_period))
am.write_attribute('SetPeriodEvent', int(event_period))
am.AttributeAdd()
- am.AttributeStart(attribute) #the attribute archiving starts even without this line
+ #am.AttributeStart(attribute) #the attribute archiving starts even without this line
def remove_attribute_from_archiver(attribute: str, archive_manager: str = 'archiving/hdbpp/confmanager01'):
- '''
+ """
Stops the data archiving of the attribute passed as input, and remove it from the subscriber's list.
- '''
+ """
am = DeviceProxy(archive_manager)
am.AttributeStop(attribute)
am.AttributeRemove(attribute)
def connect_to_archiving_db(host: str = 'archiver-maria-db', port: int = 3306, user: str = 'root', password: str = 'secret', database: str = 'hdbpp'):
- '''
- Returns a connection to a MySQL DBMS using default or user-defined credentials.
- '''
- return sql.connect(host=host,port=port,user=user,password=password,database=database)
+ """
+ Returns a session to a MySQL DBMS using default or user-defined credentials.
+ """
+ engine = create_engine('mysql+mysqlconnector://'+user+':'+password+'@'+host+':'+str(port)+'/'+database)
+ Session = sessionmaker(bind=engine)
+ return Session()
def get_all_archived_attributes():
- '''
+ """
Returns a list of the archived attributes in the DB.
- '''
- db = connect_to_archiving_db()
- cursor = db.cursor()
- sql_script = 'SELECT att_name FROM att_conf'
- cursor.execute(sql_script)
- result = cursor.fetchall()
- attrs = [item[0] for item in result]
+ """
+ session = connect_to_archiving_db()
+ attrs = session.query(Attribute).order_by(Attribute.att_conf_id).all()
+ # Returns the representation as set in __repr__ method of the mapper class
return attrs
-def get_attribute_id(attribute: str):
- '''
+def get_attribute_id(attribute_fqname: str):
+ """
Takes as input the fully-qualified name of an attribute and returns its id.
- '''
- db = connect_to_archiving_db()
- cursor = db.cursor()
+ """
+ session = connect_to_archiving_db()
try:
- [domain, family, member, name] = attribute.split('/')
+ [domain, family, member, name] = attribute_fqname.split('/')
except:
print("Attribute name error. Use FQDN - eg: LTS/Device/1/Attribute")
return
- attrid_sql_script = "SELECT att_conf_id \
- FROM att_conf \
- WHERE domain = %s AND family = %s AND member = %s AND name = %s;"
- attrid_params = (domain,family,member,name)
- cursor.execute(attrid_sql_script,attrid_params)
try:
- attr_id = cursor.fetchone()[0]
- return attr_id
+ result = session.query(Attribute.att_conf_id).filter(and_(Attribute.domain == domain, Attribute.family == family, \
+ Attribute.member == member, Attribute.name == name)).one()
+ return result[0]
except TypeError:
print("Attribute not found!")
return
-def get_attribute_datatype(attribute: str):
- '''
+def get_attribute_datatype(attribute_fqname: str):
+ """
Takes as input the fully-qualified name of an attribute and returns its Data-Type.
Data Type name indicates the type (e.g. string, int, ...) and the read/write property. The name is used
as DB table name suffix in which values are stored.
- '''
- db = connect_to_archiving_db()
- cursor = db.cursor()
+ """
+ session = connect_to_archiving_db()
try:
- [domain, family, member, name] = attribute.split('/')
+ [domain, family, member, name] = attribute_fqname.split('/')
except:
print("Attribute name error. Use FQDN - eg: LTS/Device/1/Attribute")
return
- attr_sql_script = "SELECT att_conf_data_type.data_type \
- FROM att_conf_data_type JOIN att_conf ON att_conf.att_conf_data_type_id = att_conf_data_type.att_conf_data_type_id \
- WHERE att_conf.domain = %s AND att_conf.family = %s AND att_conf.member = %s AND att_conf.name = %s;"
- attrid_params = (domain,family,member,name)
- cursor.execute(attr_sql_script,attrid_params)
try:
- attr_datatype = cursor.fetchone()[0]
- return attr_datatype
+ result = session.query(DataType.data_type).join(Attribute,Attribute.att_conf_data_type_id==DataType.att_conf_data_type_id).\
+ filter(and_(Attribute.domain == domain, Attribute.family == family, Attribute.member == member, Attribute.name == name)).one()
+ return result[0]
except TypeError:
print("Attribute not found!")
return
-
-def get_attribute_value_by_hours(attribute: str, hours: float = 1):
- '''
- Takes as input the attribute name and the number of past hours since the actual time (e.g. hours=1
- retrieves values in the last hour, hours=8.5 retrieves values in the last eight hours and half).
+
+def get_attribute_value_by_hours(attribute_fqname: str, hours: float = 1.0):
+ """
+ Takes as input the attribute fully-qualified name and the number of past hours since the actual time
+ (e.g. hours=1 retrieves values in the last hour, hours=8.5 retrieves values in the last eight hours and half).
Returns a list of timestamps and a list of values
- '''
- attr_id = get_attribute_id(attribute)
- attr_datatype = get_attribute_datatype(attribute)
+ """
+ attr_id = get_attribute_id(attribute_fqname)
+ attr_datatype = get_attribute_datatype(attribute_fqname)
attr_table_name = 'att_'+str(attr_datatype)
- db = connect_to_archiving_db()
- cursor = db.cursor()
+ # Retrieves the class that maps the DB table given the tablename
+ base_class = get_class_by_tablename(attr_table_name)
+ session = connect_to_archiving_db()
+ # Retrieves the timestamp
time_now = datetime.now()
time_delta = time_now - timedelta(hours=hours)
- history_sql_script = "SELECT data_time, value_r \
- FROM " + attr_table_name + " INNER JOIN att_conf ON att_conf.att_conf_id = " + attr_table_name +".att_conf_id \
- WHERE att_conf.att_conf_id = %s AND data_time >= %s AND data_time <= %s \
- ORDER BY data_time;"
- history_params = (attr_id,str(time_delta.strftime("%Y-%m-%d %X")),str(time_now.strftime("%Y-%m-%d %X")))
- cursor.execute(history_sql_script,history_params)
- result = cursor.fetchall()
- timestamp = [item[0].strftime("%Y-%m-%d %X:%f") for item in result]
- value = [item[1] for item in result]
- return timestamp,value
+ # Converts the timestamps in the right format for the query
+ time_now_db = str(time_now.strftime("%Y-%m-%d %X"))
+ time_delta_db = str(time_delta.strftime("%Y-%m-%d %X"))
+ result = session.query(base_class).\
+ join(Attribute,Attribute.att_conf_id==base_class.att_conf_id).\
+ filter(and_(Attribute.att_conf_id == attr_id,base_class.data_time >= time_delta_db, \
+ base_class.data_time <= time_now_db)).order_by(base_class.data_time).all()
+ #timestamp = [item[0].strftime("%Y-%m-%d %X:%f") for item in result]
+ #value = [item[1] for item in result]
+ return result
-def get_attribute_value_by_interval(attribute: str, start_time: datetime, stop_time: datetime):
+def get_attribute_value_by_interval(attribute_fqname: str, start_time: datetime, stop_time: datetime):
'''
Takes as input the attribute name and a certain starting and ending point-time.
The datetime format is pretty flexible (e.g. "YYYY-MM-dd hh:mm:ss").
Returns a list of timestamps and a list of values
'''
- attr_id = get_attribute_id(attribute)
- attr_datatype = get_attribute_datatype(attribute)
+ attr_id = get_attribute_id(attribute_fqname)
+ attr_datatype = get_attribute_datatype(attribute_fqname)
attr_table_name = 'att_'+str(attr_datatype)
- db = connect_to_archiving_db()
- cursor = db.cursor()
- history_sql_script = "SELECT data_time, value_r \
- FROM " + attr_table_name + " INNER JOIN att_conf ON att_conf.att_conf_id = " + attr_table_name +".att_conf_id \
- WHERE att_conf.att_conf_id = %s AND data_time >= %s AND data_time <= %s \
- ORDER BY data_time;"
- history_params = (attr_id,str(start_time),str(stop_time))
- cursor.execute(history_sql_script,history_params)
- result = cursor.fetchall()
- timestamp = [item[0].strftime("%Y-%m-%d %X:%f") for item in result]
- value = [item[1] for item in result]
- return timestamp,value
\ No newline at end of file
+ # Retrieves the class that maps the DB table given the tablename
+ base_class = get_class_by_tablename(attr_table_name)
+ session = connect_to_archiving_db()
+ result = session.query(base_class).\
+ join(Attribute,Attribute.att_conf_id==base_class.att_conf_id).\
+ filter(and_(Attribute.att_conf_id == attr_id,base_class.data_time >= str(start_time), \
+ base_class.data_time <= str(stop_time))).order_by(base_class.data_time).all()
+ #timestamp = [item[0].strftime("%Y-%m-%d %X:%f") for item in result]
+ #value = [item[1] for item in result]
+ return result
\ No newline at end of file
diff --git a/devices/util/archiver_base.py b/devices/util/archiver_base.py
new file mode 100644
index 0000000000000000000000000000000000000000..9d8e1b01f169be37c2557de4012980e5becbe953
--- /dev/null
+++ b/devices/util/archiver_base.py
@@ -0,0 +1,79 @@
+#! /usr/bin/env python3
+
+from sqlalchemy.orm import declarative_base
+from sqlalchemy import Column, Integer, String
+from sqlalchemy.dialects.mysql import DOUBLE,TIMESTAMP
+from sqlalchemy.sql.expression import table
+
+#Declarative system used to define classes mapped to relational DB tables
+Base = declarative_base()
+
+class Attribute(Base):
+ '''
+ Class that represents a Tango Attribute mapped to table 'att_conf'
+ '''
+ __tablename__ = 'att_conf'
+ __table_args__ = {'extend_existing': True}
+
+ att_conf_id = Column(Integer, primary_key=True)
+ att_name = Column(String)
+ att_conf_data_type_id = Column(Integer)
+ att_ttl = Column(Integer)
+ facility = Column(String)
+ domain = Column(String)
+ family = Column(String)
+ member = Column(String)
+ name = Column(String)
+
+
+ def __repr__(self):
+ return "<Attribute(fullname='%s',data_type ='%s',ttl='%s',facility ='%s',domain ='%s',family ='%s',member ='%s',name ='%s')>" \
+ % (self.att_name,self.att_conf_data_type_id,self.att_ttl,self.facility,self.domain,self.family,self.member,self.name)
+
+class DataType(Base):
+ '''
+ Class that represents a Tango Data Type mapped to table 'att_conf_data_type'
+ '''
+ __tablename__ = 'att_conf_data_type'
+ __table_args__ = {'extend_existing': True}
+
+ att_conf_data_type_id = Column(Integer, primary_key=True)
+ data_type = Column(String)
+
+ def __repr__(self):
+ return "<DataType(type='%s')>" \
+ % (self.data_type)
+
+class Scalar_Double_RO(Base):
+ '''
+ Class that represents a Tango Scalar Read-Only Value mapped to table 'att_scalar_devdouble_ro'
+ '''
+ __tablename__ = 'att_scalar_devdouble_ro'
+ __table_args__ = {'extend_existing': True}
+ # Primary key is not defined for this kind of tables, but SQLAlchemy requires a mandatory
+ # primary key definition. Anyway, this definition is on Python-side and does not compromise
+ # DBMS architecture
+
+ att_conf_id = Column(Integer, primary_key=True)
+ data_time = Column(TIMESTAMP)
+ recv_time = Column(TIMESTAMP)
+ insert_time = Column(TIMESTAMP, primary_key=True)
+ value_r = Column(DOUBLE, primary_key=True)
+ quality = Column(Integer)
+ att_error_desc_id = Column(Integer)
+
+ def __repr__(self):
+ return "<Scalar_Double_RO(att_conf_id='%s',data_time='%s',recv_time='%s',insert_time='%s',value_r='%s',quality='%s',att_error_desc_id='%s')>" \
+ % (self.att_conf_id,self.data_time,self.recv_time,self.insert_time,self.value_r,self.quality,self.att_error_desc_id)
+
+def get_class_by_tablename(tablename: str):
+ """
+ Returns class reference mapped to a table.
+ """
+ for mapper in Base.registry.mappers:
+ c = mapper.class_
+ classname = c.__name__
+ if not classname.startswith('_'):
+ if hasattr(c, '__tablename__') and c.__tablename__ == tablename:
+ return c
+ return None
\ No newline at end of file
diff --git a/docker-compose/jupyter/Dockerfile b/docker-compose/jupyter/Dockerfile
index 2ba7c46c68a21e4862ac67ef693a328c93fe540f..79e17ae5f7db30cda225600e201b570ad5d0c6df 100644
--- a/docker-compose/jupyter/Dockerfile
+++ b/docker-compose/jupyter/Dockerfile
@@ -24,7 +24,7 @@ RUN sudo pip3 install python-logstash-async
COPY jupyter-notebook /usr/local/bin/jupyter-notebook
#Install further python modules
-RUN sudo pip3 install mysql-connector-python
+RUN sudo pip3 install mysql-connector-python sqlalchemy
# Add Tini. Tini operates as a process subreaper for jupyter. This prevents kernel crashes.
ENV TINI_VERSION v0.6.0
diff --git a/jupyter-notebooks/archiving_test.ipynb b/jupyter-notebooks/archiving_test.ipynb
index 4ba8d744c2f32ee8eb1ab8b0677708c9dd2f1008..15db7b79f5d7a8f6661ef04b44e56cb3ddc40c08 100644
--- a/jupyter-notebooks/archiving_test.ipynb
+++ b/jupyter-notebooks/archiving_test.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 1,
"id": "efcbb5de",
"metadata": {},
"outputs": [],
@@ -15,7 +15,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 3,
"id": "63bbd665",
"metadata": {},
"outputs": [
@@ -25,7 +25,7 @@
"['rnd1', 'rnd2', 'rnd3', 'rnd4', 'rnd5', 'rnd6', 'rnd7', 'rnd8', 'rnd9', 'rnd10', 'rnd11', 'rnd12', 'rnd13', 'rnd14', 'rnd15', 'rnd16', 'rnd17', 'rnd18', 'rnd19', 'rnd20', 'State', 'Status']"
]
},
- "execution_count": 7,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -37,7 +37,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 4,
"id": "3f2f22af",
"metadata": {},
"outputs": [
@@ -47,7 +47,7 @@
"['AttributeOKNumber', 'AttributeNokNumber', 'AttributePendingNumber', 'AttributeNumber', 'SetAttributeName', 'SetPollingPeriod', 'SetAbsoluteEvent', 'SetRelativeEvent', 'SetPeriodEvent', 'SetCodePushedEvent', 'SetArchiver', 'AttributeMaxStoreTime', 'AttributeMinStoreTime', 'AttributeMaxProcessingTime', 'AttributeMinProcessingTime', 'AttributeRecordFreq', 'AttributeFailureFreq', 'AttributeStartedNumber', 'AttributeStoppedNumber', 'AttributeMaxPendingNumber', 'AttributePausedNumber', 'SetTTL', 'SetStrategy', 'Context', 'ArchiverList', 'ArchiverStatus', 'ArchiverStatisticsResetTime', 'ArchiverContext', 'ContextsList', 'State', 'Status']"
]
},
- "execution_count": 9,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -59,23 +59,24 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"id": "62a325e0",
"metadata": {},
"outputs": [],
"source": [
- "cm.write_attribute('SetAttributeName',\"LTS/RandomData/1/rnd2\")\n",
+ "att_fqn = \"LTS/RandomData/1/rnd15\"\n",
+ "cm.write_attribute('SetAttributeName', att_fqn)\n",
"cm.read_attribute('SetArchiver')\n",
"cm.read_attribute('ArchiverList')\n",
"cm.write_attribute('SetArchiver',\"archiving/hdbpp/eventsubscriber01\")\n",
"cm.write_attribute('SetStrategy',\"ALWAYS\")\n",
- "cm.write_attribute('SetPollingPeriod',1000)\n",
+ "cm.write_attribute('SetPollingPeriod',5000)\n",
"cm.write_attribute('SetPeriodEvent',1000)"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 9,
"id": "60935266",
"metadata": {},
"outputs": [],
@@ -85,17 +86,17 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 10,
"id": "c8e482f5",
"metadata": {},
"outputs": [],
"source": [
- "cm.AttributeStop(\"LTS/RandomData/1/rnd2\")"
+ "cm.AttributeStop(att_fqn)"
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 9,
"id": "e2b3bded",
"metadata": {},
"outputs": [],
@@ -106,22 +107,17 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 10,
"id": "a6305a27",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "['tango://databaseds:10000/lts/mock/1/mocktemperature',\n",
- " 'tango://databaseds:10000/lts/randomdata/1/rnd1',\n",
- " 'tango://databaseds:10000/lts/randomdata/1/rnd2',\n",
- " 'tango://databaseds:10000/lts/randomdata/1/rnd3',\n",
- " 'tango://databaseds:10000/lts/randomdata/1/rnd4',\n",
- " 'tango://databaseds:10000/lts/randomdata/1/rnd9']"
+ "['tango://databaseds:10000/lts/randomdata/1/rnd2']"
]
},
- "execution_count": 11,
+ "execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
@@ -132,17 +128,17 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 11,
"id": "27084117",
"metadata": {},
"outputs": [],
"source": [
- "timestamps, values = get_attribute_value_by_hours('lts/randomdata/1/rnd3',48)"
+ "timestamps, values = get_attribute_value_by_hours('lts/randomdata/1/rnd2',24)"
]
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 12,
"id": "d654a1ed",
"metadata": {},
"outputs": [
@@ -150,7 +146,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "[0.7606279998610853, 0.0010674439997622187, 0.3426962798935904, 0.6954755884710412, 0.06801608385007174, 0.040349637589830456, 0.844327803419971, 0.3776016929850671, 0.5553140388033995, 0.2007037700414519, 0.4108507825166615, 0.39299789699307863, 0.900994474294906, 0.8762676802800669, 0.09242913994120883, 0.8492810540518783, 0.4941474700658586, 0.9702291989250298, 0.9133778275466953, 0.0009224307639393858, 0.09833878951681452, 0.05001240736525259, 0.3454684705682859, 0.4645536669550526, 0.455728184090888, 0.0694213376599574, 0.09887773110333054, 0.9858453745710541, 0.699131795141024, 0.7042101034860654, 0.7007617172483673, 0.08543849103795476, 0.00585176908982199, 0.1796081401098779, 0.6238261213761166, 0.4650356584366875, 0.1562834203730672, 0.5405479018321905, 0.196054067601097, 0.32475368240313485, 0.7069400740598899, 0.07144996666541847, 0.05484307256342036, 0.43525275299433874, 0.2767588305376758, 0.6436453632856112, 0.06133622585009035, 0.2915541952515449, 0.10353942065673583, 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0.10879397245015476, 0.9329462662872089, 0.17380066630195212, 0.6734988303728583, 0.251117674407599, 0.31390876661057887, 0.8352878023082652, 0.09476697504391585, 0.8426221596148499, 0.1950432777669222, 0.010613115497807413, 0.30888430925501154, 0.7110559766366373, 0.4077778546649957, 0.6175681295346717, 0.3623802769358293, 0.43107373384531555, 0.8542365012763854, 0.5623074374879531, 0.1538079070411733, 0.428568144909361, 0.18931241498745865, 0.7841627695969312, 0.6869731509118046, 0.26079139925176487, 0.7866762761601347, 0.7152833318410747, 0.6267748315727587, 0.9777022577801266, 0.4398755535187675, 0.42432999898503165, 0.9007952854181114, 0.38605568235108956, 0.5064665326000347, 0.6350751612111938, 0.4336080245974776, 0.3375567201483318, 0.6452226214562595, 0.5478423609666304, 0.9367125061020438, 0.29108644276325846, 0.20464822010028982, 0.20892739426105456, 0.44554750644308583, 0.8454797352264943, 0.1597922254876556, 0.9826270413768617, 0.8627211469093488, 0.4698921646584201, 0.050616217946508835, 0.9063448978049136, 0.4223994781275632, 0.3923025717428701, 0.5981640891766775, 0.44014856450946716, 0.23586201299322784, 0.7322043721234809, 0.20249964078141502, 0.4235601096395526, 0.5486066191663903, 0.6645277527679566, 0.4602477248693414, 0.6840710566915555, 0.7059390641114205, 0.3284523618652845, 0.2822754301085365, 0.8151966889773219, 0.9903486852260439, 0.3388864471924554, 0.8672088518734029, 0.4972069308354532]\n"
+ "[0.20784630214668376, 0.3019711225097942, 0.5245422053030214, 0.2700524910134535]\n"
]
}
],
@@ -160,17 +156,17 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 14,
"id": "b6145fbe",
"metadata": {},
"outputs": [],
"source": [
- "timestamps, values = get_attribute_value_by_interval('lts/randomdata/1/rnd4','2021-06-07 13:20:00', '2021-06-07 13:21:00')"
+ "timestamps, values = get_attribute_value_by_interval('lts/randomdata/1/rnd2','2021-06-18 13:20:00', '2021-06-19 13:21:00')"
]
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 15,
"id": "a012d71b",
"metadata": {},
"outputs": [
@@ -178,7 +174,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "[0.008721170319330174, 0.2778457820295206, 0.08771206166994494, 0.08995306943783543, 0.4252407827730984, 0.8567703113574187, 0.6443064078665959, 0.820472639265817, 0.6724153389885987, 0.9737917508764153, 0.2574030042513442, 0.11365468019523772, 0.6469867671892283, 0.22054997528331632, 0.19647883265352262, 0.92819713442957, 0.6054952676099805, 0.4385335924804723, 0.9951106389720911, 0.08011384237343688, 0.9466835316121099, 0.8420223458578644, 0.7965281292100906, 0.7377238724947689, 0.8061675028145234, 0.459483229064807, 0.5061376890824932, 0.888112952681436, 0.8756426396399274, 0.34324035972784217, 0.8499336644006312, 0.21108646761550232, 0.8823657883678858, 0.11452389757530734, 0.23893284393127756, 0.9960508103583509, 0.5909251065648178, 0.8261812350213734, 0.8683854913299328, 0.3032002462717681, 0.7868411998647392, 0.2884397488152086, 0.12188186111639632, 0.2398054609920065, 0.15787661103771455, 0.07772481225925076, 0.09871638585797682, 0.8321893810767013, 0.5567973595348706, 0.6985377902973685, 0.0850308577504425, 0.11832525288301632, 0.7279176045413792, 0.6979789043157206, 0.6033096853838185, 0.07090560942957136, 0.020106929389148265, 0.27391797898197723, 0.20930768646037212, 0.2445019933472372]\n"
+ "[0.20784630214668376, 0.3019711225097942, 0.5245422053030214, 0.2700524910134535]\n"
]
}
],
diff --git a/jupyter-notebooks/archiving_test_v2.ipynb b/jupyter-notebooks/archiving_test_v2.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..dd6101f97e192d3d56ee4ed9e5aa145a1d4fa6d2
--- /dev/null
+++ b/jupyter-notebooks/archiving_test_v2.ipynb
@@ -0,0 +1,220 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "c7dd05cd",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "sys.path.append('/hosthome/tango/devices')\n",
+ "from util.archiver import *\n",
+ "from util.archiver_base import *\n",
+ "import mysql.connector"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "57834b5e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dev_rand = DeviceProxy(\"LTS/RandomData/1\")\n",
+ "dev_rand.get_attribute_list()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6816f78f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cm = DeviceProxy(\"archiving/hdbpp/confmanager01\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7bda559b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "get_all_archived_attributes()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f0ef38a4",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "add_attribute_to_archiver('lts/randomdata/1/rnd7',3000,1000)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7d0746e7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "remove_attribute_from_archiver('lts/randomdata/1/rnd7')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "129a75c6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<Attribute(fullname='tango://databaseds:10000/lts/randomdata/1/rnd2',data_type ='37',ttl='0',facility ='tango://databaseds:10000',domain ='lts',family ='randomdata',member ='1',name ='rnd2')>,\n",
+ " <Attribute(fullname='tango://databaseds:10000/lts/randomdata/1/rnd3',data_type ='37',ttl='0',facility ='tango://databaseds:10000',domain ='lts',family ='randomdata',member ='1',name ='rnd3')>,\n",
+ " <Attribute(fullname='tango://databaseds:10000/lts/randomdata/1/rnd15',data_type ='37',ttl='0',facility ='tango://databaseds:10000',domain ='lts',family ='randomdata',member ='1',name ='rnd15')>,\n",
+ " <Attribute(fullname='tango://databaseds:10000/lts/randomdata/1/rnd7',data_type ='37',ttl='0',facility ='tango://databaseds:10000',domain ='lts',family ='randomdata',member ='1',name ='rnd7')>]"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "get_all_archived_attributes()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "5f9865ee",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "4"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "main_att = 'lts/randomdata/1/rnd7'\n",
+ "get_attribute_id(main_att)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "2a3707a3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'scalar_devdouble_ro'"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "get_attribute_datatype(main_att)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "18100623",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:21.892781',recv_time='2021-06-23 15:00:23.040862',insert_time='2021-06-23 15:00:23.042065',value_r='0.9263038657',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:24.909897',recv_time='2021-06-23 15:00:24.911329',insert_time='2021-06-23 15:00:24.912696',value_r='0.6869173892',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:27.909636',recv_time='2021-06-23 15:00:27.910767',insert_time='2021-06-23 15:00:27.912330',value_r='0.1070759253',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:30.909940',recv_time='2021-06-23 15:00:30.911529',insert_time='2021-06-23 15:00:30.913542',value_r='0.2699634793',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:33.910365',recv_time='2021-06-23 15:00:33.910897',insert_time='2021-06-23 15:00:33.911735',value_r='0.8323236082',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:36.910232',recv_time='2021-06-23 15:00:36.911389',insert_time='2021-06-23 15:00:36.912912',value_r='0.7979368397',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:39.909182',recv_time='2021-06-23 15:00:39.909785',insert_time='2021-06-23 15:00:39.910372',value_r='0.2178505902',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:42.909868',recv_time='2021-06-23 15:00:42.911390',insert_time='2021-06-23 15:00:42.913124',value_r='0.6949464171',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:45.909946',recv_time='2021-06-23 15:00:45.911036',insert_time='2021-06-23 15:00:45.912787',value_r='0.1093199257',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:48.909615',recv_time='2021-06-23 15:00:48.910722',insert_time='2021-06-23 15:00:48.912259',value_r='0.9768430390',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:51.909200',recv_time='2021-06-23 15:00:51.910290',insert_time='2021-06-23 15:00:51.911793',value_r='0.8888621550',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:54.909296',recv_time='2021-06-23 15:00:54.910679',insert_time='2021-06-23 15:00:54.912332',value_r='0.3799629383',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='4',data_time='2021-06-23 15:00:57.909804',recv_time='2021-06-23 15:00:57.910850',insert_time='2021-06-23 15:00:57.912311',value_r='0.7681945847',quality='2',att_error_desc_id='None')>]"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "get_attribute_value_by_hours(main_att,24)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "ab476d57",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<Scalar_Double_RO(att_conf_id='3',data_time='2021-06-21 14:50:06.179562',recv_time='2021-06-21 14:50:07.180444',insert_time='2021-06-21 14:50:07.204869',value_r='0.1400088842',quality='2',att_error_desc_id='None')>,\n",
+ " <Scalar_Double_RO(att_conf_id='3',data_time='2021-06-21 14:50:10.213110',recv_time='2021-06-21 14:50:10.214549',insert_time='2021-06-21 14:50:10.216117',value_r='0.6627579896',quality='2',att_error_desc_id='None')>]"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "get_attribute_value_by_interval('lts/randomdata/1/rnd15', '2021-06-21 13:20:00', '2021-06-23 15:21:00')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "21c9b91b",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "StationControl",
+ "language": "python",
+ "name": "stationcontrol"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}