I have noticed a number of people requesting a way to show accumulated data
in the graphs for Weewx, mostly rain data. As I also need this myself, I
did a shot on how to implement it.
As suggested in a post I saw, the solution was to add another aggregation
type, called 'accu', which is then grapped in weewx/manager.py and handled
to sum the data from the first point in the selected data interval,
starting from zero. You may then use it for any interval needed.
To ease the implementation, it is only supported if an aggregate_interval
is also defined, even if this was not strictly needed.
I have only changed the file [/usr/share/weewx/]weewx/manager.py, based on
weewx v3.7.1. It is attached.
To use it, just set the aggregate_type to accu in the skin.conf file, like:
[[[dayrain]]]
# Make sure the y-axis increment is at least 0.02 for the rain
plot
yscale = None, None, 0.02
plot_type = bar
[[[[rain]]]]
aggregate_type = sum
aggregate_interval = 3600
label = Rain (hourly total)
[[[dayraintot]]]
yscale = None, None, 0.02
plot_type = bar
[[[[rain]]]]
aggregate_type = accu
aggregate_interval = 600
label = Rain (accumulated)
You may want to have a smaller aggregate_interval for the accu than for the
sum.
This of cause is only usable for 'counting' datatypes. Trying to use it on
eg. temperature will not give meaningfull results.
Please fill free to use it, and if it is good enough, to integrate it into
the main code branch.
Best regards
Henrik
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#
# Copyright (c) 2009-2017 Tom Keffer <tkef...@gmail.com>
#
# See the file LICENSE.txt for your full rights.
#
"""Classes and functions for interfacing with a weewx archive."""
from __future__ import with_statement
import math
import syslog
import sys
import datetime
import time
import weewx.accum
from weewx.units import ValueTuple
import weewx.units
import weeutil.weeutil
import weedb
from weeutil.weeutil import timestamp_to_string, isMidnight, to_int
#==============================================================================
# class Manager
#==============================================================================
class Manager(object):
"""Manages a database table. Offers a number of convenient member
functions for querying and inserting data into the table.
These functions encapsulate whatever sql statements are needed.
A limitation of this implementation is that it caches the timestamps of the
first and last record in the table. Normally, the caches get updated as data comes
in. However, if one manager is updating the table, wile another is doing
aggregate queries, the latter manager will be unaware of later records in
the database, and may choose the wrong query strategy. In this might be the case,
call member function _sync() before starting the query.
USEFUL ATTRIBUTES
database_name: The name of the database the manager is bound to.
table_name: The name of the main, archive table.
sqlkeys: A list of the SQL keys that the database table supports.
obskeys: A list of the observation types that the database table supports.
std_unit_system: The unit system used by the database table.
first_timestamp: The timestamp of the earliest record in the table.
last_timestamp: The timestamp of the last record in the table."""
def __init__(self, connection, table_name='archive', schema=None):
"""Initialize an object of type Manager.
connection: A weedb connection to the database to be managed.
table_name: The name of the table to be used in the database. Default
is 'archive'.
schema: The schema to be used. Optional. If not supplied, then an
exception of type weedb.ProgrammingError will be raised if the database
does not exist, and of type weedb.UnitializedDatabase if it exists, but
has not been initialized.
"""
self.connection = connection
self.table_name = table_name
# Now get the SQL types.
try:
self.sqlkeys = self.connection.columnsOf(self.table_name)
except weedb.ProgrammingError:
# Database exists, but is uninitialized. Did the caller supply
# a schema?
if schema is None:
# No. Nothing to be done.
syslog.syslog(syslog.LOG_ERR, "manager: Cannot get columns of table %s, and no schema specified" % self.table_name)
raise
# Database exists, but has not been initialized. Initialize it.
self._initialize_database(schema)
# Try again:
self.sqlkeys = self.connection.columnsOf(self.table_name)
# Set up cached data:
self._sync()
@classmethod
def open(cls, database_dict, table_name='archive'):
"""Open and return a Manager or a subclass of Manager.
database_dict: A database dictionary holding the information necessary
to open the database.
table_name: The name of the table to be used in the database. Default
is 'archive'. """
# This will raise a weedb.OperationalError if the database does
# not exist. The 'open' method we are implementing never attempts an
# initialization, so let it go by.
connection = weedb.connect(database_dict)
# Create an instance of the right class and return it:
dbmanager = cls(connection, table_name)
return dbmanager
@classmethod
def open_with_create(cls, database_dict, table_name='archive', schema=None):
"""Open and return a Manager or a subclass of Manager, initializing
if necessary.
database_dict: A database dictionary holding the information necessary
to open the database.
table_name: The name of the table to be used in the database. Default
is 'archive'.
schema: The schema to be used. If not supplied, then an
exception of type weedb.OperationalError will be raised if the database
does not exist, and of type weedb.UnitializedDatabase if it exists, but
has not been initialized.
"""
# This will raise a weedb.OperationalError if the database does
# not exist.
try:
connection = weedb.connect(database_dict)
except weedb.OperationalError:
# Database does not exist. Did the caller supply a schema?
if schema is None:
# No. Nothing to be done.
syslog.syslog(syslog.LOG_ERR, "manager: Cannot open database, and no schema specified")
raise
# Yes. Create the database:
weedb.create(database_dict)
# Now I can get a connection
connection = weedb.connect(database_dict)
# Create an instance of the right class and return it:
dbmanager = cls(connection, table_name=table_name, schema=schema)
return dbmanager
@property
def database_name(self):
return self.connection.database_name
@property
def obskeys(self):
"""The list of observation types"""
return [obs_type for obs_type in self.sqlkeys if obs_type not in ['dateTime', 'usUnits', 'interval']]
def close(self):
self.connection.close()
del self.sqlkeys
del self.first_timestamp
del self.last_timestamp
del self.std_unit_system
def __enter__(self):
return self
def __exit__(self, etyp, einst, etb): # @UnusedVariable
self.close()
def _initialize_database(self, schema):
"""Initialize the tables needed for the archive.
schema: The schema to be used
"""
# List comprehension of the types, joined together with commas. Put
# the SQL type in backquotes, because at least one of them ('interval')
# is a MySQL reserved word
_sqltypestr = ', '.join(["`%s` %s" % _type for _type in schema])
try:
with weedb.Transaction(self.connection) as _cursor:
_cursor.execute("CREATE TABLE %s (%s);" % (self.table_name, _sqltypestr, ))
except weedb.DatabaseError, e:
syslog.syslog(syslog.LOG_ERR, "manager: "
"Unable to create table '%s' in database '%s': %s" %
(self.table_name, self.database_name, e))
raise
syslog.syslog(syslog.LOG_NOTICE, "manager: "
"Created and initialized table '%s' in database '%s'" %
(self.table_name, self.database_name))
def _sync(self):
"""Resynch the internal caches."""
# Fetch the first row in the database to determine the unit system in
# use. If the database has never been used, then the unit system is
# still indeterminate --- set it to 'None'.
_row = self.getSql("SELECT usUnits FROM %s LIMIT 1;" % self.table_name)
self.std_unit_system = _row[0] if _row is not None else None
# Cache the first and last timestamps
self.first_timestamp = self.firstGoodStamp()
self.last_timestamp = self.lastGoodStamp()
def lastGoodStamp(self):
"""Retrieves the epoch time of the last good archive record.
returns: Time of the last good archive record as an epoch time, or
None if there are no records."""
_row = self.getSql("SELECT MAX(dateTime) FROM %s" % self.table_name)
return _row[0] if _row else None
def firstGoodStamp(self):
"""Retrieves earliest timestamp in the archive.
returns: Time of the first good archive record as an epoch time, or
None if there are no records."""
_row = self.getSql("SELECT MIN(dateTime) FROM %s" % self.table_name)
return _row[0] if _row else None
def addRecord(self, record_obj, log_level=syslog.LOG_NOTICE, accumulator=None):
"""Commit a single record or a collection of records to the archive.
record_obj: Either a data record, or an iterable that can return data
records. Each data record must look like a dictionary, where the keys
are the SQL types and the values are the values to be stored in the
database.
log_level: What syslog level to use for any logging. Default is syslog.LOG_NOTICE.
"""
# Determine if record_obj is just a single dictionary instance
# (in which case it will have method 'keys'). If so, wrap it in
# something iterable (a list):
record_list = [record_obj] if hasattr(record_obj, 'keys') else record_obj
min_ts = None
max_ts = 0
with weedb.Transaction(self.connection) as cursor:
for record in record_list:
try:
# If the accumulator time matches the record we are working with,
# use it to update the highs and lows.
if accumulator and record_obj['dateTime'] == accumulator.timespan.stop:
self._updateHiLo(accumulator, cursor)
# Then add the record to the archives:
self._addSingleRecord(record, cursor, log_level)
min_ts = min(min_ts, record['dateTime']) if min_ts is not None else record['dateTime']
max_ts = max(max_ts, record['dateTime'])
except (weedb.IntegrityError, weedb.OperationalError), e:
syslog.syslog(syslog.LOG_ERR, "manager: "
"Unable to add record %s to database '%s': %s" %
(weeutil.weeutil.timestamp_to_string(record['dateTime']),
self.database_name, e))
# Update the cached timestamps. This has to sit outside the
# transaction context, in case an exception occurs.
self.first_timestamp = min(min_ts, self.first_timestamp)
self.last_timestamp = max(max_ts, self.last_timestamp)
def _addSingleRecord(self, record, cursor, log_level):
"""Internal function for adding a single record to the database."""
if record['dateTime'] is None:
syslog.syslog(syslog.LOG_ERR,
"manager: Archive record with null time encountered")
raise weewx.ViolatedPrecondition("Manager record with null time encountered.")
# Check to make sure the incoming record is in the same unit
# system as the records already in the database:
self._check_unit_system(record['usUnits'])
# Only data types that appear in the database schema can be
# inserted. To find them, form the intersection between the
# set of all record keys and the set of all sql keys
record_key_set = set(record.keys())
insert_key_set = record_key_set.intersection(self.sqlkeys)
# Convert to an ordered list:
key_list = list(insert_key_set)
# Get the values in the same order:
value_list = [record[k] for k in key_list]
# This will a string of sql types, separated by commas. Because
# some of the weewx sql keys (notably 'interval') are reserved
# words in MySQL, put them in backquotes.
k_str = ','.join(["`%s`" % k for k in key_list])
# This will be a string with the correct number of placeholder
# question marks:
q_str = ','.join('?' * len(key_list))
# Form the SQL insert statement:
sql_insert_stmt = "INSERT INTO %s (%s) VALUES (%s)" % (self.table_name, k_str, q_str)
cursor.execute(sql_insert_stmt, value_list)
syslog.syslog(log_level, "manager: Added record %s to database '%s'" %
(weeutil.weeutil.timestamp_to_string(record['dateTime']),
self.database_name))
def _updateHiLo(self, accumulator, cursor):
pass
def genBatchRows(self, startstamp=None, stopstamp=None):
"""Generator function that yields raw rows from the archive database
with timestamps within an interval.
startstamp: Exclusive start of the interval in epoch time. If 'None',
then start at earliest archive record.
stopstamp: Inclusive end of the interval in epoch time. If 'None', then
end at last archive record.
yields: A list with the data records"""
_cursor = self.connection.cursor()
try:
if startstamp is None:
if stopstamp is None:
_gen = _cursor.execute("SELECT * FROM %s ORDER BY dateTime ASC" % self.table_name)
else:
_gen = _cursor.execute("SELECT * FROM %s WHERE dateTime <= ? ORDER BY dateTime ASC" % self.table_name, (stopstamp,))
else:
if stopstamp is None:
_gen = _cursor.execute("SELECT * FROM %s WHERE dateTime > ? ORDER BY dateTime ASC" % self.table_name, (startstamp,))
else:
_gen = _cursor.execute("SELECT * FROM %s WHERE dateTime > ? AND dateTime <= ? ORDER BY dateTime ASC" % self.table_name,
(startstamp, stopstamp))
_last_time = 0
for _row in _gen:
# The following is to get around a bug in sqlite when all the
# tables are in one file:
if _row[0] <= _last_time:
continue
_last_time = _row[0]
yield _row
finally:
_cursor.close()
def genBatchRecords(self, startstamp=None, stopstamp=None):
"""Generator function that yields records with timestamps within an
interval.
startstamp: Exclusive start of the interval in epoch time. If 'None',
then start at earliest archive record.
stopstamp: Inclusive end of the interval in epoch time. If 'None', then
end at last archive record.
yields: A dictionary where key is the observation type (eg, 'outTemp')
and the value is the observation value"""
for _row in self.genBatchRows(startstamp, stopstamp):
yield dict(zip(self.sqlkeys, _row)) if _row else None
def getRecord(self, timestamp, max_delta=None):
"""Get a single archive record with a given epoch time stamp.
timestamp: The epoch time of the desired record.
max_delta: The largest difference in time that is acceptable.
[Optional. The default is no difference]
returns: a record dictionary or None if the record does not exist."""
_cursor = self.connection.cursor()
try:
if max_delta:
time_start_ts = timestamp - max_delta
time_stop_ts = timestamp + max_delta
_cursor.execute("SELECT * FROM %s WHERE dateTime>=? AND dateTime<=? "\
"ORDER BY ABS(dateTime-?) ASC LIMIT 1" % self.table_name,
(time_start_ts, time_stop_ts, timestamp))
else:
_cursor.execute("SELECT * FROM %s WHERE dateTime=?" % self.table_name, (timestamp,))
_row = _cursor.fetchone()
return dict(zip(self.sqlkeys, _row)) if _row else None
finally:
_cursor.close()
def updateValue(self, timestamp, obs_type, new_value):
"""Update (replace) a single value in the database."""
self.connection.execute("UPDATE %s SET %s=? WHERE dateTime=?" %
(self.table_name, obs_type), (new_value, timestamp))
def getSql(self, sql, sqlargs=(), cursor=None):
"""Executes an arbitrary SQL statement on the database.
sql: The SQL statement
sqlargs: A tuple containing the arguments for the SQL statement
returns: a tuple containing the results
"""
_cursor = cursor or self.connection.cursor()
try:
_cursor.execute(sql, sqlargs)
return _cursor.fetchone()
finally:
if cursor is None:
_cursor.close()
def genSql(self, sql, sqlargs=()):
"""Generator function that executes an arbitrary SQL statement on
the database."""
_cursor = self.connection.cursor()
try:
for _row in _cursor.execute(sql, sqlargs):
yield _row
finally:
_cursor.close()
sql_dict = {'mintime' : "SELECT dateTime FROM %(table_name)s "\
"WHERE dateTime > %(start)s AND dateTime <= %(stop)s AND "\
"%(obs_type)s = (SELECT MIN(%(obs_type)s) FROM %(table_name)s "\
"WHERE dateTime > %(start)s and dateTime <= %(stop)s) AND %(obs_type)s IS NOT NULL",
'maxtime' : "SELECT dateTime FROM %(table_name)s "\
"WHERE dateTime > %(start)s AND dateTime <= %(stop)s AND "\
"%(obs_type)s = (SELECT MAX(%(obs_type)s) FROM %(table_name)s "\
"WHERE dateTime > %(start)s and dateTime <= %(stop)s) AND %(obs_type)s IS NOT NULL",
'last' : "SELECT %(obs_type)s FROM %(table_name)s "\
"WHERE dateTime = (SELECT MAX(dateTime) FROM %(table_name)s "\
"WHERE dateTime > %(start)s AND dateTime <= %(stop)s AND %(obs_type)s IS NOT NULL)",
'lasttime': "SELECT MAX(dateTime) FROM %(table_name)s "\
"WHERE dateTime > %(start)s AND dateTime <= %(stop)s AND %(obs_type)s IS NOT NULL"}
simple_sql = "SELECT %(aggregate_type)s(%(obs_type)s) FROM %(table_name)s "\
"WHERE dateTime > %(start)s AND dateTime <= %(stop)s AND %(obs_type)s IS NOT NULL"
def getAggregate(self, timespan, obs_type,
aggregate_type, **option_dict): # @UnusedVariable
"""Returns an aggregation of a statistical type for a given time period.
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
obs_type: The type over which aggregation is to be done (e.g., 'barometer',
'outTemp', 'rain', ...)
aggregate_type: The type of aggregation to be done.
option_dict: Not used in this version.
returns: A value tuple. First element is the aggregation value,
or None if not enough data was available to calculate it, or if the aggregation
type is unknown. The second element is the unit type (eg, 'degree_F').
The third element is the unit group (eg, "group_temperature") """
if aggregate_type not in ['sum', 'count', 'avg', 'max', 'min',
'mintime', 'maxtime', 'last', 'lasttime']:
raise weewx.ViolatedPrecondition("Invalid aggregation type '%s'" % aggregate_type)
interpolate_dict = {'aggregate_type' : aggregate_type,
'obs_type' : obs_type,
'table_name' : self.table_name,
'start' : timespan.start,
'stop' : timespan.stop}
select_stmt = Manager.sql_dict.get(aggregate_type, Manager.simple_sql)
_row = self.getSql(select_stmt % interpolate_dict)
_result = _row[0] if _row else None
# Look up the unit type and group of this combination of observation type and aggregation:
(t, g) = weewx.units.getStandardUnitType(self.std_unit_system, obs_type, aggregate_type)
# Form the value tuple and return it:
return weewx.units.ValueTuple(_result, t, g)
def getSqlVectors(self, timespan, obs_type,
aggregate_type=None,
aggregate_interval=None):
"""Get time and (possibly aggregated) data vectors within a time
interval.
This function is very similar to _getSqlVectors, except that for
special types 'windvec' and 'windgustvec', it returns wind data
broken down into its x- and y-components.
timespan: The timespan over which the aggregation is to be done.
obs_type: The observation type to be retrieved (e.g., 'outTemp', or 'windvec').
If this type is the special types 'windvec', or 'windgustvec', then
what will be returned is a vector of complex numbers.
aggregate_type: None if no aggregation is desired, otherwise the type
of aggregation (e.g., 'sum', 'avg', etc.) Default: None (no aggregation)
aggregate_interval: None if no aggregation is desired, otherwise
this is the time interval over which a result will be aggregated.
Required if aggregate_type is non-None.
Default: None (no aggregation)
returns: a 3-way tuple of value tuples:
(start_vec, stop_vec, data_vec)
The first element holds a ValueTuple with the start times of the aggregation interval.
The second element holds a ValueTuple with the stop times of the aggregation interval.
The third element holds a ValueTuple with the data aggregation over the interval.
If sql_type is 'windvec' or 'windgustvec', the data vector will
be a vector of types complex. The real part is the x-component of the
wind, the imaginary part the y-component.
See the file weewx.units for the definition of a ValueTuple.
"""
windvec_types = {'windvec' : ('windSpeed, windDir'),
'windgustvec' : ('windGust, windGustDir')}
# Check to see if the requested type is not 'windvec' or 'windgustvec'
if obs_type not in windvec_types:
# The type is not one of the extended wind types. Use the regular
# version:
return self._getSqlVectors(timespan, obs_type,
aggregate_type, aggregate_interval)
# It is an extended wind type. Prepare the lists that will hold the
# final results.
start_vec = list()
stop_vec = list()
data_vec = list()
std_unit_system = None
_cursor=self.connection.cursor()
try:
# Is aggregation requested?
if aggregate_type:
# Check to make sure we have everything:
if not aggregate_interval:
raise weewx.ViolatedPrecondition("Aggregation interval missing")
# Aggregation is requested.
# The aggregation should happen over the x- and y-components.
# Because they do not appear in the database (only the
# magnitude and direction do) we cannot do the aggregation
# in the SQL statement. We'll have to do it in Python.
# Do we know how to do it?
if aggregate_type not in ['sum', 'count', 'avg', 'max', 'min']:
raise weewx.ViolatedPrecondition("Invalid aggregation type" % aggregate_type)
# This SQL select string will select the proper wind types
sql_str = 'SELECT dateTime, %s, usUnits FROM %s WHERE dateTime > ? AND dateTime <= ?' % \
(windvec_types[obs_type], self.table_name)
# Go through each aggregation interval, calculating the aggregation.
for stamp in weeutil.weeutil.intervalgen(timespan[0], timespan[1], aggregate_interval):
_mag_extreme = _dir_at_extreme = None
_xsum = _ysum = 0.0
_count = 0
_last_time = None
for _rec in _cursor.execute(sql_str, stamp):
(_mag, _dir) = _rec[1:3]
if _mag is None:
continue
# A good direction is necessary unless the mag is zero:
if _mag == 0.0 or _dir is not None:
_count += 1
_last_time = _rec[0]
if std_unit_system:
if std_unit_system != _rec[3]:
raise weewx.UnsupportedFeature("Unit type cannot change "\
"within a time interval.")
else:
std_unit_system = _rec[3]
# Pick the kind of aggregation:
if aggregate_type == 'min':
if _mag_extreme is None or _mag < _mag_extreme:
_mag_extreme = _mag
_dir_at_extreme = _dir
elif aggregate_type == 'max':
if _mag_extreme is None or _mag > _mag_extreme:
_mag_extreme = _mag
_dir_at_extreme = _dir
else:
# No need to do the arithmetic if mag is zero.
# We also need a good direction
if _mag > 0.0 and _dir is not None:
_xsum += _mag * math.cos(math.radians(90.0 - _dir))
_ysum += _mag * math.sin(math.radians(90.0 - _dir))
# We've gone through the whole interval. Were there any
# good data?
if _count:
# Record the time of the last good data point:
start_vec.append(stamp.start)
stop_vec.append(stamp.stop)
# Form the requested aggregation:
if aggregate_type in ('min', 'max'):
if _dir_at_extreme is None:
# The only way direction can be zero with a
# non-zero count is if all wind velocities
# were zero
if weewx.debug:
assert(_mag_extreme <= 1.0e-6)
x_extreme = y_extreme = 0.0
else:
x_extreme = _mag_extreme * math.cos(math.radians(90.0 - _dir_at_extreme))
y_extreme = _mag_extreme * math.sin(math.radians(90.0 - _dir_at_extreme))
data_vec.append(complex(x_extreme, y_extreme))
elif aggregate_type == 'sum':
data_vec.append(complex(_xsum, _ysum))
elif aggregate_type == 'count':
data_vec.append(_count)
else:
# Must be 'avg'
data_vec.append(complex(_xsum/_count, _ysum/_count))
else:
# No aggregation desired. It's a lot simpler. Go get the
# data in the requested time period
# This SQL select string will select the proper wind types
sql_str = 'SELECT dateTime, %s, usUnits, `interval` FROM %s WHERE dateTime >= ? AND dateTime <= ?' % \
(windvec_types[obs_type], self.table_name)
for _rec in _cursor.execute(sql_str, timespan):
start_vec.append(_rec[0] - _rec[4])
stop_vec.append(_rec[0])
if std_unit_system:
if std_unit_system != _rec[3]:
raise weewx.UnsupportedFeature("Unit type cannot change "\
"within a time interval.")
else:
std_unit_system = _rec[3]
# Break the mag and dir down into x- and y-components.
(_mag, _dir) = _rec[1:3]
if _mag is None or _dir is None:
data_vec.append(None)
else:
x = _mag * math.cos(math.radians(90.0 - _dir))
y = _mag * math.sin(math.radians(90.0 - _dir))
if weewx.debug:
# There seem to be some little rounding errors that
# are driving my debugging crazy. Zero them out
if abs(x) < 1.0e-6 : x = 0.0
if abs(y) < 1.0e-6 : y = 0.0
data_vec.append(complex(x,y))
finally:
_cursor.close()
(time_type, time_group) = weewx.units.getStandardUnitType(std_unit_system, 'dateTime')
(data_type, data_group) = weewx.units.getStandardUnitType(std_unit_system, obs_type, aggregate_type)
return (weewx.units.ValueTuple(start_vec, time_type, time_group),
weewx.units.ValueTuple(stop_vec, time_type, time_group),
weewx.units.ValueTuple(data_vec, data_type, data_group))
def _check_unit_system(self, unit_system):
""" Check to make sure a unit system is the same as what's already in use in the database."""
if self.std_unit_system is not None:
if unit_system != self.std_unit_system:
raise weewx.UnitError("Unit system of incoming record (0x%02x) "\
"differs from '%s' table in '%s' database (0x%02x)" %
(unit_system, self.table_name, self.database_name,
self.std_unit_system))
else:
# This is the first record. Remember the unit system to
# check against subsequent records:
self.std_unit_system = unit_system
def _getSqlVectors(self, timespan, sql_type,
aggregate_type=None,
aggregate_interval=None):
"""Get time and (possibly aggregated) data vectors within a time
interval.
timespan: The timespan over which the aggregation is to be done.
sql_type: The observation type to be retrieved. The type should be one
of the columns in the archive database.
aggregate_type: None if no aggregation is desired, otherwise the type
of aggregation (e.g., 'sum', 'avg', etc.) Default: None (no aggregation)
aggregate_interval: None if no aggregation is desired, otherwise
this is the time interval over which a result will be aggregated.
Required if aggregate_type is non-None.
Default: None (no aggregation)
returns: a 3-way tuple of value tuples:
(start_vec, stop_vec, data_vec)
The first element holds a ValueTuple with the start times of the aggregation interval.
The second element holds a ValueTuple with the stop times of the aggregation interval.
The third element holds a ValueTuple with the data aggregation over the interval.
If aggregation is desired (aggregate_interval is not None), then each
element represents a time interval exclusive on the left, inclusive on
the right. The time elements will all fall on the same local time
boundary as startstamp.
For example, if the starting time in the timespan is 8-Mar-2009 18:00
and aggregate_interval is 10800 (3 hours), then the returned time vector
will be (shown in local times):
8-Mar-2009 21:00
9-Mar-2009 00:00
9-Mar-2009 03:00
9-Mar-2009 06:00 etc.
Note that DST happens at 02:00 on 9-Mar, so the actual time deltas
between the elements is 3 hours between times #1 and #2, but only 2
hours between #2 and #3.
NB: there is an algorithmic assumption here that the archive time
interval is a constant.
There is another assumption that the unit type does not change within
a time interval.
See the file weewx.units for the definition of a ValueTuple.
"""
startstamp, stopstamp = timespan
start_vec = list()
stop_vec = list()
data_vec = list()
std_unit_system = None
_cursor=self.connection.cursor()
try:
if aggregate_type :
# Check to make sure we have everything:
if not aggregate_interval:
raise weewx.ViolatedPrecondition("Aggregation interval missing")
if aggregate_type.lower() == 'last':
sql_str = "SELECT %s, MIN(usUnits), MAX(usUnits) FROM %s WHERE dateTime = "\
"(SELECT MAX(dateTime) FROM %s WHERE "\
"dateTime > ? AND dateTime <= ? AND %s IS NOT NULL)" % (sql_type, self.table_name,
self.table_name, sql_type)
elif aggregate_type.lower() == 'accu':
sql_str = "SELECT sum(%s), MIN(usUnits), MAX(usUnits) FROM %s "\
"WHERE dateTime > ? AND dateTime <= ?" % (sql_type, self.table_name)
else:
sql_str = "SELECT %s(%s), MIN(usUnits), MAX(usUnits) FROM %s "\
"WHERE dateTime > ? AND dateTime <= ?" % (aggregate_type, sql_type, self.table_name)
accumulated = 0
for stamp in weeutil.weeutil.intervalgen(startstamp, stopstamp, aggregate_interval):
_cursor.execute(sql_str, stamp)
_rec = _cursor.fetchone()
# Don't accumulate any results where there wasn't a record
# (signified by a null result)
if _rec and _rec[0] is not None:
if std_unit_system:
if not (std_unit_system == _rec[1] == _rec[2]):
raise weewx.UnsupportedFeature("Unit type cannot change "\
"within a time interval (%s vs %s vs %s)." %
(std_unit_system, _rec[1], _rec[2]))
else:
std_unit_system = _rec[1]
start_vec.append(stamp.start)
stop_vec.append(stamp.stop)
if (aggregate_type.lower() == 'accu'):
accumulated = accumulated+_rec[0]
data_vec.append(accumulated)
else:
data_vec.append(_rec[0])
elif aggregate_type.lower() == 'accu': # unless it is accumulated
start_vec.append(stamp.start)
stop_vec.append(stamp.stop)
data_vec.append(accumulated)
else:
# No aggregation
sql_str = "SELECT dateTime, %s, usUnits, `interval` FROM %s "\
"WHERE dateTime >= ? AND dateTime <= ?" % (sql_type, self.table_name)
for _rec in _cursor.execute(sql_str, (startstamp, stopstamp)):
start_vec.append(_rec[0] - _rec[3])
stop_vec.append(_rec[0])
if std_unit_system:
if std_unit_system != _rec[2]:
raise weewx.UnsupportedFeature("Unit type cannot change "\
"within a time interval.")
else:
std_unit_system = _rec[2]
data_vec.append(_rec[1])
finally:
_cursor.close()
(time_type, time_group) = weewx.units.getStandardUnitType(std_unit_system, 'dateTime')
(data_type, data_group) = weewx.units.getStandardUnitType(std_unit_system, sql_type, aggregate_type)
return (ValueTuple(start_vec, time_type, time_group),
ValueTuple(stop_vec, time_type, time_group),
ValueTuple(data_vec, data_type, data_group))
def reconfig(old_db_dict, new_db_dict, new_unit_system=None, new_schema=None):
"""Copy over an old archive to a new one, using a provided schema."""
with Manager.open(old_db_dict) as old_archive:
if new_schema is None:
import schemas.wview
new_schema = schemas.wview.schema
with Manager.open_with_create(new_db_dict, schema=new_schema) as new_archive:
# Wrap the input generator in a unit converter.
record_generator = weewx.units.GenWithConvert(old_archive.genBatchRecords(), new_unit_system)
# This is very fast because it is done in a single transaction
# context:
new_archive.addRecord(record_generator)
#===============================================================================
# Class DBBinder
#===============================================================================
class DBBinder(object):
"""Given a binding name, it returns the matching database as a managed object. Caches
results."""
def __init__(self, config_dict):
""" Initialize a DBBinder object.
config_dict: The configuration dictionary. """
self.config_dict = config_dict
self.default_binding_dict = {}
self.manager_cache = {}
def close(self):
for data_binding in self.manager_cache.keys():
try:
self.manager_cache[data_binding].close()
del self.manager_cache[data_binding]
except Exception:
pass
def __enter__(self):
return self
def __exit__(self, etyp, einst, etb): # @UnusedVariable
self.close()
def set_binding_defaults(self, binding_name, default_binding_dict):
"""Set the defaults for the binding binding_name."""
self.default_binding_dict[binding_name] = default_binding_dict
def get_manager(self, data_binding='wx_binding', initialize=False):
"""Given a binding name, returns the managed object"""
global default_binding_dict
if data_binding not in self.manager_cache:
# If this binding has a set of defaults, use them. Otherwise, use the generic
# defaults
defaults = self.default_binding_dict.get(data_binding, default_binding_dict)
manager_dict = get_manager_dict_from_config(self.config_dict,
data_binding,
default_binding_dict=defaults)
self.manager_cache[data_binding] = open_manager(manager_dict, initialize)
return self.manager_cache[data_binding]
# For backwards compatibility with early V3.1 alphas:
get_database = get_manager
def bind_default(self, default_binding='wx_binding'):
"""Returns a function that holds a default database binding."""
def db_lookup(data_binding=None):
if data_binding is None:
data_binding = default_binding
return self.get_manager(data_binding)
return db_lookup
#===============================================================================
# Utilities
#===============================================================================
# If the [DataBindings] section is missing or incomplete, this is the set
# of defaults that will be used.
default_binding_dict = {'database' : 'archive_sqlite',
'table_name' : 'archive',
'manager' : 'weewx.wxmanager.WXDaySummaryManager',
'schema' : 'schemas.wview.schema'}
def get_database_dict_from_config(config_dict, database):
"""Return a database dictionary holding the information necessary
to open a database. Searches top-level stanzas for any missing
information about a database.
config_dict: The configuration dictionary.
database: The database whose database dict is to be
retrieved (example: 'archive_sqlite')
Returns: a database dictionary, with everything needed to pass on to
a Manager or weedb in order to open a database.
Example. Given a configuration file snippet that looks like:
>>> import configobj, StringIO
>>> config_snippet = '''
... WEEWX_ROOT = /home/weewx
... [DatabaseTypes]
... [[SQLite]]
... driver = weedb.sqlite
... SQLITE_ROOT = %(WEEWX_ROOT)s/archive
... [Databases]
... [[archive_sqlite]]
... database_name = weewx.sdb
... database_type = SQLite'''
>>> config_dict = configobj.ConfigObj(StringIO.StringIO(config_snippet))
>>> database_dict = get_database_dict_from_config(config_dict, 'archive_sqlite')
>>> keys = sorted(database_dict.keys())
>>> for k in keys:
... print "%15s: %12s" % (k, database_dict[k])
SQLITE_ROOT: /home/weewx/archive
database_name: weewx.sdb
driver: weedb.sqlite
"""
try:
database_dict = dict(config_dict['Databases'][database])
except KeyError, e:
raise weewx.UnknownDatabase("Unknown database '%s'" % e)
# See if a 'database_type' is specified. This is something
# like 'SQLite' or 'MySQL'. If it is, use it to augment any
# missing information in the database_dict:
if 'database_type' in database_dict:
database_type = database_dict.pop('database_type')
# Augment any missing information in the database dictionary with
# the top-level stanza
if database_type in config_dict['DatabaseTypes']:
weeutil.weeutil.conditional_merge(database_dict, config_dict['DatabaseTypes'][database_type])
else:
raise weewx.UnknownDatabaseType('database_type')
return database_dict
#
# A "manager dict" is everything needed to open up a manager. It is basically
# the same as a binding dictionary, except that the database has been replaced
# with a database dictionary.
#
# As such, it includes keys:
#
# manager: The manager class
# table_name: The name of the internal table
# schema: The schema to be used in case of initialization
# database_dict: The database dictionary. This will be passed
# on to weedb.
#
def get_manager_dict_from_config(config_dict, data_binding,
default_binding_dict=default_binding_dict):
# Start with a copy of the bindings in the config dictionary (we
# will be adding to it):
try:
manager_dict = dict(config_dict['DataBindings'][data_binding])
except KeyError, e:
raise weewx.UnknownBinding("Unknown data binding '%s'" % e)
# If anything is missing, substitute from the default dictionary:
weeutil.weeutil.conditional_merge(manager_dict, default_binding_dict)
# Now get the database dictionary if it's missing:
if 'database_dict' not in manager_dict:
try:
database = manager_dict.pop('database')
manager_dict['database_dict'] = get_database_dict_from_config(config_dict,
database)
except KeyError, e:
raise weewx.UnknownDatabase("Unknown database '%s'" % e)
# The schema may be specified as a string, in which case we resolve the
# python object to which it refers. Or it may be specified as a dict with
# field_name=sql_type pairs.
schema_name = manager_dict.get('schema')
if schema_name is None:
manager_dict['schema'] = None
elif isinstance(schema_name, dict):
# Schema is a ConfigObj section (that is, a dictionary). Retrieve the
# elements of the schema in order:
manager_dict['schema'] = [(col_name, manager_dict['schema'][col_name]) for col_name in manager_dict['schema']]
else:
# Schema is a string, with the name of the schema object
manager_dict['schema'] = weeutil.weeutil._get_object(schema_name)
return manager_dict
# The following is for backwards compatibility:
def get_manager_dict(bindings_dict, databases_dict, data_binding,
default_binding_dict=default_binding_dict):
if bindings_dict.parent != databases_dict.parent:
raise weewx.UnsupportedFeature("Database and binding dictionaries"
" require common parent")
return get_manager_dict_from_config(bindings_dict.parent, data_binding,
default_binding_dict)
def open_manager(manager_dict, initialize=False):
manager_cls = weeutil.weeutil._get_object(manager_dict['manager'])
if initialize:
return manager_cls.open_with_create(manager_dict['database_dict'],
manager_dict['table_name'],
manager_dict['schema'])
else:
return manager_cls.open(manager_dict['database_dict'],
manager_dict['table_name'])
def open_manager_with_config(config_dict, data_binding,
initialize=False, default_binding_dict=default_binding_dict):
"""Given a binding name, returns an open manager object."""
manager_dict = get_manager_dict_from_config(config_dict,
data_binding=data_binding,
default_binding_dict=default_binding_dict)
return open_manager(manager_dict, initialize)
def drop_database(manager_dict):
"""Drop (delete) a database, given a manager dict"""
weedb.drop(manager_dict['database_dict'])
def drop_database_with_config(config_dict, data_binding,
default_binding_dict=default_binding_dict):
"""Drop (delete) the database associated with a binding name"""
manager_dict = get_manager_dict_from_config(config_dict,
data_binding=data_binding,
default_binding_dict=default_binding_dict)
drop_database(manager_dict)
#===============================================================================
# Class DaySummaryManager
#
# Adds daily summaries to the database.
#
# This class specializes method _addSingleRecord so that it adds
# the data to a daily summary, as well as the regular archive table.
#
# Note that a date does not include midnight --- that belongs
# to the previous day. That is because a data record archives
# the *previous* interval. So, for the date 5-Oct-2008 with
# a five minute archive interval, the statistics would include
# the following records (local time):
# 5-Oct-2008 00:05:00
# 5-Oct-2008 00:10:00
# 5-Oct-2008 00:15:00
# .
# .
# .
# 5-Oct-2008 23:55:00
# 6-Oct-2008 00:00:00
#
#===============================================================================
def show_progress(nrec, last_time):
"""Utility function to show our progress while backfilling"""
print >>sys.stdout, "Records processed: %d; Last date: %s\r" % \
(nrec, weeutil.weeutil.timestamp_to_string(last_time)),
sys.stdout.flush()
class DaySummaryManager(Manager):
"""Manage a daily statistical summary.
The daily summary consists of a separate table for each type. The columns
of each table are things like min, max, the timestamps for min and max,
sum and sumtime. The values sum and sumtime are kept to make it easy to
calculate averages for different time periods.
For example, for type 'outTemp' (outside temperature), there is
a table of name 'archive_day_outTemp' with the following column names:
dateTime, min, mintime, max, maxtime, sum, count, wsum, sumtime
wsum is the "Weighted sum," that is, the sum weighted by the archive interval.
sumtime is the sum of the archive intervals.
In addition to all the tables for each type, there is one additional table called
'archive_day__metadata', which currently holds the time of the last update. """
version = "2.0"
# The SQL statements used in the daily summary parts of the database
sql_create_str = "CREATE TABLE %s_day_%s (dateTime INTEGER NOT NULL UNIQUE PRIMARY KEY, "\
"min REAL, mintime INTEGER, max REAL, maxtime INTEGER, sum REAL, count INTEGER, "\
"wsum REAL, sumtime INTEGER);"
meta_create_str = """CREATE TABLE %s_day__metadata (name CHAR(20) NOT NULL UNIQUE PRIMARY KEY, value TEXT);"""
meta_replace_str = """REPLACE INTO %s_day__metadata VALUES(?, ?)"""
meta_select_str = """SELECT value FROM %s_day__metadata WHERE name=?"""
# Set of SQL statements to be used for calculating aggregate statistics. Key is the aggregation type.
sqlDict = {'min' : "SELECT MIN(min) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'minmax' : "SELECT MIN(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'max' : "SELECT MAX(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'maxmin' : "SELECT MAX(min) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'meanmin' : "SELECT AVG(min) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'meanmax' : "SELECT AVG(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'maxsum' : "SELECT MAX(sum) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'mintime' : "SELECT mintime FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"min = (SELECT MIN(min) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime <%(stop)s)",
'maxmintime' : "SELECT mintime FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"min = (SELECT MAX(min) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime <%(stop)s)",
'maxtime' : "SELECT maxtime FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"max = (SELECT MAX(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime <%(stop)s)",
'minmaxtime' : "SELECT maxtime FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"max = (SELECT MIN(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime <%(stop)s)",
'maxsumtime' : "SELECT maxtime FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"sum = (SELECT MAX(sum) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime <%(stop)s)",
'gustdir' : "SELECT max_dir FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s AND " \
"max = (SELECT MAX(max) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s)",
'sum' : "SELECT SUM(sum) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'accu' : "SELECT SUM(sum) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'count' : "SELECT SUM(count) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'avg' : "SELECT SUM(wsum),SUM(sumtime) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'rms' : "SELECT SUM(wsquaresum),SUM(sumtime) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'vecavg' : "SELECT SUM(xsum),SUM(ysum),SUM(dirsumtime) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'vecdir' : "SELECT SUM(xsum),SUM(ysum) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'max_ge' : "SELECT SUM(max >= %(val)s) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'max_le' : "SELECT SUM(max <= %(val)s) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'min_ge' : "SELECT SUM(min >= %(val)s) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'min_le' : "SELECT SUM(min <= %(val)s) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s",
'sum_ge' : "SELECT SUM(sum >= %(val)s) FROM %(table_name)s_day_%(obs_key)s WHERE dateTime >= %(start)s AND dateTime < %(stop)s"}
def __init__(self, connection, table_name='archive', schema=None):
"""Initialize an instance of DaySummaryManager
connection: A weedb connection to the database to be managed.
table_name: The name of the table to be used in the database. Default
is 'archive'.
schema: The schema to be used. Optional. If not supplied, then an
exception of type weedb.OperationalError will be raised if the database
does not exist, and of type weedb.UnitializedDatabase if it exists, but
has not been initialized.
"""
# Initialize my superclass:
super(DaySummaryManager, self).__init__(connection, table_name, schema)
# If the database has not been initialized with the daily summaries, then create the
# necessary tables, but only if a schema has been given.
if '%s_day__metadata' % self.table_name not in self.connection.tables():
# Database has not been initialized with the summaries. Is there a schema?
if schema is None:
# Uninitialized, but no schema was supplied. Raise an exception
raise weedb.OperationalError("No day summary schema for table '%s' in database '%s'" % (self.table_name, connection.database_name))
# There is a schema. Create all the daily summary tables as one transaction:
with weedb.Transaction(self.connection) as _cursor:
self._initialize_day_tables(schema, _cursor)
syslog.syslog(syslog.LOG_NOTICE,
"manager: Created daily summary tables")
# Get a list of all the observation types which have daily summaries
all_tables = self.connection.tables()
prefix = "%s_day_" % self.table_name
Nprefix = len(prefix)
meta_name = '%s_day__metadata' % self.table_name
self.daykeys = [x[Nprefix:] for x in all_tables if (x.startswith(prefix) and x != meta_name)]
self.version = self._read_metadata('Version')
syslog.syslog(syslog.LOG_DEBUG,
'manager: Daily summary version is %s' % self.version)
def close(self):
del self.version
# There will be no daykeys if the daily summaries have been dropped.
try:
del self.daykeys
except AttributeError:
pass
super(DaySummaryManager, self).close()
def _initialize_day_tables(self, archiveSchema, cursor): # @UnusedVariable
"""Initialize the tables needed for the daily summary."""
# Create the tables needed for the daily summaries.
for _obs_type in self.obskeys:
cursor.execute(DaySummaryManager.sql_create_str % (self.table_name, _obs_type))
# Create the meta table:
cursor.execute(DaySummaryManager.meta_create_str % self.table_name)
# Put the version number in it:
self._write_metadata('Version', DaySummaryManager.version, cursor)
def _addSingleRecord(self, record, cursor, log_level):
"""Specialized version that updates the daily summaries, as well as the
main archive table."""
# First let my superclass handle adding the record to the main archive table:
super(DaySummaryManager, self)._addSingleRecord(record, cursor, log_level=log_level)
# Get the start of day for the record:
_sod_ts = weeutil.weeutil.startOfArchiveDay(record['dateTime'])
# Get the weight
_weight = self._calc_weight(record)
# Now add to the daily summary for the appropriate day:
_day_summary = self._get_day_summary(_sod_ts, cursor)
_day_summary.addRecord(record, weight=_weight)
self._set_day_summary(_day_summary, record['dateTime'], cursor)
syslog.syslog(log_level, "manager: Added record %s to daily summary in '%s'" %
(weeutil.weeutil.timestamp_to_string(record['dateTime']),
self.database_name))
def _updateHiLo(self, accumulator, cursor):
"""Use the contents of an accumulator to update the daily hi/lows."""
# Get the start-of-day for the timespan in the accumulator
_sod_ts = weeutil.weeutil.startOfArchiveDay(accumulator.timespan.stop)
# Retrieve the daily summaries seen so far:
_stats_dict = self._get_day_summary(_sod_ts, cursor)
# Update them with the contents of the accumulator:
_stats_dict.updateHiLo(accumulator)
# Then save the results:
self._set_day_summary(_stats_dict, accumulator.timespan.stop, cursor)
def getAggregate(self, timespan, obs_type, aggregate_type, **option_dict):
"""Returns an aggregation of a statistical type for a given time period.
It will use the daily summaries if possible, otherwise the archive table.
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
obs_type: The type over which aggregation is to be done (e.g., 'barometer',
'outTemp', 'rain', ...)
aggregate_type: The type of aggregation to be done.
option_dict: Some aggregations require optional values
returns: A value tuple. First element is the aggregation value,
or None if not enough data was available to calculate it, or if the aggregation
type is unknown. The second element is the unit type (eg, 'degree_F').
The third element is the unit group (eg, "group_temperature") """
if aggregate_type.lower() == 'accu':
aggregate_type = 'sum'
# We can use the day summary optimizations if the starting and ending times of
# the aggregation interval sit on midnight boundaries, or are the first or last
# records in the database.
if aggregate_type in ['last', 'lasttime'] or not (isMidnight(timespan.start) or \
timespan.start == self.first_timestamp) \
or not (isMidnight(timespan.stop) or \
timespan.stop == self.last_timestamp):
# Cannot use the day summaries. We'll have to calculate the aggregate
# using the regular archive table:
return Manager.getAggregate(self, timespan, obs_type, aggregate_type,
**option_dict)
# We can use the daily summaries. Proceed.
# This entry point won't work for heating or cooling degree days:
if weewx.debug:
assert(obs_type not in ['heatdeg', 'cooldeg'])
assert(timespan is not None)
# Check to see if this is a valid daily summary type:
if obs_type not in self.daykeys:
raise AttributeError, "Unknown daily summary type %s" % (obs_type,)
val = option_dict.get('val')
if val is None:
target_val = None
else:
# The following is for backwards compatibility when ValueTuples had
# just two members. This hack avoids breaking old skins.
if len(val) == 2:
if val[1] in ['degree_F', 'degree_C']:
val += ("group_temperature",)
elif val[1] in ['inch', 'mm', 'cm']:
val += ("group_rain",)
target_val = weewx.units.convertStd(val, self.std_unit_system)[0]
# convert to lower-case:
aggregate_type = aggregate_type.lower()
# Form the interpolation dictionary
interDict = {'start' : weeutil.weeutil.startOfDay(timespan.start),
'stop' : timespan.stop,
'obs_key' : obs_type,
'aggregate_type': aggregate_type,
'val' : target_val,
'table_name' : self.table_name}
# Run the query against the database:
_row = self.getSql(DaySummaryManager.sqlDict[aggregate_type] % interDict)
#=======================================================================
# Each aggregation type requires a slightly different calculation.
#=======================================================================
if not _row or None in _row:
# If no row was returned, or if it contains any nulls (meaning that not
# all required data was available to calculate the requested aggregate),
# then set the results to None.
_result = None
# Do the required calculation for this aggregat type
elif aggregate_type in ['min', 'maxmin', 'max', 'minmax', 'meanmin', 'meanmax',
'maxsum', 'sum', 'gustdir']:
# These aggregates are passed through 'as is'.
_result = _row[0]
elif aggregate_type in ['mintime', 'maxmintime', 'maxtime', 'minmaxtime', 'maxsumtime',
'count', 'max_ge', 'max_le', 'min_le', 'sum_ge']:
# These aggregates are always integers:
_result = int(_row[0])
elif aggregate_type == 'avg':
_result = _row[0]/_row[1] if _row[1] else None
elif aggregate_type == 'rms':
_result = math.sqrt(_row[0]/_row[1]) if _row[1] else None
elif aggregate_type == 'vecavg':
_result = math.sqrt((_row[0]**2 + _row[1]**2) / _row[2]**2) if _row[2] else None
elif aggregate_type == 'vecdir':
if _row == (0.0, 0.0):
_result = None
deg = 90.0 - math.degrees(math.atan2(_row[1], _row[0]))
_result = deg if deg >= 0 else deg + 360.0
else:
# Unknown aggregation. Return None
_result = None
# Look up the unit type and group of this combination of stats type and aggregation:
(t, g) = weewx.units.getStandardUnitType(self.std_unit_system, obs_type, aggregate_type)
# Form the value tuple and return it:
return weewx.units.ValueTuple(_result, t, g)
def exists(self, obs_type):
"""Checks whether the observation type exists in the database."""
# Check to see if this is a valid daily summary type:
return obs_type in self.daykeys
def has_data(self, obs_type, timespan):
"""Checks whether the observation type exists in the database and whether it has any data."""
return self.exists(obs_type) and self.getAggregate(timespan, obs_type, 'count')[0] != 0
def backfill_day_summary(self, start_d=None, stop_d=None,
progress_fn=show_progress, trans_days=5):
"""Fill the daily summaries from an archive database.
Normally, the daily summaries get filled by LOOP packets (to get maximum time
resolution), but if the database gets corrupted, or if a new user is
starting up with imported wview data, it's necessary to recreate it from
straight archive data. The Hi/Lows will all be there, but the times won't be
any more accurate than the archive period.
To help prevent database errors for large archives database transactions
are limited to trans_days days of archive data. This is a trade-off between
speed and memory usage.
start_d: The first day to be included, specified as a datetime.date object
[Optional. Default is to start with the first datum in the archive.]
stop_d: The last day to be included, specified as a datetime.date object
[Optional. Default is to include the date of the last archive record.]
progress_fn: This function will be called after processing every 1000 records.
trans_day: Number of days of archive data to be used for each daily
summaries database transaction. [Optional. Default is 5.]
returns: A 2-way tuple (nrecs, ndays) where
nrecs is the number of records backfilled;
ndays is the number of days
"""
# Table of actions.
#
# State start_ts stop_ts Action
# ----- -------- ------- ------
# lastUpdate==None any any No summary. Rebuild all
# lastUpdate <lastRecord any any Aborted rebuild. lastUpdate should
# be on day boundary. Restart from there.
# lastUpdate==lastRecord None None No action.
# "" X None Rebuild from X to end
# "" None Y Rebuild from beginning through Y, inclusively
# "" X Y Rebuild from X through Y, inclusively
#
# Definitions:
# lastUpdate: last update to the daily summary
# lastRecord: last update to the archive table
# X: A start time that falls on a day boundary
# Y: A stop time that falls on a day boundary
#
syslog.syslog(syslog.LOG_INFO, "manager: Starting backfill of daily summaries")
firstRecord= self.firstGoodStamp()
if firstRecord is None:
# Nothing in the archive database, so there's nothing to do.
return (0, 0)
t1 = time.time()
lastUpdate = to_int(self._read_metadata('lastUpdate'))
lastRecord = self.last_timestamp
if lastUpdate is None or lastUpdate < lastRecord:
# We are either building the daily summary from scratch, or restarting from
# an aborted build. Must finish the rebuild first.
if start_d or stop_d:
raise weewx.ViolatedPrecondition("Daily summaries not complete. Try again without from/to dates.")
start_ts = lastUpdate or firstRecord
start_d = datetime.date.fromtimestamp(start_ts)
stop_d = datetime.date.fromtimestamp(lastRecord)
elif lastUpdate == lastRecord:
# This is the normal state of affairs. If a value for start_d or stop_d
# has been passed in, a rebuild has been requested.
if start_d == stop_d == None:
# Nothing to do
return (0, 0)
if start_d is None:
start_d = datetime.date.fromtimestamp(firstRecord)
if stop_d is None:
stop_d = datetime.date.fromtimestamp(lastRecord)
else:
raise weewx.ViolatedPrecondition("lastUpdate(%s) > lastRecord(%s)" %
(timestamp_to_string(lastUpdate),
timestamp_to_string(lastRecord)))
nrecs = 0
ndays = 0
while start_d <= stop_d:
# Calculate the last date included in this transaction
stop_transaction = min(stop_d, start_d + datetime.timedelta(days=(trans_days-1)))
day_accum = None
with weedb.Transaction(self.connection) as cursor:
# Go through all the archive records in the time span, adding them to the
# daily summaries
start_batch = time.mktime(start_d.timetuple())
stop_batch = time.mktime((stop_transaction + datetime.timedelta(days=1)).timetuple())
for rec in self.genBatchRecords(start_batch, stop_batch):
# If this is the very first record, fetch a new accumulator
if not day_accum:
# Get a TimeSpan that include's the record's timestamp:
timespan = weeutil.weeutil.archiveDaySpan(rec['dateTime'])
# Get an empty day accumulator:
day_accum = weewx.accum.Accum(timespan)
weight = self._calc_weight(rec)
# Try updating. If the time is out of the accumulator's time span, an
# exception will get raised.
try:
day_accum.addRecord(rec, weight=weight)
except weewx.accum.OutOfSpan:
# The record is out of the time span.
# Save the old accumulator:
self._set_day_summary(day_accum, None, cursor)
ndays += 1
# Get a new accumulator:
timespan = weeutil.weeutil.archiveDaySpan(rec['dateTime'])
day_accum = weewx.accum.Accum(timespan)
# try again
day_accum.addRecord(rec, weight=weight)
lastUpdate = max(lastUpdate, rec['dateTime']) if lastUpdate else rec['dateTime']
nrecs += 1
if progress_fn and nrecs % 1000 == 0:
progress_fn(nrecs, rec['dateTime'])
# We're done with this transaction. Record the daily summary for the last day unless it is empty
if day_accum and not day_accum.isEmpty:
self._set_day_summary(day_accum, None, cursor)
ndays += 1
# Patch lastUpdate:
if lastUpdate:
self._write_metadata('lastUpdate', str(int(lastUpdate)), cursor)
# Advance
start_d += datetime.timedelta(days=trans_days)
tdiff = time.time() - t1
if nrecs:
syslog.syslog(syslog.LOG_INFO,
"manager: Processed %d records to backfill %d day summaries in %.2f seconds" % (nrecs, ndays, tdiff))
else:
syslog.syslog(syslog.LOG_INFO,
"manager: Daily summaries up to date")
return (nrecs, ndays)
#--------------------------- UTILITY FUNCTIONS -----------------------------------
def _get_day_summary(self, sod_ts, cursor=None):
"""Return an instance of an appropriate accumulator, initialized to a given day's statistics.
sod_ts: The timestamp of the start-of-day of the desired day."""
# Get the TimeSpan for the day starting with sod_ts:
_timespan = weeutil.weeutil.archiveDaySpan(sod_ts,0)
# Get an empty day accumulator:
_day_accum = weewx.accum.Accum(_timespan)
_cursor = cursor or self.connection.cursor()
try:
# For each observation type, execute the SQL query and hand the results on
# to the accumulator.
for _day_key in self.daykeys:
_cursor.execute("SELECT * FROM %s_day_%s WHERE dateTime = ?" % (self.table_name, _day_key), (_day_accum.timespan.start,))
_row = _cursor.fetchone()
# If the date does not exist in the database yet then _row will be None.
_stats_tuple = _row[1:] if _row is not None else None
_day_accum.set_stats(_day_key, _stats_tuple)
return _day_accum
finally:
if not cursor:
_cursor.close()
def _set_day_summary(self, day_accum, lastUpdate, cursor):
"""Write all statistics for a day to the database in a single transaction.
day_accum: an accumulator with the daily summary. See weewx.accum
lastUpdate: the time of the last update will be set to this unless it is None.
Normally, this is the timestamp of the last archive record added to the instance
day_accum. """
# Make sure the new data uses the same unit system as the database.
self._check_unit_system(day_accum.unit_system)
_sod = day_accum.timespan.start
# For each daily summary type...
for _summary_type in day_accum:
# Don't try an update for types not in the database:
if _summary_type not in self.daykeys:
continue
# ... get the stats tuple to be written to the database...
_write_tuple = (_sod,) + day_accum[_summary_type].getStatsTuple()
# ... and an appropriate SQL command with the correct number of question marks ...
_qmarks = ','.join(len(_write_tuple)*'?')
_sql_replace_str = "REPLACE INTO %s_day_%s VALUES(%s)" % (self.table_name, _summary_type, _qmarks)
# ... and write to the database. In case the type doesn't appear in the database,
# be prepared to catch an exception:
try:
cursor.execute(_sql_replace_str, _write_tuple)
except weedb.OperationalError, e:
syslog.syslog(syslog.LOG_ERR, "manager: "
"Replace failed for database %s: %s"
% (self.database_name, e))
# If requested, update the time of the last daily summary update:
if lastUpdate is not None:
self._write_metadata('lastUpdate', str(int(lastUpdate)), cursor)
def _calc_weight(self, record):
weight = 60.0 * record['interval'] if self.version >= '2.0' else 1.0
return weight
def _read_metadata(self, key, cursor=None):
"""Obtain a value from the daily summary metadata table.
Returns:
Value of the metadata field. Returns None if no value was found.
"""
_row = self.getSql(DaySummaryManager.meta_select_str % self.table_name, (key,), cursor)
return _row[0] if _row else None
def _write_metadata(self, key, value, cursor=None):
"""Write a value to the daily summary metadata table.
Input parameters:
key: The name of the metadata field to be written to.
value: The value to be written to the metadata field.
"""
_cursor = cursor or self.connection.cursor()
try:
_cursor.execute(DaySummaryManager.meta_replace_str % self.table_name,
(key, value))
finally:
if cursor is None:
_cursor.close()
def drop_daily(self):
"""Drop the daily summaries."""
syslog.syslog(syslog.LOG_INFO,
"manager: Dropping daily summary tables from '%s' ..." % self.connection.database_name)
try:
_all_tables = self.connection.tables()
with weedb.Transaction(self.connection) as _cursor:
for _table_name in _all_tables:
if _table_name.startswith('%s_day_' % self.table_name):
_cursor.execute("DROP TABLE %s" % _table_name)
del self.daykeys
except weedb.OperationalError, e:
syslog.syslog(syslog.LOG_ERR, "manager: "
"Drop summaries failed for database '%s': %s"
% (self.connection.database_name, e))
else:
syslog.syslog(syslog.LOG_INFO, "manager: "
"Dropped daily summary tables from database '%s'"
% (self.connection.database_name,))
if __name__ == '__main__':
import configobj
config_dict = configobj.ConfigObj('/home/weewx/weewx.conf')
mgr = open_manager_with_config(config_dict, 'wx_binding', initialize=True)
start_d = datetime.date(2016,10,1)
stop_d = datetime.date(2016,10,8)
t1 = time.time()
# nrecs, ndays = mgr.backfill_day_summary(start_d, stop_d)
nrecs, ndays = mgr.backfill_day_summary(None, None)
t2 = time.time()
print nrecs, ndays, t2-t1
import doctest
if not doctest.testmod().failed:
print("PASSED")
