Andrew,
My bad, wee_import was being told to write to a US database irrespective of
the underlying database units, the QC department is being fired as I write
this. The attached weeimport.py should fix the issue, usual deal:
- move the original weewx/bin/weeimport/weeimport.py aside by renaming
it to something like weeimport_orig.py
- copy the attached weeimport.py in its place
- run wee_import
- let us know the outcome
Gary
On Saturday, 8 October 2016 13:16:30 UTC+10, Andrew Milner wrote:
>
> ..... not quite perfect ......
> Just upgraded, and thought I would correct some errors from a previous
> import by using wee_import from WU with full qc checking - as available in
> the now standard wee_import.
>
> Created a wuimport.conf, and modified the qc section of weewx.conf
>
> The --dry-run proceeded to run looking OK, but when I then went to do the
> real import I got:
>
> unit system of incoming record (0x01) differs from 'archive' table in
> 'archive' database (0x10)
> **** nothing done, exiting
>
> I AM using a metric database, but my WU data is also in metric - so
> where/how do I tell wee_import the format of the incoming record?
>
> PS I had previously used wee_import without problems, but before the
> creation of the now mandatory wee_import config file and the latest qc mods.
>
>
> On Saturday, 8 October 2016 04:01:02 UTC+3, vince wrote:
>>
>> On Friday, October 7, 2016 at 5:12:02 PM UTC-7, Tom Keffer wrote:
>>>
>>> With this release we have rearranged the User's Guide, and broken out
>>> the hardware-specific information into its own Hardware Guide
>>> <http://www.weewx.com/docs/hardware.htm>.
>>>
>>>
>>>
>> upgraded (debian setup.py method) from 3.5.0 - perfect as always.
>>
>> The documentation reorganization especially the Hardware Guide is
>> 'fabulous'.
>>
>
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#
# Copyright (c) 2009-2016 Tom Keffer <tkef...@gmail.com> and
# Gary Roderick
#
# See the file LICENSE.txt for your full rights.
#
from __future__ import with_statement
"""Module providing the base classes and API for importing observational data
into weewx.
"""
# Python imports
import datetime
import os.path
import re
import sys
import syslog
import time
from datetime import datetime as dt
# weewx imports
import weecfg
import weewx
import weewx.qc
import weewx.wxservices
from weewx.manager import open_manager_with_config
from weewx.units import unit_constants, unit_nicknames, convertStd, to_std_system, ValueTuple
from weeutil.weeutil import timestamp_to_string, option_as_list, to_int, tobool, _get_object
# List of sources we support
SUPPORTED_SOURCES = ['CSV', 'WU', 'Cumulus']
# Minimum requirements in any explicit or implicit weewx field-to-import field
# map
MINIMUM_MAP = {'dateTime': {'units': 'unix_epoch'},
'usUnits': {'units': None},
'interval': {'units': 'minute'}}
# ============================================================================
# Error Classes
# ============================================================================
class WeeImportMapError(Exception):
"""Base class of exceptions thrown when encountering an error with an
external source-to-weewx field map.
"""
class WeeImportIOError(Exception):
"""Base class of exceptions thrown when encountering an I/O error with an
external source.
"""
class WeeImportFieldError(Exception):
"""Base class of exceptions thrown when encountering an error with a field
from an external source.
"""
# ============================================================================
# class Source
# ============================================================================
class Source(object):
""" Abstract base class used for interacting with an external data source
to import records into the weewx archive.
__init__() must define the following properties:
self.dry_run - Is this a dry run (ie do not save imported records
to archive). [True|False].
self.calc_missing - Calculate any missing derived observations.
[True|False].
self.tranche - Number of records to be written to archive in a
single transaction. Integer.
self.interval - Method of determining interval value if interval
field not included in data source.
['config'|'derive'|x] where x is an integer.
Child classes are used to interract with a specific source (eg CSV file,
WU). Any such child classes must define a getRawData() method which:
- gets the raw observation data and returns an iterable yielding data
dicts whose fields can be mapped to a weewx archive field
- defines an import data field-to-weewx archive field map (self.map)
self.raw_datetime_format - Format of date time data field from which
observation timestamp is to be derived. A
string in Python datetime string format such
as '%Y-%m-%d %H:%M:%S'. If the date time
data field cannot be interpreted as a string
wee_import attempts to interpret the field
as a unix timestamp. If the field is not a
valid unix timestamp an error is raised.
"""
# reg expression to match any HTML tag of the form <...>
_tags = re.compile(r'\<.*\>')
def __init__(self, config_dict, import_config_dict, options, log):
"""A generic initialisation.
Set some realistic default values for options read from the import
config file. Obtain objects to handle missing derived obs (if required)
and QC on imported data. Parse any --date command line option so we
know what records to import.
"""
# give our source object some logging abilities
self.wlog = log
# save our weewx config dict
self.config_dict = config_dict
# get our import config dict settings
# interval, default to 'derive'
self.interval = import_config_dict.get('interval', 'derive')
# tranche, default to 250
self.tranche = to_int(import_config_dict.get('tranche', 250))
# apply QC, default to True
self.apply_qc = tobool(import_config_dict.get('qc', True))
# calc-missing, default to True
self.calc_missing = tobool(import_config_dict.get('calc_missing', True))
# Some sources include UV index and solar radiation values even if no
# sensor was present. The weewx convention is to store the None value
# when a sensor or observation does not exist. Record whether UV and/or
# solar radiation sensor was present.
# UV, default to True
self.UV_sensor = tobool(import_config_dict.get('UV', True))
# solar, default to True
self.solar_sensor = tobool(import_config_dict.get('radiation', True))
# get some weewx database info
self.db_binding_wx = get_binding(config_dict)
self.dbm = open_manager_with_config(config_dict, self.db_binding_wx,
initialize=True,
default_binding_dict={'table_name': 'archive',
'manager': 'weewx.wxmanager.WXDaySummaryManager',
'schema': 'schemas.wview.schema'})
# get the unit system used in our db
if self.dbm.std_unit_system is None:
# we have a fresh archive (ie no records) so cannot deduce
# the unit system in use, so go to our config_dict
self.archive_unit_sys = unit_constants[self.config_dict['StdConvert'].get('target_unit','US')]
else:
# get our unit system from the archive db
self.archive_unit_sys = self.dbm.std_unit_system
# do we need a WXCalculate object, if so get one
if self.calc_missing:
# parameters required to obtain a WXCalculate object
stn_dict = config_dict['Station']
altitude_t = option_as_list(stn_dict.get('altitude', (None, None)))
try:
altitude_vt = weewx.units.ValueTuple(float(altitude_t[0]),
altitude_t[1],
"group_altitude")
except KeyError, e:
raise weewx.ViolatedPrecondition(
"Value 'altitude' needs a unit (%s)" % e)
latitude_f = float(stn_dict['latitude'])
longitude_f = float(stn_dict['longitude'])
# get a WXCalculate object
self.wxcalculate = weewx.wxservices.WXCalculate(config_dict,
altitude_vt,
latitude_f,
longitude_f)
else:
self.wxcalculate = None
# get ourselves a QC object to do QC on imported records
self.import_QC = weewx.qc.QC(config_dict, parent='weeimport')
# Process our command line options
self.dry_run = options.dry_run
self.verbose = options.verbose
# If a --date command line option was used then we need to determine
# the time span over which we will import any records. We will import
# records that have dateTime > self.first_ts and <=self.last_ts.
if options.date:
# do we have a date range or a single date only - look for the '-'
dates = options.date.split('-', 1)
if len(dates) > 1:
# we have a range
# first try to get a date and time for each
try:
_first = dt.strptime(dates[0], "%Y/%m/%d %H:%M")
_first_tt = _first.timetuple()
_last = dt.strptime(dates[1], "%Y/%m/%d %H:%M")
_last_tt = _last.timetuple()
self.first_ts = time.mktime(_first_tt)
self.last_ts = time.mktime(_last_tt)
except ValueError:
# that did not work so try to get a date for each
try:
_first = dt.strptime(dates[0], "%Y/%m/%d")
_first_tt = _first.timetuple()
_last = (dt.strptime(dates[1], "%Y/%m/%d") +
datetime.timedelta(days=1))
_last_tt = _last.timetuple()
self.first_ts = time.mktime(_first_tt)
self.last_ts = time.mktime(_last_tt)
except:
raise ValueError(
"Cannot parse --date argument '%s'." % options.date)
else:
# we have a date
_first_dt = dt.strptime(dates[0], "%Y/%m/%d")
_first_tt = _first_dt.timetuple()
_last_dt = _first_dt + datetime.timedelta(days=1)
_last_tt = _last_dt.timetuple()
self.first_ts = time.mktime(_first_tt)
self.last_ts = time.mktime(_last_tt)
else:
# no date on the command line so set our first/last ts to None
self.first_ts = None
self.last_ts = None
# initialise a few properties we will need during the import
# answer flags
self.ans = None
self.interval_ans = None
# properties to help with processing multi-period imports
self.first_period = True
self.last_period = False
self.period_no = 1
# total records processed
self.total_rec_proc = 0
# total unique records identified
self.total_unique_rec = 0
# time we started to first save
self.t1 = None
@staticmethod
def sourceFactory(options, args, log):
"""Factory to produce a Source object.
Returns an appropriate object depending on the source type. Raises a
weewx.UnsupportedFeature error if an object could not be created.
"""
# get some key weewx parameters
# first the config dict to use
config_path, config_dict = weecfg.read_config(None,
args,
file_name=options.config_path)
# get wee_import config dict if it exists
import_config_path, import_config_dict = weecfg.read_config(None,
args,
file_name=options.import_config_path)
# we should have a source parameter at the root of out import config
# file, try to get it but be prepared to catch the error.
try:
source = import_config_dict['source']
except KeyError:
# we have no source parameter so check if we have a single source
# config stanza, if we do then proceed using that
_source_keys = [s for s in SUPPORTED_SOURCES if s in import_config_dict.keys()]
if len(_source_keys) == 1:
# we have a single source config stanza so use that
source = _source_keys[0]
else:
# there is no source parameter and we do not have a single
# source config stanza so raise an error
_msg = "Invalid 'source' parameter or no 'source' parameter specified in %s" % import_config_path
raise weewx.UnsupportedFeature(_msg)
# if we made it this far we have all we need to create an object
module_class = '.'.join(['weeimport',
source.lower() + 'import',
source + 'Source'])
return _get_object(module_class)(config_dict,
config_path,
import_config_dict.get(source, {}),
import_config_path,
options,
log)
def run(self):
"""Main entry point for importing from an external source.
Source data may be provided as a group of records over a single period
(eg a single CSV file) or as a number of groups of records covering
multiple periods(eg a WU multi-day import). Step through each group of
records, getting the raw data, mapping the data and saving the data for
each period.
"""
# setup a counter to count the periods of records
self.period_no = 1
with self.dbm as archive:
# step through our periods of records until we reach the end. A
# 'period' of records may comprise the contents of a file, a day
# of WU obs or a month of Cumulus obs
for period in self.period_generator():
# get the raw data
_msg = 'Obtaining raw import data for period %d...' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
_raw_data = self.getRawData(period)
_msg = 'Raw import data read successfully for period %d.' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
# map the raw data to a weewx archive compatible dictionary
_msg = 'Mapping raw import data for period %d...' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
_mapped_data = self.mapRawData(_raw_data, self.archive_unit_sys)
_msg = 'Raw import data mapped successfully for period %d.' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
# save the mapped data to archive
_msg = 'Saving mapped data to archive for period %d...' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
self.saveToArchive(archive, _mapped_data)
_msg = 'Mapped data saved to archive successfully for period %d.' % self.period_no
self.wlog.verboselog(syslog.LOG_INFO, _msg)
# increment our period counter
self.period_no += 1
# Provide some summary info now that we have finished the import.
# What we say depends on whether it was a dry run or not and
# whether we imported and records or not.
if self.total_rec_proc == 0:
# nothing imported so say so
_msg = 'No records were identified for import. Exiting. Nothing done.'
self.wlog.printlog(syslog.LOG_INFO, _msg)
else:
# we imported something
if self.dry_run:
# but it was a dry run
_msg = "Finished dry run import. %d records were processed and %d unique records would have been imported." % (self.total_rec_proc,
self.total_unique_rec)
self.wlog.printlog(syslog.LOG_INFO, _msg)
else:
# something should have been saved to database
_msg = "Finished import. %d raw records resulted in %d unique records being processed in %.2f seconds." % (self.total_rec_proc,
self.total_unique_rec,
self.tdiff)
self.wlog.printlog(syslog.LOG_INFO, _msg)
print "Those records with a timestamp already in the archive will not have been imported."
print "Confirm successful import in the weewx log file."
def parseMap(self, source_type, source, import_config_dict):
"""Produce a source field-to-weewx archive field map.
Data from an external source can be mapped to the weewx archive using:
- a fixed field map (WU),
- a fixed field map with user specified source units (Cumulus), or
- a user defined field/units map.
All user defined mapping is specified in the import config file.
To generate the field map first look to see if we have a fixed map, if
we do validate it and return the resulting map. Otherwise look for user
specified mapping in the import config file, construct the field map
and return it. If there is neither a fixed map or user specified
mapping then raise an error.
Input parameters:
source_type: String holding name of the section in
import_config_dict the holds config details for the
source being used.
source: Iterable holding the source data. Used if import field
names are included in the source data (eg CSV).
import_config_dict: config dict from import config file.
Returns a map as a dictionary of elements with each element structured
as follows:
'archive_field_name': {'field_name': 'source_field_name',
'units': 'unit_name'}
where:
- archive_field_name is an observation name in the weewx
database schema
- source_field_name is the name of a field from the external
source
- unit_name is the weewx unit name of the units used by
source_field_name
"""
# start with the minimum map
_map = dict(MINIMUM_MAP)
# Do the easy one first, do we have a fixed mapping, if so validate it
if self._header_map:
# We have a static map that maps header fields to weewx (eg WU).
# Our static map may have entries for fields that don't exist in our
# source data so step through each field name in our source data and
# only add those that exist to our resulting map.
for _key in source.fieldnames:
# if we know about the field name add it to our map
if _key in self._header_map:
_map[self._header_map[_key]['map_to']] = {'field_name': _key,
'units': self._header_map[_key]['units']}
# Do we have a user specified map, if so construct our field map
elif 'FieldMap' in import_config_dict:
# we have a user specified map so construct our map dict
for _key, _entry in import_config_dict['FieldMap'].iteritems():
# expect 2 parameters for each option: source field, units
if len(_entry) == 2:
# we have 2 parameter so that's field and units
_map[_key] = {'field_name': _entry[0],
'units': _entry[1]}
# if the entry is not empty then it might be valid ie just a
# field name (eg if usUnits is specified)
elif _entry != [''] and len(_entry) == 1:
# we have 1 parameter so it must be just name
_map[_key] = {'field_name': _entry[0]}
else:
# otherwise its invalid so ignore it
pass
# now do some crude error checking
# dateTime. We must have a dateTime mapping. Check for a 'field_name'
# field under 'dateTime' and be prepared to catch the error if it
# does not exist.
try:
if _map['dateTime']['field_name']:
# we have a 'field_name' entry so continue
pass
else:
# something is wrong, we have a 'field_name' entry but it
# is not valid so raise an error
raise WeeImportMapError(
"Invalid mapping specified in '%s' for field 'dateTime'." % self.import_config_path)
except KeyError:
raise WeeImportMapError(
"No mapping specified in '%s' for field 'dateTime'." % self.import_config_path)
# usUnits. We don't have to have a mapping for usUnits but if we
# don't then we must have 'units' specified for each field mapping.
if 'usUnits' not in _map:
# no unit system mapping do we have units specified for
# each individual field
for _key,_val in _map.iteritems():
# we don't need to check dateTime and usUnits
if _key not in ['dateTime', 'usUnits']:
if 'units' in _val:
# we have a units field, do we know about it
if _val['units'] not in weewx.units.default_unit_format_dict:
# we have an invalid unit string so tell the
# user and exit
raise weewx.UnitError(
"Unknown units '%s' specified for field '%s' in %s." % (_map[_field]['units'],
_field,
self.import_config_path))
else:
# we don't have a units field, that's not allowed
# so raise an error
raise WeeImportMapError(
"No units specified for source field '%s' in %s." % (_key,
self.import_config_path))
# if we got this far we have a usable map, advise the user what we
# will use
_msg = "The following imported field-to-weewx field map will be used:"
if self.verbose:
self.wlog.verboselog(syslog.LOG_INFO, _msg)
else:
self.wlog.logonly(syslog.LOG_INFO, _msg)
for _key, _val in _map.iteritems():
if 'field_name' in _val:
_units_msg = ""
if 'units' in _val:
_units_msg = " in units '%s'" % _val['units']
_msg = " source field '%s'%s --> weewx field '%s'" % (_val['field_name'],
_units_msg,
_key)
if self.verbose:
self.wlog.verboselog(syslog.LOG_INFO, _msg)
else:
self.wlog.logonly(syslog.LOG_INFO, _msg)
else:
# no [[FieldMap]] stanza and no _header_map so raise an error as we
# don't know what to map
_msg = "No '%s' field map found in %s." % (source_type,
self.import_config_path)
raise WeeImportMapError(_msg)
return _map
def mapRawData(self, data, unit_sys=weewx.US):
"""Maps raw data to weewx archive record compatible dictionaries.
Takes an iterable source of raw data observations, maps the fields of
each row to a list of weewx compatible archive records and performs any
necessary unit conversion.
Input parameters:
data: iterable that yields the data records to be processed.
unit_sys: weewx unit system in which the generated records will be
provided. Omission will result in US customary (weewx.US)
being used.
Returns a list of dicts of weewx compatible archive records.
"""
# initialise our list of mapped records
_records = []
# initialise some rain variables
_last_ts = None
_last_rain = None
# list of fields we have given the user a warning over, prevents us
# giving multiple warnings for the same field.
_warned = []
# step through each row in our data
for _row in data:
_rec = {}
# first off process the fields that require special processing
# dateTime
if 'field_name' in self.map['dateTime']:
# we have a map for dateTime
try:
_raw_dateTime = _row[self.map['dateTime']['field_name']]
except:
raise WeeImportFieldError(
"Field '%s' not found in source data." % self.map['dateTime']['field_name'])
# now process the raw date time data
if _raw_dateTime.isdigit():
# Our dateTime is a number, is it a timestamp already?
# Try to use it and catch the error if there is one and
# raise it higher.
try:
_rec_dateTime = int(_raw_dateTime)
except:
raise ValueError(
"Invalid '%s' field. Cannot convert '%s' to timestamp." % (self.map['dateTime']['field_name'],
_raw_dateTime))
else:
# it's a string so try to parse it and catch the error if
# there is one and raise it higher
try:
_datetm = time.strptime(_raw_dateTime,
self.raw_datetime_format)
_rec_dateTime = int(time.mktime(_datetm))
except:
raise ValueError(
"Invalid '%s' field. Cannot convert '%s' to timestamp." % (self.map['dateTime']['field_name'],
_raw_dateTime))
# if we have a timeframe of concern does our record fall within
# it
if (self.first_ts is None and self.last_ts is None) or self.first_ts <= _rec_dateTime <= self.last_ts:
# we have no timeframe or if we do it falls within it so
# save the dateTime
_rec['dateTime'] = _rec_dateTime
else:
# it is not so skip to the next record
continue
else:
# there is no mapped field for dateTime so raise an error
raise ValueError("No mapping for weewx field 'dateTime'.")
# usUnits
_units = None
if 'field_name' in self.map['usUnits']:
# we have a field map for a unit system
try:
# The mapped field is in _row so try to get the raw data.
# If its not there then raise an error.
_raw_units = int(_row[self.map['usUnits']['field_name']])
except:
raise WeeImportFieldError(
"Field '%s' not found in source data." % self.map['usUnits']['field_name'])
# we have a value but is it valid
if _raw_units in unit_nicknames:
# it is valid so use it
_units = _raw_units
else:
# the units value is not valid so raise an error
_msg = "Invalid unit system '%s'(0x%02x) mapped from data source. Check data source or field mapping." % (_raw_units,
_raw_units)
raise weewx.UnitError(_msg)
# interval
if 'field_name' in self.map['interval']:
# We have a map for interval so try to get the raw data. If
# its not there then raise an error.
try:
_tfield = _row[self.map['interval']['field_name']]
except:
raise WeeImportFieldError(
"Field '%s' not found in source data." % self.map['interval']['field_name'])
# now process the raw interval data
if _tfield is not None and _tfield != '':
try:
interval = int(_tfield)
except:
raise ValueError(
"Invalid '%s' field. Cannot convert '%s' to an integer." % (self.map['interval']['field_name'],
_tfield))
else:
# if it happens to be None then raise an error
raise ValueError(
"Invalid value '%s' for mapped field '%s' at timestamp '%s'." % (_tfield,
self.map['interval']['field_name'],
timestamp_to_string(_rec['dateTime'])))
else:
# we have no mapping so try to calculate it
interval = self.getInterval(_last_ts, _rec['dateTime'])
_rec['interval'] = interval
# now step through the rest of the fields in our map and process
# the fields that don't require special processing
for _field in self.map:
# skip those that have had special processing
if _field in MINIMUM_MAP:
continue
# process everything else
else:
# is our mapped field in the record
if self.map[_field]['field_name'] in _row:
# Yes it is. Try to get a value for the obs but if we
# can't catch the error
try:
_temp = float(_row[self.map[_field]['field_name']].strip())
except:
# perhaps we have a blank/empty entry
if _row[self.map[_field]['field_name']].strip() == '':
# if so we will use None
_temp = None
else:
# otherwise we will raise an error
_msg = "%s: cannot convert '%s' to float at timestamp '%s'." % (_field,
_row[self.map[_field]['field_name']],
timestamp_to_string(_rec['dateTime']))
raise ValueError(_msg)
# some fields need some special processing
# rain - if our imported 'rain' field is cumulative
# (self.rain == 'cumulative') then we need to calculate
# the discrete rainfall for this archive period
if _field == "rain" and self.rain == "cumulative":
_rain = self.getRain(_last_rain, _temp)
_last_rain = _temp
_temp = _rain
# wind - check any wind direction fields are within our
# bounds and convert to 0 to 360 range
if _field == "windDir" or _field == "windGustDir":
if self.wind_dir[0] <= _temp <= self.wind_dir[1]:
# normalise to 0 to 360
_temp %= 360
else:
# outside our bounds so set to None
_temp = None
# UV - if there was no UV sensor used to create the
# imported data then we need to set the imported value
# to None
if _field == 'UV' and not self.UV_sensor:
_temp = None
# solar radiation - if there was no solar radiation
# sensor used to create the imported data then we need
# to set the imported value to None
if _field == 'radiation' and not self.solar_sensor:
_temp = None
# if no mapped field for a unit system we have to do
# field by field unit conversions
if _units is None:
_temp_vt = ValueTuple(_temp,
self.map[_field]['units'],
weewx.units.obs_group_dict[_field])
_conv_vt = convertStd(_temp_vt, unit_sys)
_rec[_field] = _conv_vt.value
else:
# we do have a mapped field for a unit system so
# save the field in our record and continue, any
# unit conversion will be done in bulk later
_rec[_field] = _temp
else:
# No it's not. Set the field in our output to None
_rec[_field] = None
# now warn the user about this field if we have not
# already done so
if self.map[_field]['field_name'] not in _warned:
_msg = "Warning: Import field '%s' is mapped to weewx field '%s'" % (self.map[_field]['field_name'],
_field)
self.wlog.printlog(syslog.LOG_INFO, _msg)
_msg = " but the import field could not be found."
self.wlog.printlog(syslog.LOG_INFO, _msg)
_msg = " weewx field '%s' will be set to 'None'." % _field
self.wlog.printlog(syslog.LOG_INFO, _msg)
# make sure we do this warning once only
_warned.append(self.map[_field]['field_name'])
# if we have a mapped field for a unit system with a valid value,
# then all we need do is set 'usUnits', bulk conversion is taken
# care of by saveToArchive()
if _units is not None:
# we have a mapped field for a unit system with a valid value
_rec['usUnits'] = _units
else:
# no mapped field for unit system but we have already converted
# any necessary fields on a field by field basis so all we need
# do is set 'usUnits', any bulk conversion will be taken care of
# by saveToArchive()
_rec['usUnits'] = unit_sys
# If interval is being derived from record timestamps our first
# record will have an interval of None. In this case we wait until
# we have the second record and then we use the interval between
# records 1 and 2 as the interval for record 1.
if len(_records) == 1 and _records[0]['interval'] is None:
_records[0]['interval'] = _rec['interval']
_last_ts = _rec['dateTime']
# this record is done, add it to our list of records to return
_records.append(_rec)
# If we have more than 1 unique value for interval in our records it
# could be a sign of missing data and impact the integrity of our data,
# so do the check and see if the user wants to continue
if len(_records) > 0:
# if we have any records to return do the unique interval check
# before we return the records
_start_interval = _records[0]['interval']
_diff_interval = False
for _rec in _records:
if _rec['interval'] != _start_interval:
_diff_interval = True
break
if _diff_interval and self.interval_ans != 'y':
# we had more than one unique value for interval, warn the user
self.wlog.printlog(syslog.LOG_INFO, "Warning: Records to be imported contain multiple different 'interval' values.")
print " This may mean the imported data is missing some records and it may lead"
print " to data integrity issues. If the raw data has a known, fixed interval value"
print " setting the relevant 'interval' setting in wee_import config to this value"
print " may give a better result."
while self.interval_ans not in ['y', 'n']:
self.interval_ans = raw_input('Are you sure you want to proceed (y/n)? ')
if self.interval_ans == 'n':
# the user chose to abort, but we may have already
# processed some records. So log it then raise a SystemExit()
if self.dry_run:
print "Dry run import aborted by user. %d records were processed." % self.total_rec_proc
else:
print "Those records with a timestamp already in the archive will not have been imported."
print "Confirm successful import in syslog or weewx log file."
_msg = "User chose to abort import. %d records were processed. Exiting." % self.total_rec_proc
self.wlog.logonly(syslog.LOG_INFO, _msg)
if self.total_rec_proc > 0:
print "As the import was aborted before completion refer to the weewx log"
print "file to confirm which records were imported."
raise SystemExit('Exiting.')
raise SystemExit('Exiting. Nothing done.')
self.wlog.verboselog(syslog.LOG_INFO,
"Mapped %d records." % len(_records))
# the user wants to continue or we have only one unique value for
# interval so return the records
return _records
else:
self.wlog.verboselog(syslog.LOG_INFO, "Mapped 0 records.")
# we have no records to return so return None
return None
def getInterval(self, last_ts, current_ts):
"""Determine an interval value for a record.
The interval field can be determined in one of the following ways:
- Derived from the raw data. The interval is calculated as the
difference between the timestamps of consecutive records rounded to
the nearest minute. In this case interval can change between
records if the records are not evenly spaced in time or if there
are missing records. This method is the default and is used when
the interval parameter in wee_import.conf is 'derive'.
- Read from weewx.conf. The interval value is read from the
archive_interval parameter in [StdArchive] in weewx.conf. In this
case interval may or may not be the same as the difference in time
between consecutive records. This method may be of use when the
import source has a known interval but may be missing a number of
records which makes deriving the interval from the imported data
problematic. This method is used when the interval parameter in
wee_import.conf is 'conf'.
Input parameters:
last_ts. timestamp of the previous record.
current_rain. timestamp of the current record.
Returns the interval (in minutes) for the current record.
"""
# did we have a number specified in wee_import.conf, if so use that
try:
return float(self.interval)
except:
pass
# how are we getting interval
if self.interval.lower() == 'conf':
# get interval from weewx.conf
return to_int(float(self.config_dict['StdArchive'].get('archive_interval')) / 60.0)
elif self.interval.lower() == 'derive':
# get interval from the timestamps of consecutive records
try:
_interval = int((current_ts - last_ts) / 60.0)
# but if _interval < 0 our records are not in date time order
if _interval < 0:
# so raise an error
_msg = "Cannot derive 'interval' for record timestamp: %s." % timestamp_to_string(current_ts)
self.wlog.printlog(syslog.LOG_INFO, _msg)
raise ValueError(
"Raw data is not in ascending date time order.")
except TypeError:
_interval = None
return _interval
else:
# we don't know what to do so raise an error
raise ValueError(
"Cannot derive 'interval'. Unknown 'interval' setting in %s." % self.import_config_path)
@staticmethod
def getRain(last_rain, current_rain):
"""Determine the rainfall in a period from two cumulative rainfall
values.
If the data source provides rainfall as a cumulative value then the
rainfall in a period is the simple difference between the two values.
But we need to take into account some special cases:
No last_rain value. Will occur for very first record or maybe in an
error condition. Need to return 0.0.
last_rain > current_rain. Occurs when rain counter was reset (maybe
daily or some other period). Need to return
current_rain.
Input parameters:
last_rain. Previous rainfall total.
current_rain. Current rainfall total.
Returns the rainfall in the period.
"""
if last_rain is not None:
# we have a value for the previous period
if current_rain >= last_rain:
# just return the difference
return current_rain - last_rain
else:
# we are at at a cumulative reset point so we just want
# current_rain
return current_rain
else:
# we have no previous rain value so return zero
return 0.0
def qc(self, data_dict, data_type):
""" Apply weewx.conf QC to a record.
If qc option is set in the import config file then apply any StdQC
min/max checks specfied in weewx.conf.
Input parameters:
data_dict: A weewx compatible archive record.
Returns nothing. data_dict is modified directly with obs outside of QC
limits set to None.
"""
if self.apply_qc:
self.import_QC.apply_qc(data_dict, data_type=data_type)
def calcMissing(self, record):
""" Add missing observations to a record.
If calc_missing option is True in the import config file then add any
missing derived observations (ie observation is missing or None) to the
imported record. The weewx WxCalculate class is used to add any missing
observations.
Input parameters:
record: A weewx compatible archive record.
Returns a weewx compatible archive record that includes any derived
observations that were previously missing/None.
"""
if self.calc_missing:
self.wxcalculate.do_calculations(record, 'archive')
return record
def saveToArchive(self, archive, records):
""" Save records to the weewx archive.
Supports saving one or more records to archive. Each collection of
records is processed and saved to archive in transactions of
self.tranche records at a time.
if the import config file qc option was set quality checks on the
imported record are performed using the weewx StdQC configuration from
weewx.conf . Any missing derived observations are then added to the
archive record using the weewx WXCalculate class if the import config
file calc_missing option was set. weewx API addRecord() method is used
to add archive records.
If --dry-run was set then every aspect of the import is carried out but
nothing is saved to archive. If --dry-run was not set then the user is
requested to confirm the import before any records are saved to archive.
Input parameters:
archive: database manager object for the weewx archive.
records: iterable that provides weewx compatible archive records
(in dict form) to be written to archive
"""
if self.first_period:
# collect the time for some stats reporting later
self.t1 = time.time()
# it's convenient to give this message now
if self.dry_run:
print 'Starting dry run import ...'
else:
print 'Starting import ...'
# do we have any records?
if records and len(records) > 0:
# if this is the first period then give a little summary about what
# records we have
if self.first_period:
if self.last_period:
# there is only 1 period, so we can count them
print "%s records identified for import." % len(records)
else:
# there are more periods so say so
print "Records covering multiple periods have been identified for import."
# we do, confirm the user actually wants to save them
while self.ans not in ['y', 'n'] and not self.dry_run:
print "Proceeding will save all imported records in the weewx archive."
self.ans = raw_input("Are you sure you want to proceed (y/n)? ")
if self.ans == 'y' or self.dry_run:
# we are going to save them
# reset record counter
nrecs = 0
# initialise our list of records for this tranche
_tranche = []
# initialise a set for use in our dry run, this lets us
# give some better stats on records imported
unique_set = set()
# if we are importing multiple periods of data then tell the
# user what period we are up to
if not (self.first_period and self.last_period):
print "Period %d ..." % self.period_no
# step through each record in this period
for _rec in records:
# convert our record
_conv_rec = to_std_system(_rec, self.archive_unit_sys)
# perform any any required QC checks
self.qc(_conv_rec, 'Archive')
# now add any derived obs that we can to our record
_final_rec = self.calcMissing(_rec)
# add the record to our tranche and increment our count
_tranche.append(_final_rec)
nrecs += 1
# if we have a full tranche then save to archive and reset
# the tranche
if len(_tranche) >= self.tranche:
# add the record only if it is not a dry run
if not self.dry_run:
# add the record only if it is not a dry run
archive.addRecord(_tranche)
# add our the dateTime for each record in our tranche
# to the dry run set
for _trec in _tranche:
unique_set.add(_trec['dateTime'])
# tell the user what we have done
_msg = "Records processed: %d; Unique records: %d; Last timestamp: %s\r" % (nrecs,
len(unique_set),
timestamp_to_string(_final_rec['dateTime']))
print >> sys.stdout, _msg,
sys.stdout.flush()
_tranche = []
# we have processed all records but do we have any records left
# in the tranche?
if len(_tranche) > 0:
# we do so process them
if not self.dry_run:
# add the record only if it is not a dry run
archive.addRecord(_tranche)
# add our the dateTime for each record in our tranche to
# the dry run set
for _trec in _tranche:
unique_set.add(_trec['dateTime'])
# tell the user what we have done
_msg = "Records processed: %d; Unique records: %d; Last timestamp: %s\r" % (nrecs,
len(unique_set),
timestamp_to_string(_final_rec['dateTime']))
print >> sys.stdout, _msg,
print
sys.stdout.flush()
# update our counts
self.total_rec_proc += nrecs
self.total_unique_rec += len(unique_set)
elif self.ans == 'n':
# user does not want to import so display a message and then
# ask to exit
self.wlog.logonly(syslog.LOG_INFO,
'User chose not to import records. Exiting. Nothing done.')
raise SystemExit('Exiting. Nothing done.')
else:
# we have no records to import, advise the user but what we say
# will depend if there are any more periods to import
if self.first_period and self.last_period:
# there was only 1 period
_msg = 'No records identified for import.'
else:
# multiple periods
_msg = 'Period %d - no records identified for import.' % self.period_no
print _msg
# if we have finished record the time taken for our summary
if self.last_period:
self.tdiff = time.time() - self.t1
# ============================================================================
# class WeeImportLog
# ============================================================================
class WeeImportLog(object):
"""Class to handle wee_import logging.
This class provides a wrapper around the python syslog module to handle
wee_import logging requirements. The --log=- command line option disables
log output otherwise log output is sent to the same log used by weewx.
"""
def __init__(self, opt_logging, opt_verbose, opt_dry_run):
"""Initialise our log environment."""
# first check if we are turning off log to file or not
if opt_logging:
log_bool = opt_logging.strip() == '-'
else:
log_bool = False
# Flag to indicate whether we are logging to file or not. Log to file
# every time except when logging is explicitly turned off on the
# command line or its a dry run.
self.log = not (opt_dry_run or log_bool)
# if we are logging then setup our syslog environment
# if --verbose we log up to syslog.LOG_DEBUG
# otherwise just log up to syslog.LOG_INFO
if self.log:
syslog.openlog(logoption=syslog.LOG_PID | syslog.LOG_CONS)
if opt_verbose:
syslog.setlogmask(syslog.LOG_UPTO(syslog.LOG_DEBUG))
else:
syslog.setlogmask(syslog.LOG_UPTO(syslog.LOG_INFO))
# logging by other modules (eg WxCalculate) does not use WeeImportLog
# but we can disable most logging by raising the log priority if its a
# dry run
if opt_dry_run:
syslog.setlogmask(syslog.LOG_UPTO(syslog.LOG_CRIT))
# keep opt_verbose for later
self.verbose = opt_verbose
def logonly(self, level, message):
"""Log to file only."""
# are we logging ?
if self.log:
# add a little preamble to say this is wee_import
_message = 'wee_import: ' + message
syslog.syslog(level, _message)
def printlog(self, level, message):
"""Print to screen and log to file."""
print message
self.logonly(level, message)
def verboselog(self, level, message):
"""Print to screen if --verbose and log to file always."""
if self.verbose:
print message
self.logonly(level, message)
# ============================================================================
# Utility functions
# ============================================================================
def get_binding(config_dict):
"""Get the binding for the weewx database."""
# Extract our binding from the StdArchive section of the config file. If
# it's missing, return None.
if 'StdArchive' in config_dict:
db_binding_wx = config_dict['StdArchive'].get('data_binding',
'wx_binding')
else:
db_binding_wx = None
return db_binding_wx
