add sending udp message on behalf of an non-supporting server
This commit is contained in:
106
influx.py
106
influx.py
@ -105,6 +105,30 @@ class NamedTuple(tuple):
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raise
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return default
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@property
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def names(self):
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return tuple(self._idx_by_name)
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def tuple(self, *keys):
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return tuple(self.get(k) for k in keys)
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class Table(list):
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"""a list of tuples with meta info"""
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def __init__(self, tags, key_names, column_names):
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super().__init__()
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self.tags = tags
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self.key_names = key_names
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self.column_names = column_names
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class Single(Table):
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"""a single row of a table, as a list with meta info"""
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def __init__(self, table):
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super().__init__(table.tags, table.key_names, table.column_names)
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single, = table
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self[:] = single
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class RegExp(str):
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"""indicates, tht this string should be treated as regexp
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@ -229,23 +253,28 @@ class InfluxDBWrapper:
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# query the database
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def query(self, start=None, stop=None, interval=None, last=False, columns=None, **tags):
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def query(self, start=None, stop=None, interval=None, single=None, columns=None, **tags):
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"""Returns queried data as InfluxDB tables
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:param start: start time. default is a month ago
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:param stop: end time, default is tomorrow at the same time
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:param interval: if set an aggregation filter will be applied. This will
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return only the latest values per time interval in seconds.
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:param last: when True, only the last value within the interval is returned
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(for any existing combinations of tags!)
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:param single: when True (or 1), only the last value within the interval is returned
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(for any existing combinations of tags!)
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single=-1: return the first value instead
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:param columns: if given, return only these columns (in addition to '_time' and '_value')
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:param tags: selection criteria:
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<tag>=None
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return records independent of this tag. the value will be contained in the result dicts key
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return records independent of this tag.
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the obtained value will be contained in the result dicts key
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<tag>=[<value1>, <value2>, ...]
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return records where tag is one from the list. the value is contained in the result dicts key
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<tag>>=<value>:
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return only records with given tag matching <value>. the value is not part of the results key
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return records where tag is one from the list.
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the obtained value is contained in the result dicts key
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<tag>=<value>:
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return only records with given tag matching <value>.
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the obtained value is contained in the result dicts key only
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if the value is an instance of RegExp or when it contains an asterisk ('*')
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:return: a dict <tuple of key values> of list of <row>
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where <tuple of keys> and <row> are NamedTuple
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@ -255,55 +284,61 @@ class InfluxDBWrapper:
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msg = [f'from(bucket:"{self._bucket}")',
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f'|> range(start: {start}, stop: {stop})']
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keynames = []
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keys = {}
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dropcols = ['_start', '_stop']
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fixed_tags = {}
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for key, crit in tags.items():
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if crit is None:
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keynames.append(key)
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keys[key] = None
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continue
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if isinstance(crit, str):
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if isinstance(crit, RegExp) or '*' in crit:
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keynames.append(key)
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keys[key] = None
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append_wildcard_filter(msg, key, [crit])
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continue
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fixed_tags[key] = crit
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dropcols.append(key)
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crit = f'"{crit}"'
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elif isinstance(crit, (int, float)):
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fixed_tags[key] = crit
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dropcols.append(key)
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else:
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try:
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keynames.append(key)
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keys[key] = None
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append_wildcard_filter(msg, key, crit)
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continue
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except Exception:
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raise ValueError(f'illegal value for {key}: {crit}')
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msg.append(f'|> filter(fn:(r) => r.{key} == {crit})')
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if last:
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msg.append('|> last(column: "_time")')
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if single:
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if single < 0:
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msg.append('|> first(column: "_time")')
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else:
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msg.append('|> last(column: "_time")')
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if interval:
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msg.append(f'|> aggregateWindow(every: {interval}s, fn: last, createEmpty: false)')
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if columns is None:
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msg.append(f'''|> drop(columns:["{'","'.join(dropcols)}"])''')
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else:
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columns = ['_time', '_value'] + list(columns)
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msg.append(f'''|> keep(columns:["{'","'.join(columns + keynames)}"])''')
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msg.append(f'''|> keep(columns:["{'","'.join(columns + keys)}"])''')
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msg = '\n'.join(msg)
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print(msg)
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reader = self._client.query_api().query_csv(msg)
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print('CSV')
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print('CSV', keys, columns)
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converters = None
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group = None
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column_names = None
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column_keys = None
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key = None
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result = {}
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table = None
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tableno = None
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for row in reader:
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if not row:
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continue
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print(row)
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if row[0]:
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if row[0] == '#datatype':
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converters = {i: CONVERTER.get(d) for i, d in enumerate(row) if i > 2}
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@ -312,31 +347,27 @@ class InfluxDBWrapper:
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group = row
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continue
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if column_names is None:
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print('COL', row)
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column_names = row
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keys = {}
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for col, (name, grp) in enumerate(zip(column_names, group)):
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if grp != 'true':
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continue
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# if name in keynames or (columns is None and name not in dropcols):
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if name in keynames or columns is None:
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keys[col] = converters.pop(col)
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valuecls = NamedTuple([row[i] for i in converters])
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keycls = NamedTuple([row[i] for i in keys])
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if columns is None or name in keys:
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keys[name] = col, converters.pop(col)
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column_keys = tuple(column_names[i] for i in converters)
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continue
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if row[2] != table:
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if row[2] != tableno:
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# new table, new key
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table = row[2]
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key = keycls(f(row[i]) for i, f in keys.items())
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print('new table', table, key)
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tableno = row[2]
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key_dict = {n: f(row[i]) for n, (i, f) in keys.items()}
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key = tuple(key_dict.values())
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if result.get(key) is None:
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result[key] = []
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print('KC', key_dict, column_keys)
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result[key] = Table({**fixed_tags, **key_dict}, tuple(keys), column_keys)
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result[key].append(valuecls(f(row[i]) for i, f in converters.items()))
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if last:
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print('LAST')
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result[key].append(tuple(f(row[i]) for i, f in converters.items()))
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if single:
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for key, table in result.items():
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result[key], = table
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result[key] = Single(table)
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else:
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for table in result.values():
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table.sort()
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@ -354,9 +385,10 @@ class InfluxDBWrapper:
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:param add_prev: amount of time to look back for the last previous point (default: 1 hr)
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:param add_end: whether to add endpoint at stop time (default: False)
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:param tags: further selection criteria
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:return: a dict <tuple of key values> of list of <row>
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where <tuple of keys> and <row> are NamedTuple
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<row> is (<timestamp>, <value>)
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:return: a dict <tuple of key values> of <Table> or <Single>
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where <Table> is a list of tuples with some meta info (table.tags, table.column_names)
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and <Single> is a list (a single row of a table) with the same meta info
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when _field='float' (the default), the returned values are either a floats or None
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"""
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@ -370,7 +402,7 @@ class InfluxDBWrapper:
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else:
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result = {}
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if add_prev:
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prev_data = self.query(rstart - add_prev, rstart, last=True, **tags)
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prev_data = self.query(rstart - add_prev, rstart, single=1, **tags)
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for key, first in prev_data.items():
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curve = result.get(key)
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if first[1] is not None:
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