Inflow¶
A simple InfluxDB Python client library. It is an alternative for the official InfluxDB Python client library.
Inflow officially supports Python 2.7 and up, but the latest Python 3 version is recommended.
InfluxDB is supported from version 1.0 and up.
Documentation is hosted on Read the Docs.
Source code can be found on GitHub.
Warning
This project is still very much in development, stuff might work, or not. API’s might change, or even be removed. So be careful. This message will be removed once a stable version is released.
Example¶
You can write measurements in a few different ways, but writing a single “temperature” measurement is as simple as:
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
client.write('temperature', value=21.3)
For more examples and docs on how to use the client, go to Writing Measurements and Querying.
Installing¶
$ pip install inflow
License¶
Inflow is licensed under Mozilla Public License. © 2016 Advanced Climate Systems.
Table of Contents¶
Writing Measurements¶
Examples¶
You can write measurements in a few different ways, but writing a single “temperature” measurement is as simple as:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
client.write('temperature', value=21.3)
No time is specified in the above example, so inflow automatically set’s the
measurement’s time to the current time. Also, no tags are provided to the
write method, so no tags are attached to the measurement.
A more complex example of writing a single measurement:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
client.write(
'temperature',
tags={
'location': 'groningen',
'sensor_type': 'ni1000'
},
value=21.3,
timestamp=1475845863
)
Writing multiple measurements is also possible:
#!/usr/bin/env python
from inflow import Client, Measurement
client = Client('http://username:pass@localhost:8086/databasename')
client.write([
Measurement(
name='temperature',
tags={
'location': 'groningen',
'sensor_type': 'ni1000'
},
value=21.3,
timestamp=1475845863
),
Measurement(
name='temperature',
tags={
'location': 'groningen',
'sensor_type': 'ni1000'
},
value=20.1,
timestamp=1475848864
)
])
However, this is a bit verbose. That’s why you can also do this:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
temperature = dict(
name='temperature',
tags={
'location': 'groningen',
'sensor_type': 'ni1000'
}
)
client.write(temperature, [
{'value': 21.3, 'timestamp': 1475845863},
{'value': 20.1, 'timestamp': 1475846182}
])
In the above examples, every write call will issue a direct call to the
InfluxDB API. You can accumulate measurements and write them all at once using
Sessions.
Note
In every example, we use timestamp ints (in seconds) to specify the time for each measurement. You can also set the timestamp to a datetime. Inflow will automatically convert both to the right precision when writing to InfluxDB.
Warning
If you supply a Python datetime instance as the timestamp, make sure it is a timezone-aware instance, in the UTC timezone.
Multiple Values¶
In all the examples above, we assume there is only one actual value for
the given measurements. However, InfluxDB supports having an arbitrary amount
of values for every measurements. This is also possible in Inflow:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
client.write(
'temperature',
timestamp=1475846182,
lower_sensor=20.9,
upper_sensor=23.2
)
This will create a measurement with the lower_sensor and upper_sensor
values. This method also works when manually writing Measurement
instances, and when writing lists of dicts.
Precision¶
By default, Inflow assumes the timestamps that are written to InfluxDB are in seconds. However, you can specify a custom precision when creating the client:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename',
precision='ms')
client.write('temperature', value=21.3, timestamp=1476191999000)
The precision needs to be one of: h, m, s, ms, u or ns.
Retention Policies¶
By default, Inflow will write to the database’s default retention policy. However, you can explicitly specify which retention policy your measurements should be written to:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename',
retention_policy='rp_four_weeks')
client.write('temperature', value=21.3)
You can also specify the retention policy when calling into write:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
client.write('temperature', value=21.3, retention_policy='rp_four_weeks')
Sessions¶
In the examples listed in Writing Measurements, every call to write will
issue a direct call to the InfluxDB API. There might be situations where you’d
want to accumulate measurements and write them all at once. That’s what
sessions are for:
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
session = client.session()
session.write('temperature', value=23.1, timestamp=1475848864)
session.write('temperature', value=25.0, timestamp=1475849823)
session.commit()
In the above example, a session is created in which we issue our write
calls. After doing some write calls, we call commit on the session.
This will issue the write to the InfluxDB API. If commit isn’t called on
the sessions, the data given in the write‘s will be lost.
Note
The session’s write method works exactly the same as that of the
normal client.
Warning
Don’t try to call query on a session, as Sessions are only
meant to do writes. If you want to do queries, just use the
Client.
As a Context Manager¶
You can also use the session as a context manager:
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
with client.session() as session:
session.write('temperature', value=23.1, timestamp=1475848864)
session.write('temperature', value=25.0, timestamp=1475849823)
When the context manager exits, the session is automatically committed.
Autocommitting¶
You can also have the session autocommit after a certain amount of write
calls, using autocommit_every:
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
session = client.session(autocommit_every=5)
session.write('temperature', value=23.1, timestamp=1475848864)
session.write('temperature', value=25.0, timestamp=1475849823)
session.write('temperature', value=22.9, timestamp=1475849825)
session.write('temperature', value=28.2, timestamp=1475849912)
# This next write call will trigger the autocommit.
session.write('temperature', value=25.1, timestamp=1475849999)
Retention Policies¶
You can also specify the retention policy for the entire session:
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
with client.session(retention_policy='rp_four_weeks') as session:
session.write('temperature', value=23.1, timestamp=1475848864)
Note
Unlike the Client.write method, you cannot specify the retention policy on the Session.write. Retention policies are Session-wide.
Querying¶
Inflow contains a minimal abstraction over the /query endpoint of the
InfluxDB HTTP API.
Getting a list of measurements is as simple as:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
results = client.query('SELECT * FROM "temperatures"')
# Results will contain a list of dicts for each returned measurement.
Say you’ve got a measurement called temperature (just as in the example
above), which contains a value field, a location tag, and contains 2
values. To query that data you would call the query method as described in
the above example, which will return a list with the following structure:
[
{
'name': 'temperature',
'values': [
{
'value': 21.0,
'timestamp': '2016-01-10T00:01:00Z',
'location': 'groningen'
},
{
'valuestamp': 23.0,
'time': '2016-01-10T00:02:00Z',
'location': 'groningen'
}
]
}
]
You can use any query type that InfluxDB allows, and it should work.
Unix Timestamps¶
By default, InfluxDB will return timestamps in RFC3339 format with nanosecond
precision. If you want instead want unix timestamps (in a specific precision),
you can use the epoch kwarg, like this:
#!/usr/bin/env python
from inflow import Client
client = Client('http://username:pass@localhost:8086/databasename')
results = client.query('SELECT * FROM "temperatures"', epoch='s')
In this example, we specify that we want unix timestamps, in seconds. The
epoch argument accepts one of h, m, s, ms, u and
ns.
Error Handling¶
If you’re doing something that the InfluxDB API deems wrong, it will return an error. These errors can occur when trying to query or write data. The exceptions described below wrap the errors returned by the InfluxDB API, and you should probably make sure you handle them in your code.
Exception types¶
-
class
inflow.InfluxDBException[source]¶ Generic exception for InfluxDB HTTP error’s, all other exceptions subclass from this one.
The message in this exception (and it’s subclasses) is the raw error message returned by the InfluxDB HTTP API.
-
class
inflow.QueryFailedException[source]¶ Thrown when a query is rejected by the API. For example, this happens when you have a syntactically incorrect query.
-
class
inflow.DatabaseNotFoundException[source]¶ Thrown when trying to write to a non-existing database.
Thrown when trying to log in using incorrect credentials.