signalfx 0.3.8

SignalFx Python Library

# Python client library for SignalFx

This is a programmatic interface in Python for SignalFx's metadata and
ingest APIs. It is meant to provide a base for communicating with
SignalFx APIs that can be easily leveraged by scripts and applications
to interact with SignalFx or report metric and event data to SignalFx.
It is also the base for metric reporters that integrate with common
Python-based metric collections tools or libraries.

## Installation

To install from pip:

```
pip install signalfx
```

To install from source:

```
git clone https://github.com/signalfx/signalfx-python.git
cd signalfx-python
python setup.py install
```

## Usage

### API access token

To use this library, you need a SignalFx API access token, which can be
obtained from the SignalFx organization you want to report data into.

### Reporting data

Basic usage of the library for reporting data goes as follows:

```python
import signalfx

sfx = signalfx.SignalFx('MY_TOKEN')
sfx.send(
gauges=[
{'metric': 'myfunc.time',
'value': 532,
'timestamp': 1442960607000},
...
],
counters=[
{'metric': 'myfunc.calls',
'value': 42,
'timestamp': 1442960607000},
...
],
cumulative_counters=[
{'metric': 'myfunc.calls_cumulative',
'value': 10,
'timestamp': 1442960607000},
...
])
# After all datapoints have been sent, flush any remaining messages
# in the send queue and terminate all connections
sfx.stop()
```

The `timestamp` must be a millisecond precision timestamp; the number of
milliseconds elapsed since Epoch. The `timestamp` field is optional, but
strongly recommended. If not specified, it will be set by SignalFx's
ingest servers automatically; in this situation, the timestamp of your
datapoints will not accurately represent the time of their measurement
(network latency, batching, etc. will all impact when those datapoints
actually make it to SignalFx).

When sending datapoints with multiple calls to `send()`, it is recommended
to re-use the same SignalFx client object for each `send()` call.

If you must use multiple client objects for the same token, which is not
recommended, it is important to call `stop()` after making all `send()`
calls. Each SignalFx client object uses a background thread to send
datapoints without blocking the caller. Calling `stop()` will gracefully
flush the thread's send queue and close its TCP connections.

#### Sending multi-dimensional data

Reporting dimensions for the data is also optional, and can be
accomplished by specifying a `dimensions` parameter on each datapoint
containing a dictionary of string to string key/value pairs representing
the dimensions:

```python
import signalfx

sfx = signalfx.SignalFx('MY_TOKEN')
sfx.send(
gauges=[
{
'metric': 'myfunc.time',
'value': 532,
'timestamp': 1442960607000,
'dimensions': {'host': 'server1', 'host_ip': '1.2.3.4'}
},
...
], ...)
sfx.stop()
```

See [`examples/generic_usecase.py`](examples/generic_usecase.py) for a
complete code sample showing how to send data to SignalFx.

### Sending events

Events can be sent to SignalFx via the `send_event` function. The
event type must be specified, and dimensions and extra event properties
can be supplied as well.

```python
import signalfx

sfx = signalfx.SignalFx('MY_TOKEN')
sfx.send_event(
event_type='deployments',
dimensions={
'host': 'myhost',
'service': 'myservice',
'instance': 'myinstance'},
properties={
'version': '2015.04.29-01'})
```

See `examples/generic_usecase.py` for a complete code example.

### Metric metadata and tags

The library includes functions that search, get, and update metric
metadata and tags. Deleting tags is also supported.

```python
import signalfx

sfx = signalfx.SignalFx('MY_TOKEN')
sfx.update_tag('some_tag_name',
description='an example tag',
custom_properties={'version':'some_number'})
```

### AWS integration

Optionally, the client may be configured to append additional dimensions to
all metrics and events sent to SignalFx. One use case for this is to append
the AWS unique ID of the current host as an extra dimension.
For example,

```python
import signalfx
from signalfx.aws import AWS_ID_DIMENSION, get_aws_unique_id

sfx = signalfx.SignalFx('your_api_token')
sfx.add_dimensions({AWS_ID_DIMENSION: get_aws_unique_id()})
sfx.send(
gauges=[
{
'metric': 'myfunc.time',
'value': 532,
'timestamp': 1442960607000
'dimensions': {'host': 'server1', 'host_ip': '1.2.3.4'}
},
])
sfx.stop()
```

### Pyformance reporter

`pyformance` is a Python library that provides CodaHale-style metrics in
a very Pythonic way. We offer a reporter that can report the
`pyformance` metric registry data directly to SignalFx.

```python
from pyformance import count_calls, gauge
import signalfx.pyformance

@count_calls
def callme():
# whatever
pass

sfx = signalfx.pyformance.SignalFxReporter(api_token='MY_TOKEN')
sfx.start()

callme()
callme()
gauge('test').set_value(42)
...
```

See `examples/pyformance_usecase.py` for a complete code example using Pyformance.

### Known Issues

#### Sending only 1 datapoint and not seeing it in the chart

The reason you are not seeing the metrics in the chart is because the
script that is calling the Python client module is exiting right after
calling the send method. The Python client library is mainly targeted
towards sending a continuous stream of metrics and was implemented to be
asynchronous.

To work around this problem (most common in short-lived scripts for
example), register an `atexit` function to cleaning stop the datapoint
sending thread when your program exits:

```python
import atexit
import signalfx

sfx = signalfx.SignalFx('MY_TOKEN')
atexit.register(sfx.stop)
```

#### SSLError when sending events by calling send_event() method

```
ERROR:root:Posting to SignalFx failed.
SSLError: hostname 'ingest.signalfx.com' doesn't match either of
'*.signalfuse.com', 'signalfuse.com'.
```

Root Cause: SignalFx's API endpoints have SSL SNI enabled and the
`urllib3` module in Python versions prior to 2.7.8 had a bug that causes
the above issue. This was fixed in later versions of Python; we
recommend using Python 2.7.9 or newer when using this library.