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Project description
A Monasca-Statsd Python client.
================
Quick Start Guide
-----------------
First install the library with `pip` or `easy_install`
# Install in system python ...
sudo pip install monasca-statsd
# .. or into a virtual env
pip install monasca-statsd
Then start instrumenting your code:
```
# Import the module.
import monascastatsd as mstatsd
# Create the connection
conn = mstatsd.Connection(host='localhost', port=8125)
# Create the client with optional dimensions
client = mstatsd.Client(connection=conn, dimensions={'env': 'test'})
NOTE: You can also create a client without specifying the connection and it will create the client
with the default connection information for the monasca-agent statsd processor daemon
which uses host='localhost' and port=8125.
client = mstatsd.Client(dimensions={'env': 'test'})
# Increment and decrement a counter.
counter = client.get_counter(name='page.views')
counter.increment()
counter += 3
counter.decrement()
counter -= 3
# Record a gauge 50% of the time.
gauge = client.get_gauge('gauge', dimensions={'env': 'test'})
gauge.send('metric', 123.4, sample_rate=0.5)
# Sample a histogram.
histogram = client.get_histogram('histogram', dimensions={'test': 'True'})
histogram.send('metric', 123.4, dimensions={'color': 'red'})
# Time a function call.
timer = client.get_timer()
@timer.timed('page.render')
def render_page():
# Render things ...
pass
# Time a block of code.
timer = client.get_timer()
with timer.time('t'):
# Do stuff
time.sleep(2)
# Add dimensions to any metric.
histogram = client.get_histogram('my_hist')
histogram.send('query.time', 10, dimensions = {'version': '1.0', 'environment': 'dev'})
```
Repository
-------------
The monasca-statsd code is located here:
[here](https://github.com/stackforge/monasca-statsd).
Feedback
--------
To suggest a feature, report a bug, or general discussion, head over
[here](https://bugs.launchpad.net/monasca).
License
-------
See LICENSE file
Code was originally forked from Datadog's dogstatsd-python, hence the dual license.
================
Quick Start Guide
-----------------
First install the library with `pip` or `easy_install`
# Install in system python ...
sudo pip install monasca-statsd
# .. or into a virtual env
pip install monasca-statsd
Then start instrumenting your code:
```
# Import the module.
import monascastatsd as mstatsd
# Create the connection
conn = mstatsd.Connection(host='localhost', port=8125)
# Create the client with optional dimensions
client = mstatsd.Client(connection=conn, dimensions={'env': 'test'})
NOTE: You can also create a client without specifying the connection and it will create the client
with the default connection information for the monasca-agent statsd processor daemon
which uses host='localhost' and port=8125.
client = mstatsd.Client(dimensions={'env': 'test'})
# Increment and decrement a counter.
counter = client.get_counter(name='page.views')
counter.increment()
counter += 3
counter.decrement()
counter -= 3
# Record a gauge 50% of the time.
gauge = client.get_gauge('gauge', dimensions={'env': 'test'})
gauge.send('metric', 123.4, sample_rate=0.5)
# Sample a histogram.
histogram = client.get_histogram('histogram', dimensions={'test': 'True'})
histogram.send('metric', 123.4, dimensions={'color': 'red'})
# Time a function call.
timer = client.get_timer()
@timer.timed('page.render')
def render_page():
# Render things ...
pass
# Time a block of code.
timer = client.get_timer()
with timer.time('t'):
# Do stuff
time.sleep(2)
# Add dimensions to any metric.
histogram = client.get_histogram('my_hist')
histogram.send('query.time', 10, dimensions = {'version': '1.0', 'environment': 'dev'})
```
Repository
-------------
The monasca-statsd code is located here:
[here](https://github.com/stackforge/monasca-statsd).
Feedback
--------
To suggest a feature, report a bug, or general discussion, head over
[here](https://bugs.launchpad.net/monasca).
License
-------
See LICENSE file
Code was originally forked from Datadog's dogstatsd-python, hence the dual license.
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