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Merge remote-tracking branch 'influxdb/master'
2 parents d086aa7 + a7ba64f commit 54da635

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‎.travis.yml

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@@ -10,12 +10,24 @@ env:
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- TOX_ENV=flake8
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- TOX_ENV=coverage
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install:
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- sudo pip install tox
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- sudo pip install coveralls
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- wget http://get.influxdb.org/influxdb_0.9.0-rc26_amd64.deb && sudo dpkg -i influxdb_0.9.0-rc26_amd64.deb
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- pip install tox
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- pip install coveralls
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- mkdir influxdb_install
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- wget https://s3.amazonaws.com/influxdb/influxdb_0.9.2_amd64.deb
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- dpkg -x influxdb_*_amd64.deb influxdb_install
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script:
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- travis_wait tox -e $TOX_ENV
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- export INFLUXDB_PYTHON_INFLUXD_PATH=$(pwd)/influxdb_install/opt/influxdb/versions/0.9.2/influxd
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- travis_wait 30 tox -e $TOX_ENV
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after_success:
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- if [ "$TOX_ENV" == "coverage" ] ; then coveralls; fi
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notifications:
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email: false
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sudo: false
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# Travis caching
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cache:
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directories:
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- $HOME/.cache/pip
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before_cache:
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- rm -f $HOME/.cache/pip/log/debug.log

‎README.rst

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@@ -36,16 +36,10 @@ InfluxDB is an open-source distributed time series database, find more about Inf
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.. _installation:
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InfluxDB > v0.9 support
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=======================
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The 1.0.0 version of this library now supports InfluxDB 0.9. Please note that InfluxDB 0.9 is still pre-release software. For stability, you should use the ``influxdb.influxdb08`` module in conjunction with InfluxDB 0.8.
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InfluxDB v0.8.X users
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=====================
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Influxdb >=0.9.0 brings many breaking changes to the API. InfluxDB 0.8.X users may use the legacy client by using ``from influxdb.influxdb08 import InfluxDBClient`` instead.
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InfluxDB 0.9 was released and it is the new recommended version. However, InfluxDB 0.8.x users may still use the legacy client by using ``from influxdb.influxdb08 import InfluxDBClient`` instead.
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Installation
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============
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>>> json_body = [
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{
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"name": "cpu_load_short",
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"measurement": "cpu_load_short",
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"tags": {
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"host": "server01",
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"region": "us-west"
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},
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"timestamp": "2009-11-10T23:00:00Z",
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"time": "2009-11-10T23:00:00Z",
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"fields": {
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"value": 0.64
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}

‎docs/source/resultset.rst

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@@ -7,33 +7,39 @@ Query response object: ResultSet
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Using the ``InfluxDBClient.query()`` function will return a ``ResultSet`` Object.
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A ResultSet behaves like a dict. Its keys are series and values are points. However, it is a little bit smarter than a regular dict. Its ``__getitem__`` method can be used to query the ResultSet in several ways.
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A ResultSet can be browsed in several ways. Its ``get_points`` method can be used to retrieve points generators that filter either by measurement, tags, or both.
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Filtering by serie name
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-----------------------
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Getting all points
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------------------
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Using ``rs['cpu']`` will return a generator for all the points that are in a serie named ``cpu``, no matter the tags.
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Using ``rs.get_points()`` will return a generator for all the points in the ResultSet.
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Filtering by measurement
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------------------------
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Using ``rs.get_points('cpu')`` will return a generator for all the points that are in a serie with measurement name ``cpu``, no matter the tags.
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::
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rs = cli.query("SELECT * from cpu")
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cpu_points = list(rs['cpu'])
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cpu_points = list(rs.get_points(measurement='cpu')])
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Filtering by tags
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-----------------
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Using ``rs[{'host_name': 'influxdb.com'}]`` will return a generator for all the points that are tagged with the specified tags, no matter the serie name.
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Using ``rs.get_points(tags={'host_name': 'influxdb.com'})`` will return a generator for all the points that are tagged with the specified tags, no matter the measurement name.
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::
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rs = cli.query("SELECT * from cpu")
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cpu_influxdb_com_points = list(rs[{"host_name": "influxdb.com"}])
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cpu_influxdb_com_points = list(rs.get_points(tags={"host_name": "influxdb.com"}))
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Filtering by serie name and tags
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--------------------------------
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Filtering by measurement and tags
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---------------------------------
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Using a tuple with a serie name and a dict will return a generator for all the points that are in a serie with the given name AND whose tags match the given tags.
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Using measurement name and tags will return a generator for all the points that are in a serie with the specified measurement name AND whose tags match the given tags.
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::
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rs = cli.query("SELECT * from cpu")
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points = list(rs[('cpu', {'host_name': 'influxdb.com'})])
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points = list(rs.get_points(measurement='cpu', tags={'host_name': 'influxdb.com'}))
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See the :ref:`api-documentation` page for more information.

‎examples/tutorial.py

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@@ -12,12 +12,12 @@ def main(host='localhost', port=8086):
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query = 'select value from cpu_load_short;'
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json_body = [
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{
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"name": "cpu_load_short",
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"measurement": "cpu_load_short",
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"tags": {
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"host": "server01",
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"region": "us-west"
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},
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"timestamp": "2009-11-10T23:00:00Z",
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"time": "2009-11-10T23:00:00Z",
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"fields": {
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"value": 0.64
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}

‎examples/tutorial_server_data.py

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hostName = "server-%d" % random.randint(1, 5)
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# pointValues = [int(past_date.strftime('%s')), value, hostName]
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pointValues = {
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"timestamp": int(past_date.strftime('%s')),
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"name": metric,
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"time": int(past_date.strftime('%s')),
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"measurement": metric,
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'fields': {
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'value': value,
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},

‎examples/tutorial_sine_wave.py

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y = 10 + math.sin(math.radians(angle)) * 10
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point = {
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"name": 'foobar',
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"timestamp": int(now.strftime('%s')) + angle,
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"measurement": 'foobar',
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"time": int(now.strftime('%s')) + angle,
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"fields": {
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"value": y
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}

‎influxdb/__init__.py

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]
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__version__ = '2.2.0'
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__version__ = '2.7.3'

‎influxdb/_dataframe_client.py

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@@ -137,10 +137,10 @@ def _convert_dataframe_to_json(self, dataframe, measurement, tags=None):
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dataframe = dataframe.astype('object')
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points = [
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{'name': measurement,
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{'measurement': measurement,
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'tags': tags if tags else {},
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'fields': rec,
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'timestamp': ts.isoformat()
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'time': ts.isoformat()
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}
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for ts, rec in zip(dataframe.index, dataframe.to_dict('record'))]
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return points

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