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Convert NaN values to None in numpy arrays. #204

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Jul 5, 2015
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Convert NaN values to None in numpy arrays. #204

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28 changes: 21 additions & 7 deletions influxdb/influxdb08/dataframe_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,18 +15,17 @@ class DataFrameClient(InfluxDBClient):
The client reads and writes from pandas DataFrames.
"""

def __init__(self, *args, **kwargs):
def __init__(self, ignore_nan=True, *args, **kwargs):
super(DataFrameClient, self).__init__(*args, **kwargs)

try:
global pd
import pandas as pd
except ImportError as ex:
raise ImportError(
'DataFrameClient requires Pandas, "{ex}" problem importing'
.format(ex=str(ex))
)

raise ImportError('DataFrameClient requires Pandas, '
'"{ex}" problem importing'.format(ex=str(ex)))
self.EPOCH = pd.Timestamp('1970-01-01 00:00:00.000+00:00')
self.ignore_nan = ignore_nan

def write_points(self, data, *args, **kwargs):
"""
Expand Down Expand Up @@ -135,9 +134,24 @@ def _convert_dataframe_to_json(self, dataframe, name, time_precision='s'):
for dt in dataframe.index]
data = {'name': name,
'columns': [str(column) for column in dataframe.columns],
'points': list([list(x) for x in dataframe.values])}
'points': [self._convert_array(x) for x in dataframe.values]}
return data

def _convert_array(self, array):
try:
global np
import numpy as np
except ImportError as ex:
raise ImportError('DataFrameClient requires Numpy, '
'"{ex}" problem importing'.format(ex=str(ex)))
if self.ignore_nan:
number_types = (int, float, np.number)
condition = (all(isinstance(el, number_types) for el in array) and
np.isnan(array))
return list(np.where(condition, None, array))
else:
return list(array)

def _datetime_to_epoch(self, datetime, time_precision='s'):
seconds = (datetime - self.EPOCH).total_seconds()
if time_precision == 's':
Expand Down
26 changes: 26 additions & 0 deletions tests/influxdb/influxdb08/dataframe_client_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,6 +52,32 @@ def test_write_points_from_dataframe(self):

self.assertListEqual(json.loads(m.last_request.body), points)

def test_write_points_from_dataframe_with_float_nan(self):
now = pd.Timestamp('1970-01-01 00:00+00:00')
dataframe = pd.DataFrame(data=[[1, float("NaN"), 1.0], [2, 2, 2.0]],
index=[now, now + timedelta(hours=1)],
columns=["column_one", "column_two",
"column_three"])
points = [
{
"points": [
[1, None, 1.0, 0],
[2, 2, 2.0, 3600]
],
"name": "foo",
"columns": ["column_one", "column_two", "column_three", "time"]
}
]

with requests_mock.Mocker() as m:
m.register_uri(requests_mock.POST,
"http://localhost:8086/db/db/series")

cli = DataFrameClient(database='db')
cli.write_points({"foo": dataframe})

self.assertListEqual(json.loads(m.last_request.body), points)

def test_write_points_from_dataframe_in_batches(self):
now = pd.Timestamp('1970-01-01 00:00+00:00')
dataframe = pd.DataFrame(data=[["1", 1, 1.0], ["2", 2, 2.0]],
Expand Down