feat: Added possibility to use datetime nanoseconds precision by pandas.Timestamp

CHANGELOG.md

@@ -2,7 +2,8 @@
 
 ### Features
 1. [#136](https://github.com/influxdata/influxdb-client-python/pull/136): Allows users to skip of verifying SSL certificate
-1. [#143](https://github.com/influxdata/influxdb-client-python/pull/143): Skip of verifying SSL certificate could be configured via config file or environment properties  
+1. [#143](https://github.com/influxdata/influxdb-client-python/pull/143): Skip of verifying SSL certificate could be configured via config file or environment properties
+1. [#141](https://github.com/influxdata/influxdb-client-python/pull/141): Added possibility to use datetime nanoseconds precision by `pandas.Timestamp`  
 
 ## 1.9.0 [2020-07-17]
 

README.rst

@@ -899,10 +899,76 @@ The following forward compatible APIs are available:
 
 For detail info see `InfluxDB 1.8 example <examples/influxdb_18_example.py>`_.
 
+Nanosecond precision
+^^^^^^^^^^^^^^^^^^^^
+
+The Python's `datetime <https://docs.python.org/3/library/datetime.html>`_ doesn't support precision with nanoseconds
+so the library during writes and queries ignores everything after microseconds.
+
+If you would like to use ``datetime`` with nanosecond precision you should use
+`pandas.Timestamp <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Timestamp.html#pandas.Timestamp>`_
+that is replacement for python ``datetime.datetime`` object and also you should set a proper ``DateTimeHelper`` to the client.
+
+* sources - `nanosecond_precision.py <https://github.com/influxdata/influxdb-client-python/blob/master/examples/nanosecond_precision.py>`_
+
+.. code-block:: python
+
+    from influxdb_client import Point, InfluxDBClient
+    from influxdb_client.client.util.date_utils_pandas import PandasDateTimeHelper
+    from influxdb_client.client.write_api import SYNCHRONOUS
+
+    """
+    Set PandasDate helper which supports nanoseconds.
+    """
+    import influxdb_client.client.util.date_utils as date_utils
+
+    date_utils.date_helper = PandasDateTimeHelper()
+
+    """
+    Prepare client.
+    """
+    client = InfluxDBClient(url="http://localhost:9999", token="my-token", org="my-org")
+
+    write_api = client.write_api(write_options=SYNCHRONOUS)
+    query_api = client.query_api()
+
+    """
+    Prepare data
+    """
+
+    point = Point("h2o_feet") \
+        .field("water_level", 10) \
+        .tag("location", "pacific") \
+        .time('1996-02-25T21:20:00.001001231Z')
+
+    print(f'Time serialized with nanosecond precision: {point.to_line_protocol()}')
+    print()
+
+    write_api.write(bucket="my-bucket", record=point)
+
+    """
+    Query: using Stream
+    """
+    query = '''
+    from(bucket:"my-bucket")
+            |> range(start: 0, stop: now())
+            |> filter(fn: (r) => r._measurement == "h2o_feet")
+    '''
+    records = query_api.query_stream(query)
+
+    for record in records:
+        print(f'Temperature in {record["location"]} is {record["_value"]} at time: {record["_time"]}')
+
+    """
+    Close client
+    """
+    client.__del__()
+
+
 Local tests
 -----------
 
-.. code-block:: python
+.. code-block:: console
 
     # start/restart InfluxDB2 on local machine using docker
     ./scripts/influxdb-restart.sh

examples/nanosecond_precision.py

@@ -0,0 +1,50 @@
+from influxdb_client import Point, InfluxDBClient
+from influxdb_client.client.util.date_utils_pandas import PandasDateTimeHelper
+from influxdb_client.client.write_api import SYNCHRONOUS
+
+"""
+Set PandasDate helper which supports nanoseconds.
+"""
+import influxdb_client.client.util.date_utils as date_utils
+
+date_utils.date_helper = PandasDateTimeHelper()
+
+"""
+Prepare client.
+"""
+client = InfluxDBClient(url="http://localhost:9999", token="my-token", org="my-org")
+
+write_api = client.write_api(write_options=SYNCHRONOUS)
+query_api = client.query_api()
+
+"""
+Prepare data
+"""
+
+point = Point("h2o_feet") \
+    .field("water_level", 10) \
+    .tag("location", "pacific") \
+    .time('1996-02-25T21:20:00.001001231Z')
+
+print(f'Time serialized with nanosecond precision: {point.to_line_protocol()}')
+print()
+
+write_api.write(bucket="my-bucket", record=point)
+
+"""
+Query: using Stream
+"""
+query = '''
+from(bucket:"my-bucket")
+        |> range(start: 0, stop: now())
+        |> filter(fn: (r) => r._measurement == "h2o_feet")
+'''
+records = query_api.query_stream(query)
+
+for record in records:
+    print(f'Temperature in {record["location"]} is {record["_value"]} at time: {record["_time"]}')
+
+"""
+Close client
+"""
+client.__del__()

influxdb_client/client/flux_csv_parser.py

@@ -9,7 +9,7 @@
 
 from urllib3 import HTTPResponse
 
-from influxdb_client.client.date_utils import get_date_parse_function
+from influxdb_client.client.util.date_utils import get_date_helper
 from influxdb_client.client.flux_table import FluxTable, FluxColumn, FluxRecord
 
 
@@ -208,10 +208,7 @@ def _to_value(self, str_val, column):
             return base64.b64decode(str_val)
 
         if "dateTime:RFC3339" == column.data_type or "dateTime:RFC3339Nano" == column.data_type:
-            # todo nanosecods precision
-            # return str_val
-            return get_date_parse_function()(str_val)
-            # return timestamp_parser(str_val)
+            return get_date_helper().parse_date(str_val)
 
         if "duration" == column.data_type:
             # todo better type ?

influxdb_client/client/util/__init__.py

@@ -0,0 +1 @@
+"""Utils package."""

influxdb_client/client/util/date_utils.py

@@ -0,0 +1,49 @@
+"""Utils to get right Date parsing function."""
+
+from dateutil import parser
+
+date_helper = None
+
+
+class DateHelper:
+    """DateHelper to groups different implementations of date operations."""
+
+    def parse_date(self, date_string: str):
+        """
+        Parse string into Date or Timestamp.
+
+        :return: Returns a :class:`datetime.datetime` object or compliant implementation
+                 like :class:`class 'pandas._libs.tslibs.timestamps.Timestamp`
+        """
+        pass
+
+    def to_nanoseconds(self, delta):
+        """
+        Get number of nanoseconds in timedelta.
+
+        Solution comes from v1 client. Thx.
+        https://github.com/influxdata/influxdb-python/pull/811
+        """
+        nanoseconds_in_days = delta.days * 86400 * 10 ** 9
+        nanoseconds_in_seconds = delta.seconds * 10 ** 9
+        nanoseconds_in_micros = delta.microseconds * 10 ** 3
+
+        return nanoseconds_in_days + nanoseconds_in_seconds + nanoseconds_in_micros
+
+
+def get_date_helper() -> DateHelper:
+    """
+    Return DateHelper with proper implementation.
+
+    If there is a 'ciso8601' than use 'ciso8601.parse_datetime' else use 'dateutil.parse'.
+    """
+    global date_helper
+    if date_helper is None:
+        date_helper = DateHelper()
+        try:
+            import ciso8601
+            date_helper.parse_date = ciso8601.parse_datetime
+        except ModuleNotFoundError:
+            date_helper.parse_date = parser.parse
+
+    return date_helper

influxdb_client/client/util/date_utils_pandas.py

@@ -0,0 +1,15 @@
+"""Pandas date utils."""
+from influxdb_client.client.util.date_utils import DateHelper
+from influxdb_client.extras import pd
+
+
+class PandasDateTimeHelper(DateHelper):
+    """DateHelper that use Pandas library with nanosecond precision."""
+
+    def parse_date(self, date_string: str):
+        """Parse date string into `class 'pandas._libs.tslibs.timestamps.Timestamp`."""
+        return pd.to_datetime(date_string)
+
+    def to_nanoseconds(self, delta):
+        """Get number of nanoseconds with nanos precision."""
+        return super().to_nanoseconds(delta) + (delta.nanoseconds if hasattr(delta, 'nanoseconds') else 0)

influxdb_client/client/write/point.py

@@ -10,7 +10,7 @@
 from pytz import UTC
 from six import iteritems
 
-from influxdb_client.client.date_utils import get_date_parse_function
+from influxdb_client.client.util.date_utils import get_date_helper
 from influxdb_client.domain.write_precision import WritePrecision
 
 EPOCH = UTC.localize(datetime.utcfromtimestamp(0))
@@ -164,24 +164,13 @@ def _escape_string(value):
     return str(value).translate(_ESCAPE_STRING)
 
 
-def _to_nanoseconds(delta):
-    """
-    Solution comes from v1 client. Thx.
-
-    https://github.com/influxdata/influxdb-python/pull/811
-    """
-    nanoseconds_in_days = delta.days * 86400 * 10 ** 9
-    nanoseconds_in_seconds = delta.seconds * 10 ** 9
-    nanoseconds_in_micros = delta.microseconds * 10 ** 3
-    return nanoseconds_in_days + nanoseconds_in_seconds + nanoseconds_in_micros
-
-
 def _convert_timestamp(timestamp, precision=DEFAULT_WRITE_PRECISION):
+    date_helper = get_date_helper()
     if isinstance(timestamp, Integral):
         return timestamp  # assume precision is correct if timestamp is int
 
     if isinstance(timestamp, str):
-        timestamp = get_date_parse_function()(timestamp)
+        timestamp = date_helper.parse_date(timestamp)
 
     if isinstance(timestamp, timedelta) or isinstance(timestamp, datetime):
 
@@ -192,7 +181,7 @@ def _convert_timestamp(timestamp, precision=DEFAULT_WRITE_PRECISION):
                 timestamp = timestamp.astimezone(UTC)
             timestamp = timestamp - EPOCH
 
-        ns = _to_nanoseconds(timestamp)
+        ns = date_helper.to_nanoseconds(timestamp)
 
         if precision is None or precision == WritePrecision.NS:
             return ns

tests/test_PandasDateTimeHelper.py

@@ -0,0 +1,35 @@
+import unittest
+from datetime import datetime, timedelta
+
+from pytz import UTC
+
+from influxdb_client.client.util.date_utils_pandas import PandasDateTimeHelper
+
+
+class PandasDateTimeHelperTest(unittest.TestCase):
+
+    def setUp(self) -> None:
+        self.helper = PandasDateTimeHelper()
+
+    def test_parse_date(self):
+        date = self.helper.parse_date('2020-08-07T06:21:57.331249158Z')
+
+        self.assertEqual(date.year, 2020)
+        self.assertEqual(date.month, 8)
+        self.assertEqual(date.day, 7)
+        self.assertEqual(date.hour, 6)
+        self.assertEqual(date.minute, 21)
+        self.assertEqual(date.second, 57)
+        self.assertEqual(date.microsecond, 331249)
+        self.assertEqual(date.nanosecond, 158)
+
+    def test_to_nanoseconds(self):
+        date = self.helper.parse_date('2020-08-07T06:21:57.331249158Z')
+        nanoseconds = self.helper.to_nanoseconds(date - UTC.localize(datetime.utcfromtimestamp(0)))
+
+        self.assertEqual(nanoseconds, 1596781317331249158)
+
+    def test_to_nanoseconds_buildin_timedelta(self):
+        nanoseconds = self.helper.to_nanoseconds(timedelta(days=1))
+
+        self.assertEqual(nanoseconds, 86400000000000)

tests/test_WriteApi.py

@@ -383,6 +383,42 @@ def test_check_write_permission_by_empty_data(self):
 
         client.__del__()
 
+    def test_write_query_data_nanoseconds(self):
+
+        from influxdb_client.client.util.date_utils_pandas import PandasDateTimeHelper
+        import influxdb_client.client.util.date_utils as date_utils
+
+        date_utils.date_helper = PandasDateTimeHelper()
+
+        bucket = self.create_test_bucket()
+
+        point = Point("h2o_feet") \
+            .field("water_level", 155) \
+            .tag("location", "creek level")\
+            .time('1996-02-25T21:20:00.001001231Z')
+
+        self.write_client.write(bucket.name, self.org, [point])
+
+        flux_result = self.client.query_api().query(
+            f'from(bucket:"{bucket.name}") |> range(start: 1970-01-01T00:00:00.000000001Z)')
+        self.assertEqual(1, len(flux_result))
+
+        record = flux_result[0].records[0]
+
+        self.assertEqual(self.id_tag, record["id"])
+        self.assertEqual(record["_value"], 155)
+        self.assertEqual(record["location"], "creek level")
+        self.assertEqual(record["_time"].year, 1996)
+        self.assertEqual(record["_time"].month, 2)
+        self.assertEqual(record["_time"].day, 25)
+        self.assertEqual(record["_time"].hour, 21)
+        self.assertEqual(record["_time"].minute, 20)
+        self.assertEqual(record["_time"].second, 00)
+        self.assertEqual(record["_time"].microsecond, 1001)
+        self.assertEqual(record["_time"].nanosecond, 231)
+
+        date_utils.date_helper = None
+
 
 class AsynchronousWriteTest(BaseTest):