docs: added an example how to use RxPY and sync batching (#202)

CHANGELOG.md

@@ -1,5 +1,8 @@
 ## 1.16.0 [unreleased]
 
+### Documentation
+1. [#202](https://github.com/influxdata/influxdb-client-python/pull/202): Added an example how to use RxPY and sync batching
+
 ## 1.15.0 [2021-03-05]
 
 ### Bug Fixes

README.rst

@@ -236,8 +236,6 @@ The data could be written as
 Batching
 """"""""
 
-.. marker-batching-start
-
 The batching is configurable by ``write_options``\ :
 
 .. list-table::
@@ -348,11 +346,9 @@ The batching is configurable by ``write_options``\ :
     _write_client.close()
     _client.close()
 
-.. marker-batching-end
 
 Default Tags
 """"""""""""
-.. marker-default-tags-start
 
 Sometimes is useful to store same information in every measurement e.g. ``hostname``, ``location``, ``customer``.
 The client is able to use static value or env property as a tag value.
@@ -415,8 +411,6 @@ Examples:
 
     self.client = InfluxDBClient.from_env_properties()
 
-.. marker-default-tags-end
-
 Asynchronous client
 """""""""""""""""""
 
@@ -458,6 +452,8 @@ Data are writes in a synchronous HTTP request.
 
    client.close()
 
+.. marker-writes-end
+
 Queries
 ^^^^^^^
 
@@ -595,6 +591,8 @@ Output:
 Examples
 ^^^^^^^^
 
+.. marker-examples-start
+
 How to efficiently import large dataset
 """""""""""""""""""""""""""""""""""""""
 
@@ -703,12 +701,8 @@ If you would like to import gigabytes of data then use our multiprocessing examp
    """
    client.close()
 
-.. marker-writes-end
-
-
 Efficiency write data from IOT sensor
 """""""""""""""""""""""""""""""""""""
-.. marker-iot-start
 
 * sources - `iot_sensor.py <https://github.com/influxdata/influxdb-client-python/blob/master/examples/iot_sensor.py>`_
 
@@ -791,8 +785,6 @@ Efficiency write data from IOT sensor
 
    input()
 
-.. marker-iot-end
-
 Connect to InfluxDB Cloud
 """""""""""""""""""""""""
 The following example demonstrate a simplest way how to write and query date with the InfluxDB Cloud.
@@ -888,6 +880,12 @@ The second example shows how to use client capabilities to realtime visualizatio
 
 .. image:: https://raw.githubusercontent.com/influxdata/influxdb-client-python/master/docs/images/realtime-result.gif
 
+Other examples
+""""""""""""""
+
+You could find all examples at GitHub: `influxdb-client-python/examples <https://github.com/influxdata/influxdb-client-python/tree/master/examples#examples>`_.
+
+.. marker-examples-end
 
 Advanced Usage
 --------------

docs/usage.rst

@@ -43,3 +43,9 @@ Both request header and body will be logged to standard output.
 .. code-block:: python
 
     _client = InfluxDBClient(url="http://localhost:8086", token="my-token", debug=True, org="my-org")
+
+Examples
+^^^^^^^^
+.. include:: ../README.rst
+  :start-after: marker-examples-start
+  :end-before: marker-examples-end

examples/README.md

@@ -0,0 +1,18 @@
+# Examples
+
+## Writes
+- [import_data_set.py](import_data_set.py) - How to import CSV file
+- [import_data_set_multiprocessing.py](import_data_set_multiprocessing.py) - How to large CSV file by Python Multiprocessing
+- [ingest_dataframe_default_tags.py](ingest_dataframe_default_tags.py) - How to ingest DataFrame with default tags
+- [iot_sensor.py](iot_sensor.py) - How to write sensor data every minute by [RxPY](https://rxpy.readthedocs.io/en/latest/)
+- [import_data_set_sync_batching.py](import_data_set_sync_batching.py) - How to use [RxPY](https://rxpy.readthedocs.io/en/latest/) to prepare batches for synchronous write into InfluxDB
+
+## Queries
+- [query.py](query.py) - How to query data into `FluxTable`s, `Stream` and `CSV`
+- [query_from_file.py](query_from_file.py) - How to use a Flux query defined in a separate file
+
+## Others
+- [influx_cloud.py](influx_cloud.py) - How to connect to InfluxDB 2 Cloud
+- [influxdb_18_example.py](influxdb_18_example.py) - How to connect to InfluxDB 1.8
+- [nanosecond_precision.py](nanosecond_precision.py) - How to use nanoseconds precision
+

examples/import_data_set_sync_batching.py

@@ -0,0 +1,68 @@
+"""
+How to use RxPY to prepare batches for synchronous write into InfluxDB
+"""
+
+from csv import DictReader
+
+import rx
+from rx import operators as ops
+
+from influxdb_client import InfluxDBClient, Point
+from influxdb_client.client.write.retry import WritesRetry
+from influxdb_client.client.write_api import SYNCHRONOUS
+
+
+def csv_to_generator(csv_file_path):
+    """
+    Parse your CSV file into generator
+    """
+    for row in DictReader(open(csv_file_path, 'r')):
+        point = Point('financial-analysis') \
+            .tag('type', 'vix-daily') \
+            .field('open', float(row['VIX Open'])) \
+            .field('high', float(row['VIX High'])) \
+            .field('low', float(row['VIX Low'])) \
+            .field('close', float(row['VIX Close'])) \
+            .time(row['Date'])
+        yield point
+
+
+"""
+Define Retry strategy - 3 attempts => 2, 4, 8
+"""
+retries = WritesRetry(total=3, backoff_factor=1, exponential_base=2)
+client = InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org', retries=retries)
+
+"""
+Use synchronous version of WriteApi to strongly depends on result of write
+"""
+write_api = client.write_api(write_options=SYNCHRONOUS)
+
+"""
+Prepare batches from generator
+"""
+batches = rx \
+    .from_iterable(csv_to_generator('vix-daily.csv')) \
+    .pipe(ops.buffer_with_count(500))
+
+
+def write_batch(batch):
+    """
+    Synchronous write
+    """
+    print(f'Writing... {len(batch)}')
+    write_api.write(bucket='my-bucket', record=batch)
+
+
+"""
+Write batches
+"""
+batches.subscribe(on_next=lambda batch: write_batch(batch),
+                  on_error=lambda ex: print(f'Unexpected error: {ex}'),
+                  on_completed=lambda: print('Import finished!'))
+
+"""
+Dispose client
+"""
+write_api.close()
+client.close()