docs: clarifying how to use an org parameter (#76)

Author: bednar

CHANGELOG.md

@@ -1,5 +1,8 @@
 ## 1.6.0 [unreleased]
 
+### Documentation
+1. [#75](https://github.com/influxdata/influxdb-client-python/issues/75): Updated docs to clarify how to use an org parameter
+
 ### Bugs
 1. [#72](https://github.com/influxdata/influxdb-client-python/issues/72): Optimize serializing data into Pandas DataFrame
 

README.rst

@@ -128,7 +128,7 @@ Please follow the `Installation`_ and then run the following:
 
    p = Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
 
-   write_api.write(bucket=bucket, org="my-org", record=p)
+   write_api.write(bucket=bucket, record=p)
 
    ## using Table structure
    tables = query_api.query('from(bucket:"my-bucket") |> range(start: -10m)')
@@ -435,7 +435,7 @@ The API also support streaming ``FluxRecord`` via `query_stream <https://github.
     _point1 = Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
     _point2 = Point("my_measurement").tag("location", "New York").field("temperature", 24.3)
 
-    write_api.write(bucket="my-bucket", org="my-org", record=[_point1, _point2])
+    write_api.write(bucket="my-bucket", record=[_point1, _point2])
 
     """
     Query: using Table structure
@@ -514,7 +514,7 @@ The ``client`` is able to retrieve data in `Pandas DataFrame <https://pandas.pyd
     _point1 = Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
     _point2 = Point("my_measurement").tag("location", "New York").field("temperature", 24.3)
 
-    write_api.write(bucket="my-bucket", org="my-org", record=[_point1, _point2])
+    write_api.write(bucket="my-bucket", record=[_point1, _point2])
 
     """
     Query: using Pandas DataFrame
@@ -624,7 +624,7 @@ If you would like to import gigabytes of data then use our multiprocessing examp
    """
    Write data into InfluxDB
    """
-   write_api.write(org="my-org", bucket="my-bucket", record=data)
+   write_api.write(bucket="my-bucket", record=data)
    write_api.__del__()
 
    """
@@ -634,7 +634,7 @@ If you would like to import gigabytes of data then use our multiprocessing examp
            ' |> range(start: 0, stop: now())' \
            ' |> filter(fn: (r) => r._measurement == "financial-analysis")' \
            ' |> max()'
-   result = client.query_api().query(org="my-org", query=query)
+   result = client.query_api().query(query=query)
 
    """
    Processing results
@@ -729,7 +729,7 @@ Efficiency write data from IOT sensor
    Create client that writes data into InfluxDB
    """
    _write_api = _db_client.write_api(write_options=WriteOptions(batch_size=1))
-   _write_api.write(org="my-org", bucket="my-bucket", record=data)
+   _write_api.write(bucket="my-bucket", record=data)
 
 
    """

examples/example.py

@@ -14,13 +14,13 @@
 p = Point("my_measurement").tag("location", "Prague").field("temperature", 25.3).time(datetime.now(), WritePrecision.MS)
 
 # write using point structure
-write_api.write(org="my-org", bucket=bucket, record=p)
+write_api.write(bucket=bucket, record=p)
 
 line_protocol = p.to_line_protocol()
 print(line_protocol)
 
 # write using line protocol string
-write_api.write(org="my-org", bucket=bucket, record=line_protocol)
+write_api.write(bucket=bucket, record=line_protocol)
 
 # using Table structure
 tables = query_api.query('from(bucket:"my-bucket") |> range(start: -1m)')

examples/import_data_set.py

@@ -70,7 +70,7 @@ def parse_row(row: OrderedDict):
 """
 Write data into InfluxDB
 """
-write_api.write(org="my-org", bucket="my-bucket", record=data)
+write_api.write(bucket="my-bucket", record=data)
 write_api.__del__()
 
 """
@@ -80,7 +80,7 @@ def parse_row(row: OrderedDict):
         ' |> range(start: 0, stop: now())' \
         ' |> filter(fn: (r) => r._measurement == "financial-analysis")' \
         ' |> max()'
-result = client.query_api().query(org="my-org", query=query)
+result = client.query_api().query(query=query)
 
 """
 Processing results

examples/import_data_set_multiprocessing.py

@@ -53,7 +53,7 @@ def run(self):
                 self.terminate()
                 self.queue.task_done()
                 break
-            self.write_api.write(org="my-org", bucket="my-bucket", record=next_task)
+            self.write_api.write(bucket="my-bucket", record=next_task)
             self.queue.task_done()
 
     def terminate(self) -> None:
@@ -200,7 +200,7 @@ def init_counter(counter, progress, queue):
         '|> drop(columns: ["_start", "_stop"])|> limit(n:10, offset: 0)'
 
 client = InfluxDBClient(url="http://localhost:9999", token="my-token", org="my-org", debug=False)
-result = client.query_api().query(org="my-org", query=query)
+result = client.query_api().query(query=query)
 
 """
 Processing results

examples/iot_sensor.py

@@ -67,7 +67,7 @@ def line_protocol(temperature):
 Create client that writes data into InfluxDB
 """
 _write_api = _db_client.write_api(write_options=WriteOptions(batch_size=1))
-_write_api.write(org="my-org", bucket="my-bucket", record=data)
+_write_api.write(bucket="my-bucket", record=data)
 
 """
 Call after terminate a script

examples/query.py

@@ -13,7 +13,7 @@
 _point1 = Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
 _point2 = Point("my_measurement").tag("location", "New York").field("temperature", 24.3)
 
-write_api.write(bucket="my-bucket", org="my-org", record=[_point1, _point2])
+write_api.write(bucket="my-bucket", record=[_point1, _point2])
 
 """
 Query: using Table structure

notebooks/stock_predictions_import_data.py

@@ -60,7 +60,7 @@ def main():
     client = InfluxDBClient(url="http://localhost:9999", token="my-token", org="my-org", debug=False)
     write_api = client.write_api(write_options=WriteOptions(batch_size=50_000, flush_interval=10_000))
 
-    write_api.write(org="my-org", bucket="my-bucket", record=data)
+    write_api.write(bucket="my-bucket", record=data)
     write_api.__del__()
 
     query = '''
@@ -72,7 +72,7 @@ def main():
             |> drop(columns: ["_start", "_stop", "table", "_field","_measurement"])
     '''
 
-    result = client.query_api().query_data_frame(org="my-org", query=query)
+    result = client.query_api().query_data_frame(query=query)
     print(result.head(100))
 
     """