fixes to Kafka Connector tutorials (#16)

* fixes to Kafka Connector tutorials

Author: Chris Cho

source/tutorials/explore-change-streams.txt

@@ -40,8 +40,8 @@ Explore Change Streams
 
    .. step:: Open a Change Stream
 
-      In **ChangeStreamShell1**, create a Python script to open a change stream using
-      the PyMongo driver.
+      In **ChangeStreamShell1**, create a Python script to open a change 
+      stream using the PyMongo driver.
 
       .. code-block:: bash
          :copyable: true
@@ -62,7 +62,7 @@ Explore Change Streams
          with db.orders.watch() as stream:
              print('\nChange Stream is opened on the Tutorial1.orders namespace.  Currently watching ...\n\n')
              for change in stream:
-                 print(dumps(change, indent=2))
+                 print(dumps(change, indent = 2))
 
       Run the Python script:
 
@@ -91,7 +91,7 @@ Explore Change Streams
       After you connect successfully, you should see the following
       MongoDB shell prompt:
 
-      .. code-block::
+      .. code-block:: none
          :copyable: false
 
          rs0 [direct: primary] test>
@@ -168,11 +168,11 @@ Explore Change Streams
          from bson.json_util import dumps
          client = pymongo.MongoClient('mongodb://mongo1')
          db = client.get_database(name='Tutorial1')
-         pipeline = [ { "$match": { "$and": [ { "fullDocument.type":"temp" }, { "fullDocument.value":{ "$gte":100 } } ] } } ]
+         pipeline = [ { "$match": { "$and": [ { "fullDocument.type": "temp" }, { "fullDocument.value": { "$gte": 100 } } ] } } ]
          with db.sensors.watch(pipeline=pipeline) as stream:
              print('\nChange Stream is opened on the Tutorial1.sensors namespace.  Currently watching for values > 100...\n\n')
              for change in stream:
-                 print(dumps(change, indent=2))
+                 print(dumps(change, indent = 2))
 
       Run the Python script:
 
@@ -205,15 +205,15 @@ Explore Change Streams
       .. code-block:: json
          :copyable: false
 
-         [ { "$match": { "$and": [ { "fullDocument.type":"temp" }, { "fullDocument.value":{ "$gte":100 } } ] } } ]
+         [ { "$match": { "$and": [ { "fullDocument.type": "temp" }, { "fullDocument.value": { "$gte": 100 } } ] } } ]
 
       Try inserting the following documents in in **ChangeStreamShell2** to verify the
       change stream only produces events when the documents match the filter:
 
       .. code-block:: javascript
 
-         db.sensors.insertOne( { 'type' : 'temp', 'value':99 } )
-         db.sensors.insertOne( { 'type' : 'pressure', 'value':22 } )
+         db.sensors.insertOne( { 'type' : 'temp', 'value': 99 } )
+         db.sensors.insertOne( { 'type' : 'pressure', 'value': 22 } )
 
    .. step:: (Optional) Stop the Docker Containers
 

source/tutorials/migrate-time-series.txt

@@ -18,10 +18,6 @@ Time series collections efficiently store time series data. Time series
 data consists of measurements taken at time intervals, metadata that describes
 the measurement, and the time of the measurement.
 
-over a period of time. Time series data consists of measurement data collected
-over time, metadata that describes the measurement, and the time of the
-measurement.
-
 To convert data from a MongoDB collection to a time series collection using
 the connector, you need to perform the following tasks:
 
@@ -33,8 +29,8 @@ the connector, you need to perform the following tasks:
 
 In this tutorial, you perform these preceding tasks to migrate stock data
 from a collection to a time series collection. The time series collection
-stores the data more efficiently and retains the ability to analyze stock
-performance over time using aggregation operators.
+stores and indexes the data more efficiently and retains the ability to analyze
+stock performance over time using aggregation operators.
 
 .. important:: Apple M1 incompatibility
 

source/tutorials/replicate-with-cdc.txt

@@ -251,7 +251,7 @@ Replicate Data with a CDC Handler
       .. code-block:: json
 
          use CDCTutorial
-         db.Source.insert({ proclaim: "Hello World!" });
+         db.Source.insertOne({ proclaim: "Hello World!" });
 
       Once MongoDB completes the insert command, you should receive an
       acknowledgment that resembles the following text:

source/tutorials/sink-connector.txt

@@ -27,23 +27,23 @@ Get Started with the MongoDB Kafka Sink Connector
       Create an interactive shell session on the tutorial Docker Container
       using the following command:
 
-      .. code-block::
+      .. code-block:: bash
          :copyable: true
 
          docker run --rm --name SinkTutorialShell --network mongodb-kafka-base_localnet -it robwma/mongokafkatutorial:latest bash
 
       Create a source configuration file called ``simplesink.json`` with
       the following command:
 
-      .. code-block::
+      .. code-block:: bash
          :copyable: true
 
          nano simplesink.json
 
       Paste the following configuration information into the file and save
       your changes:
 
-      .. code-block::
+      .. code-block:: json
          :copyable: true
          :emphasize-lines: 7-9
 
@@ -70,7 +70,7 @@ Get Started with the MongoDB Kafka Sink Connector
       Run the following command in the shell to start the sink connector
       using the configuration file you created:
 
-      .. code-block::
+      .. code-block:: bash
          :copyable: true
 
          cx simplesink.json
@@ -116,8 +116,8 @@ Get Started with the MongoDB Kafka Sink Connector
 
    .. step:: Write Data to a Kafka Topic
 
-      In the same shell, create a Python script to open a change stream using
-      the PyMongo driver.
+      In the same shell, create a Python script to write data to a Kafka
+      topic.
 
       .. code-block:: bash
          :copyable: true
@@ -126,18 +126,18 @@ Get Started with the MongoDB Kafka Sink Connector
 
       Paste the following code into the file and save your changes:
 
-      .. code-block::
+      .. code-block:: python
          :copyable: true
 
          from kafka import KafkaProducer
          import json
          from json import dumps
 
-         p = KafkaProducer(bootstrap_servers=['broker:29092'],value_serializer=lambda x:dumps(x).encode('utf-8'))
+         p = KafkaProducer(bootstrap_servers = ['broker:29092'], value_serializer = lambda x:dumps(x).encode('utf-8'))
 
-         data={'name':'roscoe'}
+         data = {'name': 'roscoe'}
 
-         p.send('Tutorial2.pets', value=data)
+         p.send('Tutorial2.pets', value = data)
 
          p.flush()
 
@@ -153,31 +153,31 @@ Get Started with the MongoDB Kafka Sink Connector
       In the same shell, connect to MongoDB using ``mongosh``, the MongoDB
       shell by running the following command:
 
-      .. code-block::
+      .. code-block:: bash
          :copyable: true
 
          mongosh "mongodb://mongo1"
 
       After you connect successfully, you should see the following
       MongoDB shell prompt:
 
-      .. code-block::
+      .. code-block:: none
          :copyable: false
 
          rs0 [direct: primary] test>
 
       At the prompt, type the following commands to retrieve all the
       documents in the ``Tutorial2.pets`` MongoDB namespace:
 
-      .. code-block::
+      .. code-block:: javascript
          :copyable: true
 
          use Tutorial2
          db.pets.find()
 
       You should see the following document returned as the result:
 
-      .. code-block::
+      .. code-block:: json
          :copyable: false
 
          { _id: ObjectId("62659..."), name: 'roscoe' }

source/tutorials/source-connector.txt

@@ -102,7 +102,7 @@ Get Started with the MongoDB Kafka Source Connector
       In the same shell, connect to MongoDB using ``mongosh``, the MongoDB
       shell by running the following command:
 
-      .. code-block:: shell
+      .. code-block:: bash
 
          mongosh "mongodb://mongo1"
 
@@ -155,7 +155,7 @@ Get Started with the MongoDB Kafka Source Connector
       Confirm the content of data on the new Kafka topic by running the
       following command:
 
-      .. code-block::
+      .. code-block:: bash
 
          kc Tutorial1.orders
 
@@ -185,7 +185,7 @@ Get Started with the MongoDB Kafka Source Connector
       ``payload`` that includes the ``fullDocument`` data as highlighted in
       the following formatted JSON document:
 
-      .. code-block::
+      .. code-block:: json
          :copyable: false
          :emphasize-lines: 12-17
 
@@ -225,7 +225,7 @@ Get Started with the MongoDB Kafka Source Connector
 
       Stop the connector using the following command:
 
-      .. code-block::
+      .. code-block:: bash
 
          del mongo-simple-source
 
@@ -249,7 +249,7 @@ Get Started with the MongoDB Kafka Source Connector
       Remove the existing configuration, add the following configuration,
       and save the file:
 
-      .. code-block::
+      .. code-block:: json
 
          {
            "name": "mongo-simple-source",
@@ -271,28 +271,28 @@ Get Started with the MongoDB Kafka Source Connector
 
       Connect to MongoDB using ``mongosh`` using the following command:
 
-      .. code-block:: shell
+      .. code-block:: bash
 
          mongosh "mongodb://mongo1"
 
       At the prompt, type the following commands to insert a new document:
 
-      .. code-block::
+      .. code-block:: bash
 
          use Tutorial1
          db.orders.insertOne( { 'order_id' : 2, 'item' : 'oatmeal' } )
 
       Confirm the content of data on the new Kafka topic by running the
       following command:
 
-      .. code-block::
+      .. code-block:: bash
 
          kc Tutorial1.orders
 
       The ``payload`` field in the "Value" document should contain only the
       following document data:
 
-      .. code-block::
+      .. code-block:: json
          :copyable: false
 
          {"_id": {"$oid": "626565..."}, "order_id": 2, "item": "oatmeal"}"}

source/tutorials/tutorial-setup.txt

@@ -38,6 +38,14 @@ Set Up Your Development Environment with Docker
       contains helper scripts to simplify the commands you need to run in
       the tutorials.
 
+      Log into Docker on the command line, providing your credentials when
+      prompted, by running the following command:
+
+      .. code-block:: bash
+         :copyable: true
+
+         docker login
+
       Run the following command in your terminal to download the image from
       Docker Hub: