GitBook: [master] 2 pages modified

docs/technical-support.md

@@ -14,7 +14,7 @@ Example of the issue:
 
 To load configuration parameters, Airbyte must first `docker pull` the connector's image, which may be many hundreds of megabytes. Under poor connectivity conditions, the request to pull the image may take a very long time or time out. More context on this issue can be found [here](https://github.com/airbytehq/airbyte/issues/1462). If your internet speed is less than 30mbps down or are running bandwidth-consuming workloads concurrently with Airbyte, you may encounter this issue. Run a [speed test](https://fast.com/) to verify your internet speed.
 
-One workaround is to manually pull the latest version of every connector you'll use then resetting Airbyte. Note that this will remove any configured connections, sources, or destinations you currently have in Airbyte. To do this: 
+One workaround is to manually pull the latest version of every connector you'll use then resetting Airbyte. Note that this will remove any configured connections, sources, or destinations you currently have in Airbyte. To do this:
 
 1. Decide which connectors you'd like to use. For this example let's say you want the Postgres source and the Snowflake destination.
 2. Find the Docker image name of those connectors. Look [here](https://github.com/airbytehq/airbyte/blob/master/airbyte-config/init/src/main/resources/seed/source_definitions.yaml) for sources and [here](https://github.com/airbytehq/airbyte/blob/master/airbyte-config/init/src/main/resources/seed/destination_definitions.yaml) for destinations. For each of the connectors you'd like to use, copy the value of the `dockerRepository` and `dockerImageTag` fields. For example, for the Postgres source this would be `airbyte/source-postgres` and e.g `0.1.6`.

docs/tutorials/toy-connector.md

@@ -35,7 +35,7 @@ On some systems, `python` points to a Python2 installation and `python3` points
 
 Our connector will output the daily price of a stock since a given date. We'll leverage the free [IEX Cloud API](https://iexcloud.io/docs/api/) for this. We'll use Python to implement the connector because its syntax is accessible to most programmers, but the process described here can be applied to any language.
 
-Here's the outline of what we'll do to build our connector: 
+Here's the outline of what we'll do to build our connector:
 
 1. Use the Airbyte connector template to bootstrap the connector package
 2. Implement the methods required by the Airbyte Specification for our connector: 
@@ -77,7 +77,7 @@ $ npm install
 $ npm run generate
 ```
 
-We'll select the generic template and call the connector `stock-ticker-api`: 
+We'll select the generic template and call the connector `stock-ticker-api`:
 
 ![](../.gitbook/assets/newsourcetutorial_plop.gif)
 
@@ -103,7 +103,7 @@ $ touch source.py
 
 #### Implement the spec operation
 
-At this stage in the tutorial, we just want to implement the `spec` operation as described in the [Airbyte Protocol](https://docs.airbyte.io/architecture/airbyte-specification#spec). This involves a couple of steps: 
+At this stage in the tutorial, we just want to implement the `spec` operation as described in the [Airbyte Protocol](https://docs.airbyte.io/architecture/airbyte-specification#spec). This involves a couple of steps:
 
 1. Decide which inputs we need from the user in order to connect to the stock ticker API i.e: the connector's specification, and encode it as a JSON file.
 2. Identify when the connector has been invoked with the `spec` operation and return the specification as an `AirbyteMessage`
@@ -223,7 +223,7 @@ if __name__ == "__main__":
     main()
 ```
 
-Some notes on the above code: 
+Some notes on the above code:
 
 1. As described in the [specification](https://docs.airbyte.io/architecture/airbyte-specification#key-takeaways), Airbyte connectors are CLIs which communicate via stdout, so the output of the command is simply a JSON string formatted according to the Airbyte Specification. So to "return" a value we use `print` to output the return value to stdout.
 2. All Airbyte commands can output log messages that take the form `{"type":"LOG", "log":"message"}`, so we create a helper method `log(message)` to allow logging.
@@ -241,7 +241,7 @@ We've implemented the first command! Three more and we'll have a working connect
 
 The second command to implement is the [check operation](https://docs.airbyte.io/architecture/airbyte-specification#key-takeaways) `check --config <config_name>`, which tells the user whether a config file they gave us is correct. In our case, "correct" means they input a valid stock ticker and a correct API key like we declare via the `spec` operation.
 
-To achieve this, we'll: 
+To achieve this, we'll:
 
 1. Create valid and invalid configuration files to test the success and failure cases with our connector. We'll place config files in the `secrets/` directory which is gitignored everywhere in the Airbyte monorepo by default to avoid accidentally checking in API keys.
 2. Add a `check` method which calls the IEX Cloud API to verify if the provided token & stock ticker are correct and output the correct airbyte message.
@@ -366,7 +366,7 @@ The `discover` command, described in the [Airbyte Specification](https://docs.ai
 
 The data output by this connector will be structured in a very simple way. This connector outputs records belonging to exactly one Stream \(table\). Each record contains three Fields \(columns\): `date`, `price`, and `stock_ticker`, corresponding to the price of a stock on a given day.
 
-To implement `discover`, we'll: 
+To implement `discover`, we'll:
 
 1. Add a method `discover` in `source.py` which outputs the Catalog. To better understand what a catalog is, check out our [Beginner's Guide to the AirbyteCatalog](beginners-guide-to-catalog.md).
 2. Extend the arguments parser to use detect the `discover --config <config_path>` command and call the `discover` method.
@@ -961,7 +961,7 @@ That's it! We've created a fully functioning connector. Now let's get to the exc
 
 ### Use the connector in the Airbyte UI
 
-Let's recap what we've achieved so far: 
+Let's recap what we've achieved so far:
 
 1. Implemented a connector
 2. Packaged it in a Docker image
@@ -1016,23 +1016,23 @@ Then on the admin page, click "New Connector":
 
 ![](../.gitbook/assets/newsourcetutorial_admin_page.png)
 
-On the modal that pops up, enter the following information then click "Add" 
+On the modal that pops up, enter the following information then click "Add"
 
 ![](../.gitbook/assets/newsourcetutorial_new_connector_modal.png)
 
-Now from the "Sources" page \(if not redirected, click "Sources" on the left panel\) , click the "New source" button. You'll be taken to the detail page for adding a new source. Choose the "Stock Ticker API" source and add the following information, then click "Set up source": 
+Now from the "Sources" page \(if not redirected, click "Sources" on the left panel\) , click the "New source" button. You'll be taken to the detail page for adding a new source. Choose the "Stock Ticker API" source and add the following information, then click "Set up source":
 
 ![](../.gitbook/assets/newsourcetutorial_source_config.png)
 
-on the following page, click the "add destination" button then "add new destination": 
+on the following page, click the "add destination" button then "add new destination":
 
 ![](../.gitbook/assets/newsourcetutorial_add_destination.png)
 
-Configure a local JSON destination as follows:  Note that we setup the output directory to `/local/tutorial_json`. When we run syncs, we'll find the output on our local filesystem in `/tmp/airbyte_local/tutorial_json`.
+Configure a local JSON destination as follows: Note that we setup the output directory to `/local/tutorial_json`. When we run syncs, we'll find the output on our local filesystem in `/tmp/airbyte_local/tutorial_json`.
 
 ![](../.gitbook/assets/newsourcetutorial_destination_config.png)
 
-Finally, setup the connection configuration: 
+Finally, setup the connection configuration:
 
 ![](../.gitbook/assets/newsourcetutorial_schema_select.png)