docs: improve README files for batch 01 (apache_hbase → gnews)

apache_hbase/README.md

@@ -6,15 +6,25 @@ This connector shows how to sync data from Apache HBase databases using Fivetran
 
 ## Requirements
 
-* [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)   
-* Operating system:
-  * Windows: 10 or later (64-bit only)
-  * macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
-  * Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
+- [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)
+- Operating system:
+  - Windows: 10 or later (64-bit only)
+  - macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
+  - Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
 
 ## Getting started
 
-Refer to the [Setup Guide](https://fivetran.com/docs/connectors/connector-sdk/setup-guide) to get started.
+Refer to the [Connector SDK Setup Guide](https://fivetran.com/docs/connectors/connector-sdk/setup-guide) to get started.
+
+To initialize a new Connector SDK project using this connector as a starting point, run:
+
+```
+fivetran init --template apache_hbase
+```
+
+`fivetran init` initializes a new Connector SDK project by setting up the project structure, configuration files, and a connector you can run immediately with `fivetran debug`. For more information on `fivetran init`, refer to the [Connector SDK `init` documentation](https://fivetran.com/docs/connector-sdk/connector-development-and-configuration/connector-sdk-commands#fivetraninit).
+
+> Note: Ensure you have updated the `configuration.json` file with the necessary parameters before running `fivetran debug`. See the [Configuration file](#configuration-file) section for details on the required configuration parameters.
 
 ## Features
 
@@ -26,18 +36,18 @@ Refer to the [Setup Guide](https://fivetran.com/docs/connectors/connector-sdk/se
 
 ## Configuration file
 
-The connector requires the following configuration parameters: 
+The connector requires the following configuration parameters:
 
-```
+```json
 {
   "hostname": "<YOUR_HBASE_HOSTNAME>",
   "port": "<YOUR_HBASE_PORT>",
-  "table_name": "<YOUR_HBASE_TABLE_NAME>", 
+  "table_name": "<YOUR_HBASE_TABLE_NAME>",
   "column_family": "<YOUR_HBASE_COLUMN_FAMILY>"
 }
 ```
 
-Note: Ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
+> Note: When submitting connector code as a [Community Connector](https://github.com/fivetran/fivetran-csdk-connectors/tree/main) in the open-source [Connector SDK repository](https://github.com/fivetran/fivetran-csdk-connectors/tree/main), ensure the `configuration.json` file has placeholder values. When adding the connector to your production repository, ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
 
 ## Requirements file
 
@@ -47,7 +57,7 @@ This connector requires the happybase library to communicate with Apache HBase:
 happybase==1.2.0
 ```
 
-Note: The `fivetran_connector_sdk:latest` and `requests:latest` packages are pre-installed in the Fivetran environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
+> Note: [Some packages](https://fivetran.com/docs/connector-sdk/technical-reference#preinstalledpackages) are pre-installed in the Connector SDK runtime environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
 
 ## Authentication
 
@@ -61,8 +71,7 @@ Refer to the `execute_query_and_upsert` function, which implements batched data
 
 ## Data handling
 
-
-The connector processes data from HBase in the following way:  
+The connector processes data from HBase in the following way:
 - Creates a connection to the HBase server using the `happybase` library.
 - Scans the specified table with a filter based on the `created_at` timestamp.
 - Decodes and transforms each row into a structured format
@@ -71,26 +80,25 @@ The connector processes data from HBase in the following way:
 
 ## Error handling
 
-The connector implements error handling at multiple levels:  
+The connector implements error handling at multiple levels:
 - Connection errors: Captured in the `create_hbase_connection` function, raising a descriptive RuntimeError
 - Data processing errors: The `execute_query_and_upsert` function uses try-except blocks to handle missing columns in row data, logging warnings and continuing execution without failing the entire sync
 
-## Tables Created
+## Tables created
 
-
-The connector creates one table:  
+The connector creates one table:
 - profile_table
 
 The schema of the created table is as follows:
 
-```
+```json
 {
     "table": "profile_table",
     "primary_key": ["id"],
     "columns": {
         "id": "STRING",
-        "created_at": "UTC_DATETIME",
-    },
+        "created_at": "UTC_DATETIME"
+    }
 }
 ```
 

apache_hive/using_pyhive/README.md

@@ -6,16 +6,26 @@ This connector shows how to fetch data from Apache Hive using the `PyHive` and `
 
 ## Requirements
 
-* [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)   
-* Operating system:
-  * Windows: 10 or later (64-bit only)
-  * macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
-  * Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
+- [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)
+- Operating system:
+  - Windows: 10 or later (64-bit only)
+  - macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
+  - Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
 
 ## Getting started
 
 Refer to the [Connector SDK setup guide](https://fivetran.com/docs/connectors/connector-sdk/setup-guide) to get started.
 
+To initialize a new Connector SDK project using this connector as a starting point, run:
+
+```
+fivetran init --template apache_hive/using_pyhive
+```
+
+`fivetran init` initializes a new Connector SDK project by setting up the project structure, configuration files, and a connector you can run immediately with `fivetran debug`. For more information on `fivetran init`, refer to the [Connector SDK `init` documentation](https://fivetran.com/docs/connector-sdk/connector-development-and-configuration/connector-sdk-commands#fivetraninit).
+
+> Note: Ensure you have updated the `configuration.json` file with the necessary parameters before running `fivetran debug`. See the [Configuration file](#configuration-file) section for details on the required configuration parameters.
+
 ## Features
 
 - Direct connection to Apache Hive data source.
@@ -26,7 +36,7 @@ Refer to the [Connector SDK setup guide](https://fivetran.com/docs/connectors/co
 
 This connector requires the following configuration parameters to establish a connection to your Hive instance:
 
-```
+```json
 {
   "hostname": "YOUR_HIVE_HOSTNAME",
   "port": "<YOUR_HIVE_PORT>",
@@ -36,7 +46,7 @@ This connector requires the following configuration parameters to establish a co
 }
 ```
 
-Note: Ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
+> Note: When submitting connector code as a [Community Connector](https://github.com/fivetran/fivetran-csdk-connectors/tree/main) in the open-source [Connector SDK repository](https://github.com/fivetran/fivetran-csdk-connectors/tree/main), ensure the `configuration.json` file has placeholder values. When adding the connector to your production repository, ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
 
 ## Requirements file
 
@@ -48,11 +58,11 @@ thrift_sasl
 sasl
 ```
 
-Note: The `fivetran_connector_sdk:latest` and `requests:latest` packages are pre-installed in the Fivetran environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
+> Note: [Some packages](https://fivetran.com/docs/connector-sdk/technical-reference#preinstalledpackages) are pre-installed in the Connector SDK runtime environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
 
 ## Authentication
 
-The connector supports `CUSTOM` authentication for Apache Hive. You need to provide:  
+The connector supports `CUSTOM` authentication for Apache Hive. You need to provide:
 - `hostname`: The address of your Hive server
 - `port`: The port number Hive is listening on (typically 10000)
 - `username`: Your Hive username
@@ -62,25 +72,25 @@ Authentication is handled in the `create_hive_connection` function.
 
 ## Data handling
 
-The connector performs the following data handling operations:  
+The connector performs the following data handling operations:
 - Fetching: Data is retrieved from Apache Hive using SQL queries with timestamp-based filtering.
 - Processing: The `process_row` function converts raw Hive data into dictionary format suitable for Fivetran.
   - Column names are extracted and mapped to their values.
-- Batching: Data is processed in configurable batches (1000 rows by default) to prevent memory overflow. 
+- Batching: Data is processed in configurable batches (1000 rows by default) to prevent memory overflow.
 - State management: The connector tracks the latest created timestamp to enable incremental syncs.
 
 ## Tables created
 
 The connector creates a table named `PEOPLE` with the following schema:
 
-```
+```json
 {
     "table": "people",
     "primary_key": ["id"],
     "columns": {
         "id": "INT",
         "created_at": "UTC_DATETIME"
-    },
+    }
 }
 ```
 

apache_hive/using_sqlalchemy/README.md

@@ -6,16 +6,26 @@ This connector demonstrates how to fetch data from Apache Hive using `SQLAlchemy
 
 ## Requirements
 
-* [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)   
-* Operating system:
-  * Windows: 10 or later (64-bit only)
-  * macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
-  * Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
+- [Supported Python versions](https://github.com/fivetran/fivetran-csdk-connectors/blob/main/README.md#requirements)
+- Operating system:
+  - Windows: 10 or later (64-bit only)
+  - macOS: 13 (Ventura) or later (Apple Silicon [arm64] or Intel [x86_64])
+  - Linux: Distributions such as Ubuntu 20.04 or later, Debian 10 or later, or Amazon Linux 2 or later (arm64 or x86_64)
 
 ## Getting started
 
 Refer to the [Connector SDK setup guide](https://fivetran.com/docs/connectors/connector-sdk/setup-guide) to get started.
 
+To initialize a new Connector SDK project using this connector as a starting point, run:
+
+```
+fivetran init --template apache_hive/using_sqlalchemy
+```
+
+`fivetran init` initializes a new Connector SDK project by setting up the project structure, configuration files, and a connector you can run immediately with `fivetran debug`. For more information on `fivetran init`, refer to the [Connector SDK `init` documentation](https://fivetran.com/docs/connector-sdk/connector-development-and-configuration/connector-sdk-commands#fivetraninit).
+
+> Note: Ensure you have updated the `configuration.json` file with the necessary parameters before running `fivetran debug`. See the [Configuration file](#configuration-file) section for details on the required configuration parameters.
+
 ## Features
 
 - Connection to Apache Hive data source using SQLAlchemy ORM.
@@ -26,16 +36,16 @@ Refer to the [Connector SDK setup guide](https://fivetran.com/docs/connectors/co
 
 This connector requires the following configuration parameters to establish a connection to your Hive instance:
 
-```
+```json
 {
   "hostname": "<YOUR_HIVE_HOSTNAME>",
   "port": "<YOUR_HIVE_PORT>",
   "username": "<YOUR_HIVE_USERNAME>",
-  "database": "<YOUR_HIVE_DATABASE>",
+  "database": "<YOUR_HIVE_DATABASE>"
 }
 ```
 
-Note: Ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
+> Note: When submitting connector code as a [Community Connector](https://github.com/fivetran/fivetran-csdk-connectors/tree/main) in the open-source [Connector SDK repository](https://github.com/fivetran/fivetran-csdk-connectors/tree/main), ensure the `configuration.json` file has placeholder values. When adding the connector to your production repository, ensure that the `configuration.json` file is not checked into version control to protect sensitive information.
 
 ## Requirements file
 
@@ -47,13 +57,14 @@ PyHive==0.7.0
 thrift_sasl
 sasl
 ```
+
 `PyHive` is required for actual dialect implementation for Hive along with the `SQLAlchemy` ORM. The `thrift_sasl` and `sasl` packages are necessary for SASL authentication, which is commonly used with Hive.
 
-Note: The `fivetran_connector_sdk:latest` and `requests:latest` packages are pre-installed in the Fivetran environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
+> Note: [Some packages](https://fivetran.com/docs/connector-sdk/technical-reference#preinstalledpackages) are pre-installed in the Connector SDK runtime environment. To avoid dependency conflicts, do not declare them in your `requirements.txt`.
 
 ## Authentication
 
-The connector supports authentication for Apache Hive through SQLAlchemy. You need to provide the following:  
+The connector supports authentication for Apache Hive through SQLAlchemy. You need to provide the following:
 - `hostname`: The address of your Hive server
 - `port`: The port number Hive is listening on (typically 10000)
 - `username`: Your Hive username
@@ -63,7 +74,7 @@ Authentication is handled in the `create_hive_connection` function.
 
 ## Data handling
 
-The connector performs the following data handling operations:  
+The connector performs the following data handling operations:
 - Fetching: Data is retrieved from Apache Hive using SQLAlchemy with raw SQL queries and stream options.
 - Processing: The `process_row` function converts raw Hive data into a dictionary format suitable for Fivetran.
   - Column names are extracted and mapped to their values.
@@ -74,17 +85,17 @@ The connector performs the following data handling operations:
 
 The connector creates a table named `PEOPLE` with the following schema:
 
-```
+```json
 {
     "table": "people",
     "primary_key": ["id"],
     "columns": {
         "id": "INT",
         "created_at": "UTC_DATETIME"
-    },
+    }
 }
 ```
 
 ## Additional considerations
 
-The examples provided are intended to help you effectively use Fivetran's Connector SDK. While we've tested the code, Fivetran cannot be held responsible for any unexpected or negative consequences that may arise from using these examples. For inquiries, please reach out to our [Support team](https://support.fivetran.com/)..
+The examples provided are intended to help you effectively use Fivetran's Connector SDK. While we've tested the code, Fivetran cannot be held responsible for any unexpected or negative consequences that may arise from using these examples. For inquiries, please reach out to our [Support team](https://support.fivetran.com/).