diff --git a/.circleci/config.yml b/.circleci/config.yml
index 244fb2f..a20989a 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -22,6 +22,16 @@ jobs:
pip install -r integration_tests/requirements.txt
mkdir -p ~/.dbt
cp integration_tests/ci/sample.profiles.yml ~/.dbt/profiles.yml
+ - run:
+ name: "Run Tests - Postgres"
+ command: |
+ . venv/bin/activate
+ echo `pwd`
+ cd integration_tests
+ dbt deps
+ dbt seed --target postgres --full-refresh
+ dbt run --target postgres --full-refresh
+ dbt test --target postgres
- run:
name: "Run Tests - Redshift"
command: |
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 178a3db..6cbdda8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,3 +1,21 @@
+# dbt_asana_source v0.6.0
+🛠 Deprecated columns fix 🛠
+## 🚨 Breaking Changes 🚨
+- As per our Release Notes for the Asana connector, this new version of the package removes deprecated columns from the Task table (https://fivetran.com/docs/applications/asana/changelog#june2021) - please refer to the June 2021 and May 2021 release notes. The following columns have been deprecated from the Task table:
+ - `assingee_status`
+ - `hearted` - the `liked` column has been added to replace hearted
+ - `num_hearts` - the `num_likes` column has been added to replace num_hearts
+Please be sure to update your queries.
+
+## 🎉 Features 🎉
+PR [#24](https://github.com/fivetran/dbt_asana_source/pull/24) introduced the following updates.
+- PostgreSQL compatibility
+- Updated README for enhanced user experience
+- Add source identifiers to give users more dynamic flexibility
+
+## Contributors
+- @fivetran-poonamagate ([#21](https://github.com/fivetran/dbt_asana_source/pull/21)).
+
# dbt_asana_source v0.5.1
## Under the Hood
- Leveraged the `{{ dbt_utils.type_timestamp() }}` macro within the staging models for all timestamp fields.
diff --git a/README.md b/README.md
index a1c443b..d6bd5f2 100644
--- a/README.md
+++ b/README.md
@@ -1,42 +1,45 @@
-[](https://opensource.org/licenses/Apache-2.0)
-# Asana
-
-This package models Asana data from [Fivetran's connector](https://fivetran.com/docs/applications/asana). It uses data in the format described by [this ERD](https://fivetran.com/docs/applications/asana#schemainformation).
-
-This package enriches your Fivetran data by doing the following:
-* Adds descriptions to tables and columns that are synced using Fivetran
-* Adds freshness tests to source data
-* Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
-* Models staging tables, which will be used in our transform package
-
-## Models
-
-This package contains staging models, designed to work simultaneously with our [Asana transform package](https://github.com/fivetran/dbt_asana). The staging models:
-* Remove any rows that are soft-deleted
-* Name columns consistently across all packages:
- * Boolean fields are prefixed with `is_` or `has_`
- * Timestamps are appended with `_at`
- * ID primary keys are prefixed with the name of the table. For example, the user table's ID column is renamed user_id.
- * Foreign keys include the table that they refer to. For example, the project table's owner ID column is renamed owner_user_id.
-
-## Installation Instructions
-Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions, or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.
-
-Include in your `packages.yml`
-
+
+
+ 
+
+ 
+
+ 
+
+ 
+
+
+# Asana Source dbt Package ([Docs](https://fivetran.github.io/dbt_asana_source/))
+# 📣 What does this dbt package do?
+- Materializes [Asana staging tables](https://fivetran.github.io/dbt_asana_source/#!/overview/asana_source/models/?g_v=1&g_e=seeds), which leverage data in the format described by [this ERD](https://fivetran.com/docs/applications/asana#schemainformation). These staging tables clean, test, and prepare your Asana data from [Fivetran's connector](https://fivetran.com/docs/applications/asana) for analysis by doing the following:
+ - Names columns for consistency across all packages and for easier analysis
+ - Removes any rows that are soft-deleted
+ - Adds freshness tests to source data
+ - Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
+- Generates a comprehensive data dictionary of your Asana data through the [dbt docs site](https://fivetran.github.io/dbt_asana_source/).
+- These tables are designed to work simultaneously with our [Asana transformation package](https://github.com/fivetran/dbt_asana).
+
+# 🎯 How do I use the dbt package?
+## Step 1: Prerequisites
+To use this dbt package, you must have the following:
+
+- At least one Fivetran Asana connector syncing data into your destination.
+- A **BigQuery**, **Snowflake**, **Redshift**, or **PostgreSQL** destination.
+
+## Step 2: Install the package
+Include the following asana_source package version in your `packages.yml` file.
+> TIP: Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions, or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.
```yaml
packages:
- package: fivetran/asana_source
- version: [">=0.5.0", "<0.6.0"]
+ version: [">=0.6.0", "<0.7.0"]
```
-## Configuration
-By default, this package will run using your target database and the `asana` schema. If this is not where your Asana data is (perhaps your Asana schema is `asana_fivetran`), add the following configuration to your `dbt_project.yml` file:
+## Step 3: Define database and schema variables
+By default, this package runs using your destination and the `asana` schema. If this is not where your Asana data is (for example, if your Asana schema is named `asana_fivetran`), add the following configuration to your root `dbt_project.yml` file:
```yml
-# dbt_project.yml
-
-...
config-version: 2
vars:
@@ -44,49 +47,67 @@ vars:
asana_database: your_database_name
asana_schema: your_schema_name
```
+## (Optional) Step 4: Additional configurations
+Expand for configurations
-To add additional columns to tasks use the pass-through column variable. This is useful for adding custom fields not already included in this package.
+### Passing Through Additional Columns
+To add additional columns to tasks use the pass-through column variable. This is useful for adding custom fields not already included in this package.
```yml
-# dbt_project.yml
-
-...
vars:
asana_source:
task_pass_through_columns: [custom_status, custom_department]
```
### Changing the Build Schema
-By default this package will build the Asana staging models within a schema titled ( + `_stg_asana`) in your target database. If this is not where you would like your Asana staging data to be written to, add the following configuration to your `dbt_project.yml` file:
+By default this package will build the Asana staging models within a schema titled ( + `_stg_asana`) in your destination. If this is not where you would like your Asana staging data to be written to, add the following configuration to your root `dbt_project.yml` file:
```yml
-# dbt_project.yml
-
-...
models:
asana_source:
+schema: my_new_schema_name # leave blank for just the target_schema
```
-## Database support
-This package is compatible with BigQuery, Snowflake, and Redshift.
+### Change the source table references
+If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:
+
+> IMPORTANT: See this project's [`dbt_project.yml`](https://github.com/fivetran/dbt_asana_source/blob/main/dbt_project.yml) variable declarations to see the expected names.
+
+```yml
+vars:
+ asana__identifier: your_table_name
+```
+
+Expand for more details
+
+Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Learn how to set up your project for orchestration through Fivetran in our [Transformations for dbt Core™ setup guides](https://fivetran.com/docs/transformations/dbt#setupguide).
+
+