Fix: verified sources tests

sources/airtable/README.md

@@ -67,7 +67,7 @@ to the
 1. You're now ready to run the pipeline! To get started, run the following command:
 
    ```bash
-   python3 airtable_pipeline.py
+   python airtable_pipeline.py
    ```
 
 1. Once the pipeline has finished running, you can verify that everything loaded correctly by using

sources/airtable/__init__.py

@@ -1,13 +1,11 @@
 """Source that loads tables form Airtable.
 Supports whitelisting of tables or loading of all tables from a specified base.
 """
-from typing import Optional, Iterable, Iterator, List, Dict, Any
+from typing import Any, Dict, Iterable, Iterator, List, Optional
 
 import dlt
-from dlt.sources import DltResource
-from dlt.common.typing import TDataItem
-
 import pyairtable
+from dlt.sources import DltResource
 
 
 @dlt.source
@@ -19,9 +17,13 @@ def airtable_source(
     """
     Represents tables for a single Airtable base.
     Args:
-        base_id (str): The id of the base. Obtain it e.g. from the URL in your webbrowser. It starts with "app". See https://support.airtable.com/docs/finding-airtable-ids
-        table_names (Optional[List[str]]): A list of table IDs or table names to load. Unless specified otherwise, all tables in the schema are loaded.  Names are freely user-defined. IDs start with "tbl". See https://support.airtable.com/docs/finding-airtable-ids
-        access_token (str): The personal access token. See https://support.airtable.com/docs/creating-and-using-api-keys-and-access-tokens#personal-access-tokens-basic-actions
+        base_id (str): The id of the base. Obtain it e.g. from the URL in your webbrowser.
+            It starts with "app". See https://support.airtable.com/docs/finding-airtable-ids
+        table_names (Optional[List[str]]): A list of table IDs or table names to load.
+            Unless specified otherwise, all tables in the schema are loaded.
+            Names are freely user-defined. IDs start with "tbl". See https://support.airtable.com/docs/finding-airtable-ids
+        access_token (str): The personal access token.
+            See https://support.airtable.com/docs/creating-and-using-api-keys-and-access-tokens#personal-access-tokens-basic-actions
     """
     api = pyairtable.Api(access_token)
     all_tables_url = api.build_url(f"meta/bases/{base_id}/tables")
@@ -43,7 +45,8 @@ def airtable_resource(
     Represents a single airtable.
     Args:
         api (pyairtable.Api): The API connection object
-        base_id (str): The id of the base. Obtain it e.g. from the URL in your webbrowser. It starts with "app". See https://support.airtable.com/docs/finding-airtable-ids
+        base_id (str): The id of the base. Obtain it e.g. from the URL in your webbrowser.
+            It starts with "app". See https://support.airtable.com/docs/finding-airtable-ids
         table (Dict[str, Any]): Metadata about an airtable, does not contain the actual records
     """
     primary_key_id = table["primaryFieldId"]

sources/airtable/requirements.txt

@@ -1,2 +1,2 @@
 pyairtable~=2.1
-dlt>=0.3.17
+dlt>=0.3.25

sources/airtable_pipeline.py

@@ -1,16 +1,18 @@
-from typing import List
+from typing import List, Dict, Any
 
 import dlt
+
 from airtable import airtable_source
 
 
-def load_entire_base(base_id: str) -> None:
+def load_entire_base(base_id: str, resources_to_apply_hints: Dict[str, Any]) -> None:
     """
     Loads all tables from the specified Airtable base.
 
     Args:
         base_id (str): The id of the base. Obtain it, e.g. from the URL in your web browser.
             It starts with "app". See https://support.airtable.com/docs/finding-airtable-ids
+        resources_to_apply_hints (dict): Dict of table names and fields we want to apply hints.
 
     Note:
         - The base_id can either be passed directly or set up in ".dlt/config.toml".
@@ -23,6 +25,13 @@ def load_entire_base(base_id: str) -> None:
     # Retrieve data from Airtable using airtable_source.
     airtables = airtable_source(base_id=base_id)
 
+    # typing columns to silence warnings
+    for resource_name, field_names in resources_to_apply_hints.items():
+        for field_name in field_names:
+            airtables.resources[resource_name].apply_hints(
+                columns={field_name: {"name": field_name, "data_type": "text"}}
+            )
+
     load_info = pipeline.run(airtables, write_disposition="replace")
     print(load_info)
 
@@ -37,6 +46,7 @@ def load_select_tables_from_base_by_id(base_id: str, table_names: List[str]) ->
         table_names (List[str]): A list of table IDs or table names to load. Unless specified otherwise,
             all tables in the schema are loaded.  Names are freely user-defined. IDs start with "tbl".
             See https://support.airtable.com/docs/finding-airtable-ids
+        resources_to_apply_hints (dict): Dict of table names and fields we want to apply hints.
 
     Note:
         - Filtering by names is less reliable than filtering on IDs because names can be changed by Airtable users.
@@ -60,7 +70,7 @@ def load_select_tables_from_base_by_id(base_id: str, table_names: List[str]) ->
 
 
 def load_select_tables_from_base_by_name(
-    base_id: str, table_names: List[str], resource_name: str, field_name: str
+    base_id: str, table_names: List[str], resources_to_apply_hints: Dict[str, Any]
 ) -> None:
     """
     Loads specific table names from an Airtable base.
@@ -71,8 +81,7 @@ def load_select_tables_from_base_by_name(
         table_names (List[str]): A list of table IDs or table names to load. Unless specified otherwise,
             all tables in the schema are loaded.  Names are freely user-defined. IDs start with "tbl".
             See https://support.airtable.com/docs/finding-airtable-idss
-        resource_name (str): The table name we want to apply hints.
-        field_name (str): The table field name for which we want to apply hints.
+        resources_to_apply_hints (dict): Dict of table names and fields we want to apply hints.
 
     Note:
         - Filtering by names is less reliable than filtering on IDs because names can be changed by Airtable users.
@@ -89,16 +98,19 @@ def load_select_tables_from_base_by_name(
         table_names=table_names,
     )
 
-    airtables.resources[resource_name].apply_hints(
-        primary_key=field_name,
-        columns={field_name: {"data_type": "text"}},
-    )
+    # typing columns to silence warnings
+    for resource_name, field_names in resources_to_apply_hints.items():
+        for field_name in field_names:
+            airtables.resources[resource_name].apply_hints(
+                columns={field_name: {"name": field_name, "data_type": "text"}}
+            )
+
     load_info = pipeline.run(airtables, write_disposition="replace")
     print(load_info)
 
 
 def load_and_customize_write_disposition(
-    base_id: str, table_names: List[str], resource_name: str, field_name: str
+    base_id: str, table_names: List[str], resources_to_apply_hints: Dict[str, Any]
 ) -> None:
     """
     Loads data from a specific Airtable base's table with customized write disposition("merge") using field_name.
@@ -109,8 +121,8 @@ def load_and_customize_write_disposition(
         table_names (List[str]): A list of table IDs or table names to load. Unless specified otherwise,
             all tables in the schema are loaded.  Names are freely user-defined. IDs start with "tbl".
             See https://support.airtable.com/docs/finding-airtable-ids
-        resource_name (str): The table name we want to apply hints.
-        field_name (str): The table field name for which we want to apply hints.
+        resources_to_apply_hints (dict): Dict of table names and fields we want to apply hints.
+
 
     Note:
         - Filtering by names is less reliable than filtering on IDs because names can be changed by Airtable users.
@@ -127,31 +139,41 @@ def load_and_customize_write_disposition(
         base_id=base_id,
         table_names=table_names,
     )
-    airtables.resources[resource_name].apply_hints(
-        primary_key=field_name,
-        columns={field_name: {"data_type": "text"}},
-    )
+
+    # typing columns to silence warnings
+    for resource_name, field_names in resources_to_apply_hints.items():
+        for field_name in field_names:
+            airtables.resources[resource_name].apply_hints(
+                primary_key=field_name,
+                columns={field_name: {"name": field_name, "data_type": "text"}},
+                write_disposition="merge",
+            )
+
     load_info = pipeline.run(airtables)
     print(load_info)
 
 
 if __name__ == "__main__":
-    base_id_example = "Please set me up!"
-    table_names_example = ["Please set me up!"]
-    resource_name_to_apply_hints = "Please set me up!"
-    field_name_example = "Please set me up!"
-
-    load_entire_base(base_id_example)
-    load_select_tables_from_base_by_id(base_id_example, table_names_example)
+    load_entire_base(
+        base_id="app7RlqvdoOmJm9XR",
+        resources_to_apply_hints={
+            "🎤 Speakers": ["Name"],
+            "📆 Schedule": ["Activity"],
+            "🪑 Attendees": ["Name"],
+            "💰 Budget": ["Item"],
+        },
+    )
+    load_select_tables_from_base_by_id(
+        base_id="app7RlqvdoOmJm9XR",
+        table_names=["tblKHM5s3AujfSbAH", "tbloBrS8PnoO63aMP"],
+    )
     load_select_tables_from_base_by_name(
-        base_id_example,
-        table_names_example,
-        resource_name_to_apply_hints,
-        field_name_example,
+        "app7RlqvdoOmJm9XR",
+        table_names=["💰 Budget"],
+        resources_to_apply_hints={"💰 Budget": ["Item"]},
     )
     load_and_customize_write_disposition(
-        base_id_example,
-        table_names_example,
-        resource_name_to_apply_hints,
-        field_name_example,
+        base_id="appcChDyP0pZeC76v",
+        table_names=["tbl1sN4CpPv8pBll4"],
+        resources_to_apply_hints={"Sheet1": ["Name"]},
     )

sources/asana_dlt/README.md

@@ -16,10 +16,10 @@ Resources that can be loaded using this verified source are:
 
 ## Initialize the pipeline with Asana source
 ```bash
-dlt init asana_dlt bigquery
+dlt init asana_dlt duckdb
 ```
 
-Here, we chose BigQuery as the destination. Alternatively, you can also choose redshift, duckdb, or any of the other [destinations](https://dlthub.com/docs/dlt-ecosystem/destinations/).
+Here, we chose DuckDB as the destination. Alternatively, you can also choose redshift, bigquery, or any of the other [destinations](https://dlthub.com/docs/dlt-ecosystem/destinations/).
 
 ## Grab Asana credentials
 
@@ -29,41 +29,41 @@ To grab the Asana credentials please refer to the [full documentation here.](htt
 
 1. Open .dlt/secrets.toml.
 2. Enter the access token:
-    
+
     ```toml
     [sources.asana_dlt]
     access_token = "access_token" # please set me up!
     ```
-    
+
 3. Enter credentials for your chosen destination as per the [docs](https://dlthub.com/docs/dlt-ecosystem/destinations/).
 
 ## Run the pipeline
 
 1. Before running the pipeline, ensure that you have installed all the necessary dependencies by running the command:
-    
+
     ```bash
     pip install -r requirements.txt
-    
+
     ```
-    
+
 2. You're now ready to run the pipeline! To get started, run the following command:
-    
+
     ```bash
-    python3 asana_dlt_pipeline.py
-    
+    python asana_dlt_pipeline.py
+
     ```
-    
+
 3. Once the pipeline has finished running, you can verify that everything loaded correctly by using the following command:
-    
+
     ```bash
     dlt pipeline <pipeline_name> show
     ```
-    
-    Note that in the above command, replace `<pipeline_name>` with the name of your pipeline. For example, if you named your pipeline "asana," you would run:
-    
+
+    Note that in the above command, replace `<pipeline_name>` with the name of your pipeline. For example, if you named your pipeline "asana" you would run:
+
     ```bash
     dlt pipeline asana show
     ```
-    
+
 
 💡 To explore additional customizations for this pipeline, I recommend referring to the official Asana documentation. It provides comprehensive information and guidance on how to further customize and tailor the pipeline to suit your specific needs. You can find the Asana documentation in [Setup Guide: Asana](https://dlthub.com/docs/dlt-ecosystem/verified-sources/asana)

sources/asana_dlt/__init__.py

@@ -7,33 +7,30 @@
 """
 
 import typing as t
-from typing import Iterable, Any
+from typing import Any, Iterable
+
 import dlt
 from dlt.common.typing import TDataItem
 
+from .helpers import get_client
 from .settings import (
-    PROJECT_FIELDS,
-    USER_FIELDS,
     DEFAULT_START_DATE,
+    PROJECT_FIELDS,
     REQUEST_TIMEOUT,
     SECTION_FIELDS,
+    STORY_FIELDS,
     TAG_FIELDS,
     TASK_FIELDS,
-    STORY_FIELDS,
     TEAMS_FIELD,
+    USER_FIELDS,
     WORKSPACE_FIELDS,
 )
-from .helpers import get_client
 
 
 @dlt.source
-def asana_source(
-    access_token: str = dlt.secrets.value,
-) -> Any:  # should be Sequence[DltResource]:
+def asana_source() -> Any:  # should be Sequence[DltResource]:
     """
     The main function that runs all the other functions to fetch data from Asana.
-    Args:
-        access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
     Returns:
         Sequence[DltResource]: A sequence of DltResource objects containing the fetched data.
     """
@@ -57,6 +54,7 @@ def workspaces(
     Fetches and returns a list of workspaces from Asana.
     Args:
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Yields:
         dict: The workspace data.
     """
@@ -78,6 +76,7 @@ def projects(
     Args:
         workspace (dict): The workspace data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The project data for the given workspace.
     """
@@ -105,6 +104,7 @@ def sections(
     Args:
         project_array (list): The project data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The sections data for the given project.
     """
@@ -131,6 +131,7 @@ def tags(
     Args:
         workspace (dict): The workspace data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The tags data for the given workspace.
     """
@@ -160,6 +161,7 @@ def tasks(
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
 
         modified_at (str): The date from which to fetch modified tasks.
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Yields:
         dict: The task data for the given project.
     """
@@ -190,6 +192,7 @@ def stories(
     Args:
         task (dict): The task data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The stories data for the given task.
     """
@@ -218,6 +221,7 @@ def teams(
     Args:
         workspace (dict): The workspace data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The teams data for the given workspace.
     """
@@ -246,6 +250,7 @@ def users(
     Args:
         workspace (dict): The workspace data.
         access_token (str): The access token to authenticate the Asana API client, provided in the secrets file
+        fields (Iterable[str]): The list of workspace fields to be retrieved from Asana API.
     Returns:
         list[dict]: The user data for the given workspace.
     """

sources/asana_dlt/helpers.py

@@ -8,6 +8,8 @@ def get_client(
 ) -> AsanaClient:
     """
     Returns an Asana API client.
+    Args:
+        access_token (str): The access token to authenticate the Asana API client.
     Returns:
         AsanaClient: The Asana API client.
     """