Merge pull request #987 from dlt-hub/d#/update_pipeline_links_script

add update pipeline links script

.github/workflows/deploy_docs.yml

@@ -0,0 +1,16 @@
+name: deploy docs
+
+on:
+  schedule:
+    - cron:  '0 2 * * *'
+  workflow_dispatch:
+
+env:
+  NETLIFY_DOCS_PRODUCTION_DEPLOY_HOOK: ${{ secrets.NETLIFY_DOCS_PRODUCTION_DEPLOY_HOOK }}
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Trigger deploy hook
+        run: curl ${{ env.NETLIFY_DOCS_PRODUCTION_DEPLOY_HOOK }} -X POST

docs/examples/chess_production/chess.py

@@ -6,7 +6,6 @@
 from dlt.common.typing import StrAny, TDataItems
 from dlt.sources.helpers.requests import client
 
-
 @dlt.source
 def chess(
     chess_url: str = dlt.config.value,
@@ -60,7 +59,6 @@ def players_games(username: Any) -> Iterator[TDataItems]:
 
 MAX_PLAYERS = 5
 
-
 def load_data_with_retry(pipeline, data):
     try:
         for attempt in Retrying(
@@ -70,7 +68,9 @@ def load_data_with_retry(pipeline, data):
             reraise=True,
         ):
             with attempt:
-                logger.info(f"Running the pipeline, attempt={attempt.retry_state.attempt_number}")
+                logger.info(
+                    f"Running the pipeline, attempt={attempt.retry_state.attempt_number}"
+                )
                 load_info = pipeline.run(data)
                 logger.info(str(load_info))
 
@@ -92,7 +92,9 @@ def load_data_with_retry(pipeline, data):
     # print the information on the first load package and all jobs inside
     logger.info(f"First load package info: {load_info.load_packages[0]}")
     # print the information on the first completed job in first load package
-    logger.info(f"First completed job info: {load_info.load_packages[0].jobs['completed_jobs'][0]}")
+    logger.info(
+        f"First completed job info: {load_info.load_packages[0].jobs['completed_jobs'][0]}"
+    )
 
     # check for schema updates:
     schema_updates = [p.schema_update for p in load_info.load_packages]
@@ -150,4 +152,4 @@ def load_data_with_retry(pipeline, data):
     )
     # get data for a few famous players
     data = chess(chess_url="https://api.chess.com/pub/", max_players=MAX_PLAYERS)
-    load_data_with_retry(pipeline, data)
+    load_data_with_retry(pipeline, data)

docs/examples/connector_x_arrow/load_arrow.py

@@ -3,7 +3,6 @@
 import dlt
 from dlt.sources.credentials import ConnectionStringCredentials
 
-
 def read_sql_x(
     conn_str: ConnectionStringCredentials = dlt.secrets.value,
     query: str = dlt.config.value,
@@ -15,17 +14,16 @@ def read_sql_x(
         protocol="binary",
     )
 
-
 def genome_resource():
     # create genome resource with merge on `upid` primary key
     genome = dlt.resource(
-        name="acanthochromis_polyacanthus",
+        name="genome",
         write_disposition="merge",
-        primary_key="analysis_id",
+        primary_key="upid",
         standalone=True,
     )(read_sql_x)(
-        "mysql://[email protected]:3306/acanthochromis_polyacanthus_core_100_1",  # type: ignore[arg-type]
-        "SELECT * FROM analysis LIMIT 20",
+        "mysql://[email protected]:4497/Rfam",  # type: ignore[arg-type]
+        "SELECT * FROM genome ORDER BY created LIMIT 1000",
     )
     # add incremental on created at
     genome.apply_hints(incremental=dlt.sources.incremental("created"))

docs/examples/google_sheets/google_sheets.py

@@ -9,15 +9,13 @@
 )
 from dlt.common.typing import DictStrAny, StrAny
 
-
 def _initialize_sheets(
     credentials: Union[GcpOAuthCredentials, GcpServiceAccountCredentials]
 ) -> Any:
     # Build the service object.
     service = build("sheets", "v4", credentials=credentials.to_native_credentials())
     return service
 
-
 @dlt.source
 def google_spreadsheet(
     spreadsheet_id: str,
@@ -57,7 +55,6 @@ def get_sheet(sheet_name: str) -> Iterator[DictStrAny]:
         for name in sheet_names
     ]
 
-
 if __name__ == "__main__":
     pipeline = dlt.pipeline(destination="duckdb")
     # see example.secrets.toml to where to put credentials
@@ -70,4 +67,4 @@ def get_sheet(sheet_name: str) -> Iterator[DictStrAny]:
             sheet_names=range_names,
         )
     )
-    print(info)
+    print(info)

docs/examples/incremental_loading/zendesk.py

@@ -6,11 +6,12 @@
 from dlt.common.typing import TAnyDateTime
 from dlt.sources.helpers.requests import client
 
-
 @dlt.source(max_table_nesting=2)
 def zendesk_support(
     credentials: Dict[str, str] = dlt.secrets.value,
-    start_date: Optional[TAnyDateTime] = pendulum.datetime(year=2000, month=1, day=1),  # noqa: B008
+    start_date: Optional[TAnyDateTime] = pendulum.datetime(  # noqa: B008
+        year=2000, month=1, day=1
+    ),
     end_date: Optional[TAnyDateTime] = None,
 ):
     """
@@ -112,12 +113,11 @@ def get_pages(
         if not response_json["end_of_stream"]:
             get_url = response_json["next_page"]
 
-
 if __name__ == "__main__":
     # create dlt pipeline
     pipeline = dlt.pipeline(
         pipeline_name="zendesk", destination="duckdb", dataset_name="zendesk_data"
     )
 
     load_info = pipeline.run(zendesk_support())
-    print(load_info)
+    print(load_info)

docs/examples/nested_data/nested_data.py

@@ -13,7 +13,6 @@
 
 CHUNK_SIZE = 10000
 
-
 # You can limit how deep dlt goes when generating child tables.
 # By default, the library will descend and generate child tables
 # for all nested lists, without a limit.
@@ -82,7 +81,6 @@ def load_documents(self) -> Iterator[TDataItem]:
         while docs_slice := list(islice(cursor, CHUNK_SIZE)):
             yield map_nested_in_place(convert_mongo_objs, docs_slice)
 
-
 def convert_mongo_objs(value: Any) -> Any:
     if isinstance(value, (ObjectId, Decimal128)):
         return str(value)

docs/examples/pdf_to_weaviate/pdf_to_weaviate.py

@@ -4,7 +4,6 @@
 from dlt.destinations.impl.weaviate import weaviate_adapter
 from PyPDF2 import PdfReader
 
-
 @dlt.resource(selected=False)
 def list_files(folder_path: str):
     folder_path = os.path.abspath(folder_path)
@@ -16,7 +15,6 @@ def list_files(folder_path: str):
             "mtime": os.path.getmtime(file_path),
         }
 
-
 @dlt.transformer(primary_key="page_id", write_disposition="merge")
 def pdf_to_text(file_item, separate_pages: bool = False):
     if not separate_pages:
@@ -30,7 +28,6 @@ def pdf_to_text(file_item, separate_pages: bool = False):
         page_item["page_id"] = file_item["file_name"] + "_" + str(page_no)
         yield page_item
 
-
 pipeline = dlt.pipeline(pipeline_name="pdf_to_text", destination="weaviate")
 
 # this constructs a simple pipeline that: (1) reads files from "invoices" folder (2) filters only those ending with ".pdf"
@@ -54,4 +51,4 @@ def pdf_to_text(file_item, separate_pages: bool = False):
 
 client = weaviate.Client("http://localhost:8080")
 # get text of all the invoices in InvoiceText class we just created above
-print(client.query.get("InvoiceText", ["text", "file_name", "mtime", "page_id"]).do())
+print(client.query.get("InvoiceText", ["text", "file_name", "mtime", "page_id"]).do())

docs/examples/qdrant_zendesk/qdrant.py

@@ -10,12 +10,13 @@
 
 from dlt.common.configuration.inject import with_config
 
-
 # function from: https://github.com/dlt-hub/verified-sources/tree/master/sources/zendesk
 @dlt.source(max_table_nesting=2)
 def zendesk_support(
     credentials: Dict[str, str] = dlt.secrets.value,
-    start_date: Optional[TAnyDateTime] = pendulum.datetime(year=2000, month=1, day=1),  # noqa: B008
+    start_date: Optional[TAnyDateTime] = pendulum.datetime(  # noqa: B008
+        year=2000, month=1, day=1
+    ),
     end_date: Optional[TAnyDateTime] = None,
 ):
     """
@@ -79,15 +80,13 @@ def _parse_date_or_none(value: Optional[str]) -> Optional[pendulum.DateTime]:
         return None
     return ensure_pendulum_datetime(value)
 
-
 # modify dates to return datetime objects instead
 def _fix_date(ticket):
     ticket["updated_at"] = _parse_date_or_none(ticket["updated_at"])
     ticket["created_at"] = _parse_date_or_none(ticket["created_at"])
     ticket["due_at"] = _parse_date_or_none(ticket["due_at"])
     return ticket
 
-
 # function from: https://github.com/dlt-hub/verified-sources/tree/master/sources/zendesk
 def get_pages(
     url: str,
@@ -128,7 +127,6 @@ def get_pages(
         if not response_json["end_of_stream"]:
             get_url = response_json["next_page"]
 
-
 if __name__ == "__main__":
     # create a pipeline with an appropriate name
     pipeline = dlt.pipeline(
@@ -148,6 +146,7 @@ def get_pages(
 
     print(load_info)
 
+
     # running the Qdrant client to connect to your Qdrant database
 
     @with_config(sections=("destination", "qdrant", "credentials"))

docs/examples/transformers/pokemon.py

@@ -1,7 +1,6 @@
 import dlt
 from dlt.sources.helpers import requests
 
-
 @dlt.source(max_table_nesting=2)
 def source(pokemon_api_url: str):
     """"""
@@ -47,7 +46,6 @@ def species(pokemon_details):
 
     return (pokemon_list | pokemon, pokemon_list | pokemon | species)
 
-
 if __name__ == "__main__":
     # build duck db pipeline
     pipeline = dlt.pipeline(
@@ -56,4 +54,4 @@ def species(pokemon_details):
 
     # the pokemon_list resource does not need to be loaded
     load_info = pipeline.run(source("https://pokeapi.co/api/v2/pokemon"))
-    print(load_info)
+    print(load_info)

docs/website/docs/dlt-ecosystem/destinations/athena.md

@@ -160,4 +160,14 @@ aws_data_catalog="awsdatacatalog"
 You can choose the following file formats:
 * [parquet](../file-formats/parquet.md) is used by default
 
-------
+<!--@@@DLT_SNIPPET_START tuba::athena-->
+## Additional Setup guides
+
+- [Load data from Chess.com to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-athena)
+- [Load data from Notion to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-athena)
+- [Load data from HubSpot to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-athena)
+- [Load data from GitHub to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-athena)
+- [Load data from Google Analytics to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-athena)
+- [Load data from Google Sheets to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-athena)
+- [Load data from Stripe to AWS Athena in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-athena)
+<!--@@@DLT_SNIPPET_END tuba::athena-->

docs/website/docs/dlt-ecosystem/destinations/bigquery.md

@@ -173,3 +173,15 @@ This destination [integrates with dbt](../transformations/dbt/dbt.md) via [dbt-b
 
 ### Syncing of `dlt` state
 This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination)
+
+<!--@@@DLT_SNIPPET_START tuba::bigquery-->
+## Additional Setup guides
+
+- [Load data from Notion to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-bigquery)
+- [Load data from Google Analytics to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-bigquery)
+- [Load data from Chess.com to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-bigquery)
+- [Load data from HubSpot to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-bigquery)
+- [Load data from GitHub to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-bigquery)
+- [Load data from Google Sheets to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-bigquery)
+- [Load data from Stripe to BigQuery in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-bigquery)
+<!--@@@DLT_SNIPPET_END tuba::bigquery-->

docs/website/docs/dlt-ecosystem/destinations/databricks.md

@@ -184,3 +184,15 @@ This destination [integrates with dbt](../transformations/dbt/dbt.md) via [dbt-d
 
 ### Syncing of `dlt` state
 This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination).
+
+<!--@@@DLT_SNIPPET_START tuba::databricks-->
+## Additional Setup guides
+
+- [Load data from GitHub to Databricks in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-databricks)
+- [Load data from Notion to Databricks in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-databricks)
+- [Load data from Stripe to Databricks in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-databricks)
+- [Load data from HubSpot to Databricks in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-databricks)
+- [Load data from Google Analytics to Databricks in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-databricks)
+- [Load data from Google Sheets to Databricks in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-databricks)
+- [Load data from Chess.com to Databricks in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-databricks)
+<!--@@@DLT_SNIPPET_END tuba::databricks-->

docs/website/docs/dlt-ecosystem/destinations/duckdb.md

@@ -113,3 +113,15 @@ This destination [integrates with dbt](../transformations/dbt/dbt.md) via [dbt-d
 
 ### Syncing of `dlt` state
 This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination)
+
+<!--@@@DLT_SNIPPET_START tuba::duckdb-->
+## Additional Setup guides
+
+- [Load data from Google Analytics to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-duckdb)
+- [Load data from Google Sheets to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-duckdb)
+- [Load data from Stripe to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-duckdb)
+- [Load data from Notion to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-duckdb)
+- [Load data from Chess.com to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-duckdb)
+- [Load data from HubSpot to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-duckdb)
+- [Load data from GitHub to DuckDB in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-duckdb)
+<!--@@@DLT_SNIPPET_END tuba::duckdb-->

docs/website/docs/dlt-ecosystem/destinations/filesystem.md

@@ -234,3 +234,6 @@ You can choose the following file formats:
 ## Syncing of `dlt` state
 This destination does not support restoring the `dlt` state. You can change that by requesting the [feature](https://github.com/dlt-hub/dlt/issues/new/choose) or contributing to the core library 😄
 You can however easily [backup and restore the pipeline working folder](https://gist.github.com/rudolfix/ee6e16d8671f26ac4b9ffc915ad24b6e) - reusing the bucket and credentials used to store files.
+
+<!--@@@DLT_SNIPPET_START tuba::filesystem-->
+<!--@@@DLT_SNIPPET_END tuba::filesystem-->

docs/website/docs/dlt-ecosystem/destinations/motherduck.md

@@ -99,3 +99,6 @@ My observation is that if you write a lot of data into the database then close t
 
 ### Invalid Input Error: Initialization function "motherduck_init" from file
 Use `duckdb 0.8.1` or above.
+
+<!--@@@DLT_SNIPPET_START tuba::motherduck-->
+<!--@@@DLT_SNIPPET_END tuba::motherduck-->

docs/website/docs/dlt-ecosystem/destinations/mssql.md

@@ -110,3 +110,14 @@ destination.mssql.credentials="mssql://loader:<password>@loader.database.windows
 ### dbt support
 No dbt support yet
 
+<!--@@@DLT_SNIPPET_START tuba::mssql-->
+## Additional Setup guides
+
+- [Load data from Stripe to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-mssql)
+- [Load data from Google Analytics to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-mssql)
+- [Load data from Google Sheets to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-mssql)
+- [Load data from Chess.com to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-mssql)
+- [Load data from GitHub to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-mssql)
+- [Load data from Notion to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-mssql)
+- [Load data from HubSpot to Microsoft SQL Server in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-mssql)
+<!--@@@DLT_SNIPPET_END tuba::mssql-->

docs/website/docs/dlt-ecosystem/destinations/postgres.md

@@ -96,3 +96,15 @@ This destination [integrates with dbt](../transformations/dbt/dbt.md) via dbt-po
 
 ### Syncing of `dlt` state
 This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination)
+
+<!--@@@DLT_SNIPPET_START tuba::postgres-->
+## Additional Setup guides
+
+- [Load data from HubSpot to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/hubspot/load-data-with-python-from-hubspot-to-postgres)
+- [Load data from GitHub to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/github/load-data-with-python-from-github-to-postgres)
+- [Load data from Chess.com to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/chess/load-data-with-python-from-chess-to-postgres)
+- [Load data from Notion to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/notion/load-data-with-python-from-notion-to-postgres)
+- [Load data from Google Analytics to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/google_analytics/load-data-with-python-from-google_analytics-to-postgres)
+- [Load data from Google Sheets to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/google_sheets/load-data-with-python-from-google_sheets-to-postgres)
+- [Load data from Stripe to PostgreSQL in python with dlt](https://dlthub.com/docs/pipelines/stripe_analytics/load-data-with-python-from-stripe_analytics-to-postgres)
+<!--@@@DLT_SNIPPET_END tuba::postgres-->

docs/website/docs/dlt-ecosystem/destinations/qdrant.md

@@ -220,3 +220,6 @@ You can find the setup instructions to run Qdrant [here](https://qdrant.tech/doc
 ### Syncing of `dlt` state
 
 Qdrant destination supports syncing of the `dlt` state.
+
+<!--@@@DLT_SNIPPET_START tuba::qdrant-->
+<!--@@@DLT_SNIPPET_END tuba::qdrant-->