docs: add more examples to garf-executors library

Author: AndreyMarkinPPC

docs/usage/api-executor.md

@@ -1,68 +1,72 @@
-# Combine fetching and saving with `ApiQueryExecutor`
+#ApiExecutor
+
+If your job is to execute query and write it to local/remote storage you can use `ApiQueryExecutor` to do it easily.
 
 ## Install
 
 Ensure that `garf-executors` library is installed:
 
-```
+```bash
 pip install garf-executors
 ```
+## Run
 
-## Initialize
-
-If your job is to execute query and write it to local/remote storage you can use `ApiQueryExecutor` to do it easily.
-> When reading query from file `ApiQueryExecutor` will use query file name as a name for output file/table.
-/// tab | Python
-```python
-from garf_core.fetchers import FakeApiReportFetcher
-from garf_executors import api_executor
-from garf_io import reader
+Let's take an example of working with [YouTube Data API fetcher](../fetchers/youtube-data-api.md) to get some stats on YouTube video.
 
+!!! important
+    Make sure that corresponding library for interacting with YouTube Data API is installed
 
-# initialize query_executor to fetch report and store them in local/remote storage
-fake_report_fetcher = FakeApiReportFetcher(data=[{'campaign': {'id': 1}}])
+    ```bash
+    pip install garf_youtube_data_api
+    ```
 
-query_executor = api_executor.ApiQueryExecutor(fetcher=fake_report_fetcher)
+/// tab | bash
 
-context = api_executor.ApiExecutionContext(writer='csv')
-```
-///
+```bash
 
-## Run
+echo "
+SELECT
+  id,
+  snippet.publishedAt AS published_at,
+  snippet.title AS title
+FROM videos" > query.sql
 
-/// tab | bash
 
-```
-garf <QUERIES> --source <API_SOURCE> \
-  --output <OUTPUT_TYPE> \
-  --source.params1=<VALUE>
+garf query.sql --source youtube_data_api \
+  --output console \
+  --source.ids=VIDEO_ID
 ```
 
 where
 
-* `<QUERIES>`- local or remote path(s) to files with queries.
-* `<API_SOURCE>`- type of API to use. Based on that the appropriate report fetcher will be initialized.
-* `<OUTPUT_TYPE>` - output supported by [`garf-io` library](../garf_io/README.md).
-
-If your report fetcher requires additional parameters you can pass them via key value pairs under `--source.` argument, i.e.`--source.regionCode='US'` - to get data only from *US*.
-> Concrete `--source` parameters are dependent on a particular report fetcher and should be looked up in a documentation for this fetcher.
+* `query` - local or remote path(s) to files with queries.
+* `source`- type of API to use. Based on that the appropriate report fetcher will be initialized.
+* `output` - output supported by [`garf-io` library](https://google.github.io/garf/usage/writers/).
 
 ///
 /// tab | Python
 ```python
-query_text = "SELECT campaign.id AS campaign_id, FROM campaign"
+from garf_executors import api_executor
+
+
 
-# execute query and save results to `campaign.csv`
-query_executor.execute(query=query_text, title="campaign", context=context)
+query_executor = api_executor.ApiQueryExecutor.from_fetcher_alias(
+  'youtube-data-api'
+)
+context = api_executor.ApiExecutionContext(writer='csv')
 
-# execute query from file and save to results to `query.csv`
-reader_client = reader.FileReader()
-query_path="path/to/query.sql"
+query_text = """
+SELECT
+  id,
+  snippet.publishedAt AS published_at,
+  snippet.title AS title
+FROM videos
+"""
 
 query_executor.execute(
-    query=reader_client.read(query_path),
-    title=query_path,
-    context=context
+  query=query_text,
+  title="query",
+  context=context
 )
 ```
 ///

docs/usage/bq-executor.md

@@ -1,10 +1,12 @@
 # BigQuery Executor
 
+`BigQueryExecutor` allows you to execute SQL code in BigQuery.
+
 ## Install
 
 Ensure that `garf-executors` library is installed with BigQuery support:
 
-```
+```bash
 pip install garf-executors[bq]
 ```
 
@@ -13,15 +15,15 @@ pip install garf-executors[bq]
 After `garf-executors` is installed you can use `garf` utility to perform fetching.
 
 /// tab | bash
-```
+```bash
 garf <QUERIES> --source bq \
-  --output <OUTPUT_TYPE> \
-  --source.project_id=YOUR_GCP_PROJECT
+  --output csv \
+  --source.project_id=MY_PROJECT
 ```
 where
 
-* `<QUERIES>`- local or remote path(s) to files with queries.
-* `<OUTPUT_TYPE>` - output supported by [`garf-io` library](../garf_io/README.md).
+* `query`- local or remote path(s) to files with queries.
+* `output` - output supported by [`garf-io` library](../garf_io/README.md).
 ///
 
 /// tab | Python