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How can I access the cached results of a HttpStrea...
# replication-ask-ai
k
How can I access the cached results of a HttpStream in the HttpSubStream?
k
To access the cached results of a 
HttpStream
in the 
HttpSubStream
, you need to use the caching mechanism provided by Airbyte. Here's how it works: 1. If a request is made for the first time, the returned value will be written to disk. All requests made by the 
read_records
method will be written to the cache file. 2. When the same request is made again, instead of making another HTTP request, the result will be read from disk. It is checked whether the required request is in the cache file, and if so, the data from this file is returned. However, if the check for the request's existence in the cache file fails, a new request will be made, and its result will be added to the cache file. To enable caching, you need to override the 
use_cache
property of the 
HttpStream
class to return 
True
. Here's an example:
Copy code
python class Employees(HttpStream):    ...       @property    def use_cache(self) -> bool:    return True
For child streams, there is an 
HttpSubStream
class inheriting from 
HttpStream
and overriding the 
stream_slices
method that returns a generator of all parent entries. Here's an example:
Copy code
python class EmployeeDetails(HttpSubStream):    ...
To use caching in the parent/child relationship, perform the following steps: 1. Turn on parent stream caching by overriding the 
use_cache
property. 2. Inherit child stream class from 
HttpSubStream
class. For more details, you can refer to the [official documentation](https://docs.airbyte.com/connector-development/cdk-python/http-streams).
k
@kapa.ai Is there a default path where the results are being written to the disk?
k
Yes, there is a default path where the results are written to the disk. By default, data is written to the 
/tmp/airbyte_local
directory on the host machine running Airbyte. This applies to local destinations such as Local CSV, Local JSON, SQLite, and DuckDB. The 
destination_path
will always start with 
/local
whether it is specified by the user or not. Any directory nesting within 
/local
will be mapped onto the local mount. The local mount is mounted by Docker onto 
LOCAL_ROOT
, which means the 
/local
is substituted by 
/tmp/airbyte_local
by default. For example, if 
destination_path
is set to 
/local/cars/models
, then all data will be written to the 
/tmp/airbyte_local/cars/models
directory on the host machine. Please ensure that Docker Desktop has access to 
/tmp
(and 
/private
on a MacOS, as /tmp has a symlink that points to /private. It will not work otherwise). You can allow it with "File sharing" in 
Settings -> Resources -> File sharing -> add the one or two above folder
and hit the "Apply & restart" button. Sources: - [Local CSV](https://docs.airbyte.com/integrations/destinations/csv) - [Local JSON](https://docs.airbyte.com/integrations/destinations/local-json) - [SQLite](https://docs.airbyte.com/integrations/destinations/sqlite) - [DuckDB](https://docs.airbyte.com/integrations/destinations/duckdb) - [Browsing Output Logs](https://docs.airbyte.com/operator-guides/browsing-output-logs)
k
@kapa.ai after implementing read_records, Read_pages and fetch_next_page, get: Read 0 records from <myStream> stream
k
A message from kapa.ai
Based on the information provided, it seems like your 
read_records
, 
Read_pages
and 
fetch_next_page
implementations are not returning any records. Here are a few things you could check: 1. Check your 
read_records
implementation: Ensure that your 
read_records
method is correctly reading data from your source and yielding records. Remember, this method should output an iterable object containing records from the data source. Generators are recommended for their efficiency with regards to memory requirements. [source](https://docs.airbyte.com/connector-development/cdk-python/full-refresh-stream) 2. Check your 
Read_pages
and 
fetch_next_page
methods: Make sure these methods are correctly implemented to fetch and iterate over all the pages of data from your source. The framework works by iterating over all the partitions defined by the stream's partition router. For each partition, it submits a request to the partner API as defined by the requester, selects the records from the response, and repeats for as long as the paginator points to a next page. [source](https://docs.airbyte.com/connector-development/config-based/advanced-topics) 3. Check your stream's schema: Ensure that your stream's schema is correctly defined. This can be done either by storing the schema in the 
schemas/
directory or inline in the YAML file. [source](https://docs.airbyte.com/connector-development/config-based/tutorial/reading-data) 4. Debug your code: You can run the 
read
operation with the 
--debug
flag to print out debug information, including the outgoing request and its associated response. This can help you identify any issues with your code. [source](https://docs.airbyte.com/connector-development/config-based/tutorial/reading-data) If you've checked all of these and are still seeing "Read 0 records", it's possible that there's an issue with your data source or the way you're connecting to it. You might want to verify that your connection configuration is correct and that your data source contains the data you expect to read.
k
@kapa.ai I can add a print(response.json()) to my pare_response method which gives me a valid output, so the api call works as expected, however I still get Read 0 records from <myStream> stream. I have them implemented like this: 
def parse_response(self, response: requests.Response, **kwargs) -> Iterable[Mapping]:
res = response.json()
if response.status_code == 200:
yield from res.get("data", [])
elif response.status_code == 404:
return []
def read_records(
self,
sync_mode: SyncMode,
cursor_field: List[str] = None,
stream_slice: Mapping[str, Any] = None,
stream_state: Mapping[str, Any] = None,
) -> Iterable[StreamData]:
yield from self._read_pages(
lambda req, res, state, _slice: self.parse_response(res, stream_slice=_slice, stream_state=state), stream_slice, stream_state
)
def _read_pages(
self,
records_generator_fn: Callable[
[requests.PreparedRequest, requests.Response, Mapping[str, Any], Mapping[str, Any]], Iterable[StreamData]
],
stream_slice: Mapping[str, Any] = None,
stream_state: Mapping[str, Any] = None,
) -> Iterable[StreamData]:
stream_state = stream_state or {}
pagination_complete = False
next_page_token = None
while not pagination_complete:
request, response = self._fetch_next_page(stream_slice, stream_state, next_page_token)
yield from records_generator_fn(request, response, stream_state, stream_slice)
next_page_token = self.next_page_token(response)
if not next_page_token:
pagination_complete = True
# Always return an empty generator just in case no records were ever yielded
yield from []
def _fetch_next_page(
self, stream_slice: Mapping[str, Any] = None, stream_state: Mapping[str, Any] = None, next_page_token: Mapping[str, Any] = None
) -> Tuple[requests.PreparedRequest, requests.Response]:
request_headers = self.request_headers(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token)
request = self._create_prepared_request(
path=self.path(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token),
headers=dict(request_headers, **self.authenticator.get_auth_header()),
params=self.request_params(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token),
json=self.request_body_json(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token),
data=self.request_body_data(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token),
)
request_kwargs = self.request_kwargs(stream_state=stream_state, stream_slice=stream_slice, next_page_token=next_page_token)
response = self._send_request(request, request_kwargs)
return request, response
k
A message from kapa.ai
Your code seems to be correctly structured. However, the issue might be with the 
parse_response
method. In the 
parse_response
method, you are yielding from 
res.get("data", [])
. This means that the method is expecting the records to be under the "data" key in the response JSON. If the records are not under this key, it would result in "Read 0 records" message. Here are a few things you could check: 1. Check the structure of your API response: Ensure that the records are indeed under the "data" key in the response JSON. If they are under a different key, you should modify the 
parse_response
method to yield from the correct key. 2. Check the status code: You're only yielding records if the status code is 200. If the API is returning a different status code, no records would be yielded. You can print the status code to check this. 3. Check the pagination: In the 
_read_pages
method, you're using a 
next_page_token
to handle pagination. Ensure that this is being correctly set and used. If the 
next_page_token
is not correctly set, it might result in the same page being read repeatedly, or some pages being skipped. 4. Check the 
yield from []
line: At the end of the 
_read_pages
method, you're yielding from an empty list. This line will yield no records. If your pagination logic is causing this line to be hit before all pages have been read, it would result in "Read 0 records" message. You might want to move this line to a different location, or remove it if it's not needed. If you've checked all of these and are still seeing "Read 0 records", it's possible that there's an issue with your data source or the way you're connecting to it. You might want to verify that your connection configuration is correct and that your data source contains the data you expect to read.
k
@kapa.ai when I print my result, I get {'task_id': '12345'}. So it seems the error is the "data" key, right? How do I need to update the yield statement?
k
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