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Python CDK Speedrun: Creating a Source

CDK Speedrun (HTTP API Source Creation Any Route)

This is a blazing fast guide to building an HTTP source connector. Think of it as the TL;DR version of this tutorial.

If you are a visual learner and want to see a video version of this guide going over each part in detail, check it out below.

A speedy CDK overview.


  1. Python >= 3.9
  2. Poetry
  3. Docker

Generate the Template

# # clone the repo if you havent already
# git clone --depth 1
# cd airbyte # start from repo root
cd airbyte-integrations/connector-templates/generator

Select the Python CDK Source and name it python-http-example.

Create Dev Environment

cd ../../connectors/source-python-http-example
poetry install

Define Connector Inputs

cd source_python_http_example

We're working with the PokeAPI, so we need to define our input schema to reflect that. Open the spec.yaml file here and replace it with:

title: Pokeapi Spec
type: object
- pokemon_name
type: string
description: Pokemon requested from the API.
pattern: ^[a-z0-9_\-]+$
- ditto
- luxray
- snorlax

As you can see, we have one input to our input schema, which is pokemon_name, which is required. Normally, input schemas will contain information such as API keys and client secrets that need to get passed down to all endpoints or streams.

Ok, let's write a function that checks the inputs we just defined. Nuke the file. Now add this code to it. For a crucial time skip, we're going to define all the imports we need in the future here. Also note that your AbstractSource class name must be a camel-cased version of the name you gave in the generation phase. In our case, this is SourcePythonHttpExample.

from typing import Any, Iterable, List, Mapping, MutableMapping, Optional, Tuple

import requests
import logging
from airbyte_cdk.sources import AbstractSource
from airbyte_cdk.sources.streams import Stream
from airbyte_cdk.sources.streams.http import HttpStream

from . import pokemon_list

logger = logging.getLogger("airbyte")

class SourcePythonHttpExample(AbstractSource):
def check_connection(self, logger, config) -> Tuple[bool, any]:"Checking Pokemon API connection...")
input_pokemon = config["pokemon_name"]
if input_pokemon not in pokemon_list.POKEMON_LIST:
result = f"Input Pokemon {input_pokemon} is invalid. Please check your spelling and input a valid Pokemon.""PokeAPI connection failed: {result}")
return False, result
else:"PokeAPI connection success: {input_pokemon} is a valid Pokemon")
return True, None

def streams(self, config: Mapping[str, Any]) -> List[Stream]:
return [Pokemon(pokemon_name=config["pokemon_name"])]

Create a new file called at the same level. This will handle input validation for us so that we don't input invalid Pokemon. Let's start with a very limited list - any Pokemon not included in this list will get rejected.

""" includes a list of all known pokemon for config validation in


Test it.

cd ..
mkdir sample_files
echo '{"pokemon_name": "pikachu"}' > sample_files/config.json
echo '{"pokemon_name": "chikapu"}' > sample_files/invalid_config.json
poetry run source-python-http-example check --config sample_files/config.json
poetry run source-python-http-example check --config sample_files/invalid_config.json

Expected output:

> poetry run source-python-http-example check --config sample_files/config.json
{"type": "CONNECTION_STATUS", "connectionStatus": {"status": "SUCCEEDED"}}

> poetry run source-python-http-example check --config sample_files/invalid_config.json
{"type": "CONNECTION_STATUS", "connectionStatus": {"status": "FAILED", "message": "'Input Pokemon chikapu is invalid. Please check your spelling our input a valid Pokemon.'"}}

Define your Stream

In your file, add this Pokemon class. This stream represents an endpoint you want to hit, which in our case, is the single Pokemon endpoint.

class Pokemon(HttpStream):
url_base = ""

# Set this as a noop.
primary_key = None

def __init__(self, pokemon_name: str, **kwargs):
self.pokemon_name = pokemon_name

def next_page_token(self, response: requests.Response) -> Optional[Mapping[str, Any]]:
# The API does not offer pagination, so we return None to indicate there are no more pages in the response
return None

def path(
) -> str:
return "" # TODO

def parse_response(
) -> Iterable[Mapping]:
return None # TODO

Now download this file. Name it pokemon.json and place it in /source_python_http_example/schemas.

This file defines your output schema for every endpoint that you want to implement. Normally, this will likely be the most time-consuming section of the connector development process, as it requires defining the output of the endpoint exactly. This is really important, as Airbyte needs to have clear expectations for what the stream will output. Note that the name of this stream will be consistent in the naming of the JSON schema and the HttpStream class, as pokemon.json and Pokemon respectively in this case. Learn more about schema creation here.

Test your discover function. You should receive a fairly large JSON object in return.

poetry run source-python-http-example discover --config sample_files/config.json

Note that our discover function is using the pokemon_name config variable passed in from the Pokemon stream when we set it in the __init__ function.

Reading Data from the Source

Update your Pokemon class to implement the required functions as follows:

class Pokemon(HttpStream):
url_base = ""

# Set this as a noop.
primary_key = None

def __init__(self, pokemon_name: str, **kwargs):
# Here's where we set the variable from our input to pass it down to the source.
self.pokemon_name = pokemon_name

def path(self, **kwargs) -> str:
pokemon_name = self.pokemon_name
# This defines the path to the endpoint that we want to hit.
return f"pokemon/{pokemon_name}"

def request_params(
stream_state: Mapping[str, Any],
stream_slice: Mapping[str, Any] = None,
next_page_token: Mapping[str, Any] = None,
) -> MutableMapping[str, Any]:
# The api requires that we include the Pokemon name as a query param so we do that in this method.
return {"pokemon_name": self.pokemon_name}

def parse_response(
response: requests.Response,
stream_state: Mapping[str, Any],
stream_slice: Mapping[str, Any] = None,
next_page_token: Mapping[str, Any] = None,
) -> Iterable[Mapping]:
# The response is a simple JSON whose schema matches our stream's schema exactly,
# so we just return a list containing the response.
return [response.json()]

def next_page_token(self, response: requests.Response) -> Optional[Mapping[str, Any]]:
# While the PokeAPI does offer pagination, we will only ever retrieve one Pokemon with this implementation,
# so we just return None to indicate that there will never be any more pages in the response.
return None

We now need a catalog that defines all of our streams. We only have one stream: Pokemon. Download that file here. Place it in /sample_files named as configured_catalog.json. More clearly, this is where we tell Airbyte all the streams/endpoints we support for the connector and in which sync modes Airbyte can run the connector on. Learn more about the AirbyteCatalog here and learn more about sync modes here.

Let's read some data.

poetry run source-python-http-example read --config sample_files/config.json --catalog sample_files/configured_catalog.json

If all goes well, containerize it so you can use it in the UI:

Option A: Building the docker image with airbyte-ci

This is the preferred method for building and testing connectors.

If you want to open source your connector we encourage you to use our airbyte-ci tool to build your connector. It will not use a Dockerfile but will build the connector image from our base image and use our internal build logic to build an image from your Python connector code.

Running airbyte-ci connectors --name source-<source-name> build will build your connector image. Once the command is done, you will find your connector image in your local docker host: airbyte/source-<source-name>:dev.

Option B: Building the docker image with a Dockerfile

If you don't want to rely on airbyte-ci to build your connector, you can build the docker image using your own Dockerfile. This method is not preferred, and is not supported for certified connectors.

Create a Dockerfile in the root of your connector directory. The Dockerfile should look something like this:

FROM airbyte/python-connector-base:1.1.0

COPY . ./airbyte/integration_code
RUN pip install ./airbyte/integration_code

# The entrypoint and default env vars are already set in the base image
# ENV AIRBYTE_ENTRYPOINT "python /airbyte/integration_code/"
# ENTRYPOINT ["python", "/airbyte/integration_code/"]

Please use this as an example. This is not optimized.

Build your image:

docker build . -t airbyte/source-example-python:dev

You're done. Stop the clock :)

Further reading

If you have enjoyed the above example, and would like to explore the Python CDK in even more detail, you may be interested looking at how to build a connector to extract data from the Webflow API