target-s3
is a Singer target for s3.
Build with the Meltano Target SDK.
about
stream-maps
schema-flattening
A full list of supported settings and capabilities for this target is available by running:
target-s3 --about
Setting | Required | Default | Description |
---|---|---|---|
aws_access_key | False | None | The aws secret access key for auth to S3. |
aws_secret_access_key | False | None | The aws secret access key for auth to S3. |
aws_region | True | None | The aws region to target |
bucket | True | None | The aws bucket to target. |
prefix | False | None | The prefix for the key. |
append_date_to_prefix | False | None | A flag to append the date to the key prefix. |
append_date_to_prefix_grain | False | None | The grain of the date to append to the prefix. |
append_date_to_filename | False | None | A flag to append the date to the key filename. |
append_date_to_filename_grain | False | None | The grain of the date to append to the filename. |
object_format | False | None | The format of the storage object. |
flatten_records | False | None | A flag indictating to flatten records. |
stream_maps | False | None | Config object for stream maps capability. For more information check out Stream Maps. |
stream_map_config | False | None | User-defined config values to be used within map expressions. |
flattening_enabled | False | None | 'True' to enable schema flattening and automatically expand nested properties. |
flattening_max_depth | False | None | The max depth to flatten schemas. |
This Singer target will automatically import any environment variables within the working directory's
.env
if the --config=ENV
is provided, such that config values will be considered if a matching
environment variable is set either in the terminal context or in the .env
file.
You can easily run target-s3
by itself or in a pipeline using Meltano.
target-s3 --version
target-s3 --help
# Test using the "Carbon Intensity" sample:
tap-carbon-intensity | target-s3 --config /path/to/target-s3-config.json
Follow these instructions to contribute to this project.
pipx install poetry
poetry install
Create tests within the target_s3/tests
subfolder and
then run:
poetry run pytest
You can also test the target-s3
CLI interface directly using poetry run
:
poetry run target-s3 --help
Testing with Meltano
Note: This target will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.
Next, install Meltano (if you haven't already) and any needed plugins:
# Install meltano
pipx install meltano
# Initialize meltano within this directory
cd target-s3
meltano install
Now you can test and orchestrate using Meltano:
# Test invocation:
meltano invoke target-s3 --version
# OR run a test `elt` pipeline with the Carbon Intensity sample tap:
meltano elt tap-carbon-intensity target-s3
See the dev guide for more instructions on how to use the Meltano Singer SDK to develop your own Singer taps and targets.