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Exporters provide a flexible way to export data from multiple sources to multiple destinations, allowing filtering and transforming the data.

This Github repository is used as a central repository.

Full documentation can be found here

Getting Started

Install exporters

First of all, we recommend to create a virtualenv:

virtualenv exporters
source exporters/bin/activate


pip install exporters

Creating a configuration

Then, we can create our first configuration object and store it in a file called config.json.

This configuration will read from an s3 bucket and store it in our filesystem, exporting only the records which have United States in field country:

     "reader": {
         "name": "exporters.readers.s3_reader.S3Reader",
         "options": {
             "bucket": "YOUR_BUCKET",
             "aws_access_key_id": "YOUR_ACCESS_KEY",
             "aws_secret_access_key": "YOUR_SECRET_KEY",
             "prefix": "exporters-tutorial/sample-dataset"
     "filter": {
         "name": "exporters.filters.key_value_regex_filter.KeyValueRegexFilter",
         "options": {
             "keys": [
                 {"name": "country", "value": "United States"}
         "name": "exporters.writers.fs_writer.FSWriter",
         "options": {
             "filebase": "/tmp/output/"

Export with script

We can use the provided script to run this export:

python bin/ --config config.json

Use it as a library

The export can be run using exporters as a library:

from exporters import BasicExporter

exporter = BasicExporter.from_file_configuration('config.json')

Resuming an export job

Let’s suppose we have a pickle file with a previously failed export job. If we want to resume it we must run the export script:

python bin/ --resume pickle://pickle-file.pickle

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