Skip to main content

A microframework for simple ETL solutions

Project description

[![Documentation Status](](

# Bert A microframework for simple ETL solutions.

## Architecture

At its core, bert-etl uses Dynamodb Streams to communicate between lambda functions. bert-etl.yaml provides control on how the initial lambda function is called, either by periodic events, sns topics, or s3 bucket (planned)events. Passing an event to bert-etl is straight forward from zappa or a generic AWS lambda function you’ve hooked up to API Gateway.

At this moment in time, there are no plans to attach API Gateway to bert-etl.yaml because there is already great software(like zappa) that does this.

## Warning: aws-lambda deploy target still considered beta

bert-etl ships with a deploy target to aws-lambda. This feature isn’t very well documented yet, and has quite a bit of work to de done so it may function more consistently. Be aware that aws-lambda is a product ran and controlled by AWS. If you incure charges using bert-etl while utilizing aws-lambda, you may not consider us responsible. bert-etl is offered under MIT license which includes a Use at your own risk clause.

## Begin with

Lets begin with an example of loading data from a file-server and than loading it into numpy arrays

` $ virtualenv -p $(which python3) env $ source env/bin/activate $ pip install bert-etl $ pip install librosa # for demo project $ docker run -p 6379:6379 -d redis # bert-etl runs on redis to share data across CPUs $ -n demo $ PYTHONPATH='.' -m demo -j sync_sounds -f `

## Release Notes

### 0.3.0

  • Added Error Management. When an error occurs, bert-runner will log the error and re-run the job. If the same error happens often enough, the job will be aborted

### 0.2.1

  • Added Release Notes

### 0.2.0

  • Added Redis Service auto run. Using docker, redis will be pulled and started in the background
  • Added Redis Service channels, sometimes you’ll want to run to etl-jobs on the same machine

## Fund Bounty Target Upgrades

Bert provides a boiler plate framework that’ll allow one to write concurrent ETL code using Pythons’ microprocessing module. One function starts the process, piping data into a Redis backend that’ll then be consumed by the next function. The queues are respectfully named for the scope of the function: Work(start) and Done(end) queue. Please consider contributing to Bert Bounty Targets to improve this documentation

## Roadmap

  • Create configuration file, bert-etl.yaml
  • Support conda venv
  • Support pyenv venv
  • Support dynamodb flush
  • Support multipule invocations per AWS account
  • Support undeploy AWS Lambda
  • Support Bottle functions in AWS Lambda

## Tutorial Roadmap

  • Introduce Bert API
  • Explain bert.binding
  • Explain comm_binder
  • Explain work_queue
  • Explain done_queue
  • Explain ologger
  • Explain DEBUG and how turning it off allows for x-concurrent processes
  • Show an example on how to load timeseries data, calcualte the mean, and display the final output of the mean
  • Expand the example to show how to scale the application implicitly
  • Show how to run locally using Redis
  • Show how to run locally without Redis, using Dynamodb instead
  • Show how to run remotly using AWSLambda and Dynamodb
  • Talk about dynamodb and eventual consistency

Project details

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for bert-etl, version 0.4.77
Filename, size File type Python version Upload date Hashes
Filename, size bert-etl-0.4.77.tar.gz (48.7 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page