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        "author": "Joseph Curtin <42@jbcurtin.io",
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        "description": "[![Documentation Status](https://readthedocs.org/projects/bert-etl/badge/?version=latest)](https://bert-etl.readthedocs.io/en/latest/?badge=latest)\n\n# Bert\nA microframework for simple ETL solutions.\n\n\n## Architecture\n\nAt 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.\n\nAt 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.\n\n## Warning: aws-lambda deploy target still considered beta\n\n`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.\n\n## Begin with\n\nLets begin with an example of loading data from a file-server and than loading it into numpy arrays\n\n```\n$ virtualenv -p $(which python3) env\n$ source env/bin/activate\n$ pip install bert-etl\n$ pip install librosa # for demo project\n$ docker run -p 6379:6379 -d redis # bert-etl runs on redis to share data across CPUs\n$ bert-runner.py -n demo\n$ PYTHONPATH='.' bert-runner.py -m demo -j sync_sounds -f\n```\n\n## Release Notes\n\n### 0.3.0\n\n* 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\n\n### 0.2.1\n\n* Added Release Notes\n\n### 0.2.0\n\n* Added Redis Service auto run. Using docker, redis will be pulled and started in the background\n* Added Redis Service channels, sometimes you'll want to run to etl-jobs on the same machine\n\n## Fund Bounty Target Upgrades\n\nBert 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\n\nhttps://www.patreon.com/jbcurtin\n\n\n## Roadmap\n\n* Create configuration file, `bert-etl.yaml`\n* Support conda venv\n* Support pyenv venv\n* Support dynamodb flush\n* Support multipule invocations per AWS account\n* Support undeploy AWS Lambda\n* Support Bottle functions in AWS Lambda\n\n\n## Tutorial Roadmap\n\n* Introduce Bert API\n* Explain `bert.binding`\n* Explain `comm_binder`\n* Explain `work_queue`\n* Explain `done_queue`\n* Explain `ologger`\n* Explain `DEBUG` and how turning it off allows for x-concurrent processes\n* Show an example on how to load timeseries data, calcualte the mean, and display the final output of the mean\n* Expand the example to show how to scale the application implicitly\n* Show how to run locally using Redis\n* Show how to run locally without Redis, using Dynamodb instead\n* Show how to run remotly using AWSLambda and Dynamodb \n* Talk about dynamodb and eventual consistency",
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