ethereum-etl
spotty
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| ethereum-etl | spotty | |
|---|---|---|
| 3 | 3 | |
| 2,823 | 491 | |
| 1.6% | 0.8% | |
| 6.9 | 0.0 | |
| 17 days ago | 6 months ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ethereum-etl
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Blockchain transactions decoding: making wallet activity understandable
Event is a log entity which EVM smart contracts can emit during transaction execution. Events are very good at signalling that an some action has taken place on-chain. Applications can subscribe and listen to events to trigger some off-chain logic or they can index, transform and store events in some off-chain storage (look at The Graph protocol or Ethereum ETL).
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data engineering in web3
I'm surprised this is the only good response in this thread so far. Blockchain data is completely open but requires some organization in order to perform analytics. Nansen for example is a product that is built on top of ethereum-etl which you can checkout here
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Trying To Recover Old ETH
You can use https://github.com/blockchain-etl/ethereum-etl
spotty
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[D] Interactive Compute Platform Recommendations for ML Research
Use spotty https://github.com/spotty-cloud/spotty to launch AWS Spot instances that you can use ssh port forwarding with to run GPU experiments from a jupyer notebook.
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[P]Spotml.io: Seamless ML training on AWS Spot instances, with docker (training 3X cheaper)
SpotML is a command line tool that automatically manages ML training on AWS spot instances. It lets you handle spot interruptions by resuming training using the latest checkpoint. Documentation link to try it out Looking for feedback from early testers. You would be an ideal candidate if you have a side project that you're spending your own money to train. Acknowledgement: - SpotML is built on top of existing open source library Spotty
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Show HN: Seamless ML training on AWS Spot instances
- SpotML is built on top of existing open source library Spotty: https://github.com/spotty-cloud/spotty
What are some alternatives?
CueObserve - Timeseries Anomaly detection and Root Cause Analysis on data in SQL data warehouses and databases
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
helium-etl-queries - A collection of SQL views used to enrich data produced by a Helium blockchain-etl
sagemaker-training-toolkit - Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
rainbow_csv - 🌈Rainbow CSV - Vim plugin: Highlight columns in CSV and TSV files and run queries in SQL-like language
sagemaker-tensorflow-training-toolkit - Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.
NetXML-to-CSV - Convert .netxml file into CSV file
micro-service-email - Deploy a self-hosted gmail microservice in minutes
dbd - dbd is a database prototyping tool that enables data analysts and engineers to quickly load and transform data in SQL databases.
gcptree - Like the unix tree command but for GCP Org Heirarchy
BigQuery-Python - Simple Python client for interacting with Google BigQuery.
aws-ethereum-miner - CloudFormation template for mining Ethereum crypto currency on AWS