Core module for Fishnet compute-over-data (COD) network on Aleph.im
Project description
Fishnet
Fishnet stands for Financial time Series Hosting NETwork.
It is a Compute-over-Data (CoD) system that uses the distributed Aleph.im network as a substrate for computation. It is a decentralized, peer-to-peer, and serverless system that allows users to run statistical computations on their timeseries data without having to upload it to a centralized server.
This python module contains a common data model, built on the Aleph Active Record SDK (AARS), that is being used by the Fishnet API and executor VMs. The data model is used to store and query:
- Timeseries & Datasets
- Algorithms
- Permissions
- Executions
- Results
Roadmap
- Basic message model
- API for communicating with Fishnet system
- Basic CRUD operations
- Permission management
- Timeslice distribution across executor nodes
- Signature verification of requests
- Local VM caching
- Executor VM
- Listens for Aleph "Execution" messages and executes them
- Uploads results to Aleph
- Pandas support
- Distributed execution & aggregation
- Different execution environments (e.g. PyTorch, Tensorflow)
- GPU support
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.
Source Distribution
Built Distribution
File details
Details for the file fishnet_cod-0.0.4.tar.gz
.
File metadata
- Download URL: fishnet_cod-0.0.4.tar.gz
- Upload date:
- Size: 3.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5467dc8771323258f23d70b3abb4a4b14fb1209a70a252ae01fa200bf1aa4205 |
|
MD5 | 916019805f6ff18a552b9436608f7144 |
|
BLAKE2b-256 | 1f0f0637416d676a7992639c8f0e4193ad6d4958bcd82732782882668b0b237a |
File details
Details for the file fishnet_cod-0.0.4-py3-none-any.whl
.
File metadata
- Download URL: fishnet_cod-0.0.4-py3-none-any.whl
- Upload date:
- Size: 4.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | dcdf70b7e8f7af16254af0a6f8167dd9c3c66e5f32a77eb475d1f4510492e215 |
|
MD5 | 998eaffabd711bddeb284d193e36a4b6 |
|
BLAKE2b-256 | 5be5e482e6dff414af29965d4eb18d035d6298a4da80865974110d9b3b2193e9 |