Reverse Dependencies of google-cloud-storage
The following projects have a declared dependency on google-cloud-storage:
- hound — A FireCloud database extension
- houston-client — Houston Python Client
- hstestaq — Prediction Infrastructure for Data Scientists
- humailib — HUMAI data science framework
- hydra-ml — A cloud-agnostic ML Platform
- hydrotools.gcp-client — Retrieve National Water Model data from Google Cloud Platform.
- hydrotools.nwm-client — Retrieve National Water Model data from various sources.
- hydrotools.nwm-client-new — Retrieve National Water Model data from various sources.
- hyperdb — Hyperdb provides wrapper functions for working with Tableau hyper datasources and moving data between Tableau Server, Google Cloud Platform and Microsoft Azure through a common interface
- ibkr-report-parser — Interactive Brokers (IBKR) Report Parser for MyTax (vero.fi)
- idg-metadata-client — Ingestion Framework for OpenMetadata
- im-futuregcscompose — function for composing an folder full of text files, into one text file, in gcs, for Google App Engine, Python standard environment
- image-service-foundation — no summary
- inbound — declarative data ingestion.
- indexify-extractor-sdk — Indexify Extractor SDK to build new extractors for extraction from unstructured data
- indxdatalaketools — Package that allows the upload of files to a datalake
- indykite-sdk-python — A python SDK package for Indykite's system (with protobuf)
- ingaia-libs — inGaia Python Utility Library
- insomnyak-connector — Suite of prebuilt connectors to other APIs
- instackup — A package to ease interaction with cloud services, DB connections and commonly used functionalities in data analytics.
- inyourface — In Your Face
- io-orbit — Simple and flexible ML workflow engine
- janis-pipelines.runner — Easier way to run workflows, configurable across environments
- jefferson-street-singer-ingest — Library holding the taps and targets for Jefferson Street Ingestion
- jesspack — Project Description
- joes-giant-toolbox — A large collection of general python functions and classes that I use in my daily work
- joint-calling — Pipeline for joint calling, sample and variant QC for WGS germline variant calling data
- jrdb — no summary
- kcli — Provisioner/Manager for Libvirt/Vsphere/Aws/Gcp/Kubevirt/Ovirt/Openstack/IBM Cloud and containers
- kedro-vertexai — Kedro plugin with GCP Vertex AI support
- keephq — Alerting. for developers, by developers.
- keras-bucket-tensorboard-callback — A Keras Callback that uploads your Tensorboard logs to a Cloud Bucket
- keycloak-sync — keycloak cli tool
- kfp — KubeFlow Pipelines SDK
- kfserving — KFServing Python SDK
- kghub-downloader — Downloads and caches files for knowledge graph ETL
- kinto-attachment — Attach files to Kinto records
- kiwi-booster — Python utility functions and classes for KiwiBot AI&Robotics team
- klaytn-etl-cli — Tools for exporting Klaytn blockchain data to JSON
- klaytn-etl-test — Tools for exporting Klaytn blockchain data to JSON
- klio-cli — Main entrypoint for Klio jobs
- klops — Klops: Koin Machine Learning Ops
- knada-kafka-consumer — no summary
- koala-buckets — Python package to handle buckets.
- koala-task-manager — Python package for creating task and logging with Naisjob.
- koku-nise — A tool for generating sample cost and usage data for testing purposes.
- kraken-g-api — Kraken g api
- kraken-gstorage — Kraken gstorage
- kserve — KServe Python SDK
- kserve-mathking — KServe Python SDK
- kubeflow-fairing — Kubeflow Fairing Python SDK.
- kubeflow-fairing-dmtest — Kubeflow Fairing Python SDK.
- kubric — A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation, depth maps, and optical flow.
- kubric-nightly — A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation, depth maps, and optical flow.
- kwola — Kwola makes an AI powered tool for finding bugs in software
- labmachine — A simple creator of machines with Jupyterlab
- lanceviewer — no summary
- langchain-google-community — An integration package connecting miscellaneous Google's products and LangChain
- langchain-google-vertexai — An integration package connecting Google VertexAI and LangChain
- lapdog — A relaxed wrapper for FISS and dalmatian
- larcoh — Pipeline for joint calling, sample and variant QC for WGS germline variant calling data in large cohorts
- latch-cloud-clients — no summary
- launchflow — Python-native infrastructure for the cloud: LaunchFlow provides a Python SDK that automatically creates and connects to production-ready infrastructure (such as Postgres, Redis, etc..) in your own cloud account. LaunchFlow completely removes the need for DevOps allowing you to focus on your application logic.
- leadguru-jobs — LGT jobs builds
- legal-doc-processing — Theolex document processing
- lilac — Organize unstructured data
- lilacai — Organize unstructured data
- lithops — Lithops lets you transparently run your Python applications in the Cloud
- liveramp-automation — This is the base liveramp_automation_framework
- llama-index-vector-stores-vertexaivectorsearch — llama-index vector_stores Vertex AI Vector Search integration
- llm-index — rag for llm
- llm4bi-embedder — Package including any embedder for the LLM4BI project
- lmcmlflow — MLflow: A Platform for ML Development and Productionization
- loads-pipeline — Loads Pipeline Workflow Package.
- lolaml — LolaML - track your ML experiments
- lolpop — A software engineering framework for machine learning workflows
- lowclouds — The lowclouds is a shortcut library for several cloud service libraries.
- lsst-resources — An abstraction layer for reading and writing from URI file resources.
- lume — Lume
- luminoth — Computer vision toolkit based on TensorFlow
- luntaiDs — Make Data Scientist life Easier Tool
- lvfs — Convenient high level file IO across multiple protocols
- lwc-common — no summary
- m4-utils — Biblioteca com funções de uso comum em projetos de aprendizado de máquina e ciencia de dados.
- mango — Library with a collection of usefull classes and methods to DRY
- mara-storage — Configuration of storage connections for mara
- matos-gcp-provider — Python matos gcp provider
- mattlib — API data extraction and formatting utilities.
- mbari-pbp — PyPAM based Processing
- meerkat-ml — Meerkat is building new data abstractions to make machine learning easier.
- meltano — Meltano is your CLI for ELT+: Open Source, Flexible, and Scalable. Move, transform, and test your data with confidence using a streamlined data engineering workflow you’ll love.
- mercury-ml — A library for managing Machine Learning workflows
- merlin-sdk — Python SDK for Merlin
- metemcyber — Decentralized Cyber Threat Intelligence Kaizen Framework.
- michaelvll-skypilot — An intercloud broker above the cloud
- mim-ocr — Tool for using different OCR engines and process their results using common data structures.
- Minari — A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities.
- minato — A Unified File I/O Library for Python
- misp-feed-manager — Set of utilities to manage MISP feeds
- mk-feature-store — Python SDK for Feast