René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Feature Request:  InfluxDB ReadOnly On/Offline, use Waitress instead of Gunicorn, and integrate Feast.client into repo ","articleBody":"Hello!\r\n\r\nCouple of thoughts (simple implementations) that would be fantastic improvements for Feast:\r\n1) **InfluxDB**: You've integrated with TimescaleDB (a.k.a. Postgres) and Redis.  Why not integrate with a simple read provider to influxdb?  I believe the influxdb client is as simple as Redis, although influxdb is less of a \"table like\" database, so I don't believe deletes/updates would be necessary (it might be nice to ingest influx and store it into a DB like redshift/postgres).  \r\n2) **Waitress** option for WSGI as an alternative to gunicorn - I installed Feast on my AWS EC2 instance no problem!  I went to use it on my windows dev machine, and voila, my entire project came to a big halt!  \"Fcntl not found.\" Gunicorn relies on package **fcntl** for file locking, but **fcntl is not available on windows** except possibly via WSL (Windows Subsystem for Linux).  If you all want widescale adoption, developers are on PCs/Macs/Linux - choosing a Linux specific system seems counter productive to the adoption of Feast.  I realize I may get some windows-haters comments, but the fact is, the more successful Feast is, the more adoption it will have and it will require support on all platforms.  Alternate solution would be to make a \"feast[client]\" that doesn't install the gunicorn package.\r\n3) **Feast Client integration:**   At the time I'm writing this, it doesn't appear that Feast's client code is in the codebase (https://api.docs.feast.dev/python/_modules/feast/client).  It would be great for developers to be able to access Feast as they do with MLFLow:\r\n\r\n`\r\nimport mlflow\r\nremote_server_uri = \"http://192.1.6.299:5000\"\r\nmlflow.set_tracking_uri(remote_server_uri)\r\n\r\nif save_model:\r\n with mlflow.start_run(run_name=\"test_run\"):\r\n    mlflow.log_artifact(\"jupyter_notebook_2024_02_23_MLFLOW.py\")\r\n    mlflow.log_artifact(\"cleaned_parquet_file_166\")\r\n`\r\n\r\nLook at how simple it is to integrate MLFlow into my workflow!!!  I believe this is very attainable for Feast, and kind of necessary in a client/server world.  \r\n\r\nFinally, THANK YOU for upgrade support of Pandas 2.2.x @sudohainguyen!  That was an absolute show stopper for us if it wasn't resolved (currently I'm running with Pandas 2.2.1 while the PR gets approved and merged into the pip binaries).","author":{"url":"https://github.com/SeanWidesense","@type":"Person","name":"SeanWidesense"},"datePublished":"2024-02-27T21:26:46.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":6},"url":"https://github.com/3973/feast/issues/3973"}