Today's release introduces parallelization of Python scripts in your fal runs. During a run, fal creates a directed acyclic graph (DAG) of links between models and scripts. The number of threads represents the maximum number of tasks fal handles simultaneously. When fal is running, it will read the configuration for
We started the fal project with a simple objective; we wanted to build a developer tool that enables running python scripts downstream of dbt models. Since we launched the initial capabilities of fal, we have received an overwhelming amount of requests to run python scripts before, after and in between
After our Unbundling of Airflow [https://blog.fal.ai/the-unbundling-of-airflow-2/] article, it has been a wild few weeks here at Features & Labels. Gorkem’s [https://twitter.com/gorkemyurt] now-viral post resonated with tens of thousands of data people around the globe. Meanwhile, we have been hard at work cooking up
dbt [https://www.getdbt.com/] is our favorite tool to build data pipelines. It allows us to skip boilerplate data engineering code, focus only on SQL and helps us build with software engineering practices like reusability, auto generating docs and tests. We recently introduced our open source project fal [https:
Sentiment analysis is the practice of determining whether a text / statement is positive, negative or neutral typically using natural language processing (NLP). Applying sentiment analysis on data such as reviews, tickets, feedback and survey responses can help you understand how your organization is doing in the eyes of your customers.
Google Firestore [https://cloud.google.com/firestore/] is a cloud-hosted NoSQL database that can be directly accessed by mobile and web applications through native SDKs. It has a rich set of use cases [https://cloud.google.com/architecture/building-scalable-apps-with-cloud-firestore#when_to_use_firestore] , including keeping track of inventories, user sessions
Using Slack bots can be a great time saver. They can enhance whatever workflow they are a part of, be it project management [https://slack.com/apps/A074YH40Z-trello?tab=more_info], version control [https://slack.github.com/] or simple content sharing [https://slack.com/apps/A0F827J2C-giphy]. As we bring our
At Features & Labels [https://fal.ai], dbt [https://www.getdbt.com/] is one of our favorite tools to use while managing our data pipelines. It is a category defining tool (see Analytics Engineering [https://www.getdbt.com/what-is-analytics-engineering/]) that enables us to build data transformations without having to write boilerplate