v0.7 — Playing nice with dbt Python models
dbt recently introduced native Python models support! At fal, we believe this should be the way to run your Python models, so we have been working on dbt-fal, an adapter that enables you to run dbt Python models with any datawarehouse (including Redshift, Postgres). dbt-fal can be used to run
Parallelizing Python Workflows in fal
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
How to run sentiment analysis on your dbt models from Python
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.