v0.9: New functional API (preview), faster refutations, and better independence tests for GCMs

• Preview for the new functional API (see notebook). The new API (in experimental stage) allows for a modular use of the different functionalities and includes separate fit and estimate methods for causal estimators. Please leave your feedback here. The old DoWhy API based on CausalModel should work as before. (@andresmor-ms)

• Faster, better sensitivity analyses.

  • Many refutations now support joblib for parallel processing and show a progress bar (@astoeffelbauer, @yemaedahrav).
  • Non-linear sensitivity analysis [ `Chernozhukov, Cinelli, Newey, Sharma & Syrgkanis (2021), example notebook ] (@anusha0409)
  • E-value sensitivity analysis [ Ding & Vanderweele (2016), example notebook] (@jlgleason)

• New API for unit change attribution (@kailashbuki)

• New quality option BEST for auto-assignment of causal mechanisms, which uses the optional auto-ML library AutoGluon (@bloebp)

• Better conditional independence tests through the causal-learn package (@bloebp)

• Algorithms for computing efficient backdoor sets [ example notebook ] (@esmucler)

• Support for estimating controlled direct effect (@amit-sharma)

• Support for multi-valued treatments for econml estimators (@EgorKraevTransferwise)

• New PyData theme for documentation with new homepage, Getting started guide, revised User Guide and examples page (@petergtz)

• A contributing guide and simplified instructions for new contributors (@MichaelMarien)

• Streamlined dev environment using Poetry for managing dependencies and project builds (@darthtrevino)

• Bug fixes