FYI there's (at least?) two Judea Pearl books on causality. "Causality" was written in early 2000s, and is filled with theorems + proof + prose detailing all the major results from the theory. It's not a particularly hard book if you studied Mathematics, but it is Mathematics.

"Causal inference in statistics" is a 2017 book that covers the actually important results from the previous book, in an approachable manner, and with a focus on applying the results to actual problems. Some theorems are stated formally, but usually without proof. It's 40$ on Amazon, strongly recommended. https://www.amazon.com/Causal-Inference-Statistics-Judea-Pea...

There's also this primer, recently out: https://www.amazon.com/Causal-Inference-Statistics-Judea-Pea...

"Causal Inference in Statistics: A Primer" is somewhat lighter (at least if you have an statistics background).

https://www.amazon.com/Causal-Inference-Statistics-Judea-Pea...