Emergent parallelism and execution branching from inside your functions
Project description
bifurcate 🔀
Emergent parallelism and execution branching from inside your functions.
Standard patterns force you to extract your logic and wrap it in for loops or complex task graphs just to run variations of a pipeline. bifurcate lets you branch the execution graph dynamically from inside the function itself.
Write your logic sequentially, as if it only runs once. Let the system magically map the permutations.
Usage
import bifurcate
@bifurcate.collect
def calculate_pricing(user_id):
# 1. Standard execution starts normally
base_price = database.get_price(user_id)
# BRANCH POINT:
# The system transparently branches the execution universe here.
# The function will conceptually branch, returning a different
# value to 'discount' for each path.
discount = bifurcate.branch([0.0, 0.10, 0.20])
# 2. This logic is evaluated cleanly for each distinct branch
final_price = base_price * (1 - discount)
print(f"Calculated: {final_price}")
return final_price
# The decorator catches the parallel universes and aggregates the results
results = calculate_pricing("user_123")
# Output: [100.0, 90.0, 80.0]
Features
- In-line Branching: No more
forloops polluting your caller logic. Keep your domain functions completely isolated and focused on single-item math. - Zero-Boilerplate Permutations: Perfect for A/B testing, ML hyperparameter sweeps, or fallback strategies.
- The List Monad for Python: Achieves mathematically pure map/flatMap operations using standard, highly-readable imperative Python syntax.
Installation
uv add bifurcate
# or
pip install bifurcate
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