Financial modelling for pandas users.
Financial modelling with Excel can be a nightmare. These models are hard to maintain, hard to extend, and hard to encode with any sophisticated logic. PyCashflow provides the framework to construct sophisitcated financial models using python-native constructs.
from pycashflow import FinancialModel, LineItem
model = FinancialModel("Simple Cashflow Model")
model["Revenue Stream #1"] = LineItem(lambda t: 1000)
model["Revenue Stream #2"] = LineItem(lambda t: 100 + 10*t)
model["Expense #1"] = LineItem(lambda t: 500)
model["Expense #2"] = LineItem(lambda t: 50 + 5*t)
model["Profit"] = (
model["Revenue Stream #1"]
+ model["Revenue Stream #2"]
- model["Expense #1"]
- model["Expense #2"]
)
df = model.run(steps=24)
df.tail()We rely on just to act as our command runner.
It is not possible to install this via PyPI and instead you must rely on the
installation instructions on the Github page.
The most common installation method is to use conda. To create a new virtual
environment, install just and the package requirements, you can run the
following commands:
conda create -n pycashflow python just
# wait for this to complete...
conda activate pycashflow
pip install -e .[dev]