Metadata-Version: 2.4
Name: fpppy
Version: 0.0.4
Summary: Helper functions for Forecasting: Principles and Practice, the Pythonic Way
Author: Azul Garza, Mariana Menchero, Rob J Hyndman
License-Expression: GPL-3.0-only
Project-URL: Homepage, https://OTexts.com/fpppy
Project-URL: Source, https://github.com/OTexts/fpppy
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ipython
Requires-Dist: jinja2
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: statsmodels
Requires-Dist: utilsforecast
Provides-Extra: dev
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Dynamic: license-file

# fpppy

Helper functions used in the code of
[*Forecasting: Principles and Practice, the Pythonic Way*](https://OTexts.com/fpppy)
by Rob J Hyndman, George Athanasopoulos, Azul Garza, Cristian Challu,
Max Mergenthaler and Kin G Olivares.

The package provides plotting wrappers around
[utilsforecast](https://github.com/Nixtla/utilsforecast) (`plot_series()`,
`plot_series_stacked()`, `plot_diagnostics()`) and a `LinearRegression`
class that extends scikit-learn's with residuals, standard errors and
prediction intervals.

```bash
pip install fpppy
```

To run the book's code, install the pinned versions in the book's
[`requirements.txt`](https://github.com/OTexts/fpppy/blob/main/data/requirements.txt),
which includes fpppy. See the book's
[Using Python](https://OTexts.com/fpppy/UsingPython.html) page.

## Development setup


### 1. install [`uv`](https://github.com/astral-sh/uv/)

use `uv` to manage your virtual environments:

```bash
pip install uv
```

### 2. create a virtual environment

create an environment using python 3.10 (or your preferred version):

```bash
uv venv --python 3.10
```

### 3. activate the environment

activate the virtual environment:

```bash
source .venv/bin/activate
```

### 4. install dependencies

install the package with its development tools:

```bash
uv pip install -e ".[dev]"
```

### 5. install pre-commits

```bash
pre-commit install
```

## ready to code  
you're now all set to start building your project.
