Find relative paths from a project root directory

Finding project directories in Python (data science) projects, just like there R here and rprojroot packages.

Problem: I have a project that has a specific folder structure, for example, one mentioned in Noble 2009 or something similar to this project template, and I want to be able to:

1. Run my python scripts without having to specify a series of ../ to get to the data folder.
2. cd into the directory of my python script instead of calling it from the root project directory and specify all the folders to the script.
3. Reference datasets from a root directory when using a jupyter notebook because everytime I use a jupyter notebook, the working directory changes to the location of the notebook, not where I launched the notebook server.

Solution: pyprojroot finds the root working directory for your project as a pathlib object. You can now use the here function to pass in a relative path from the project root directory (no matter what working directory you are in the project), and you will get a full path to the specified file. That is, in a jupyter notebook, you can write something like pandas.read_csv(here('./data/my_data.csv')) instead of pandas.read_csv('../data/my_data.csv'). This allows you to restructure the files in your project without having to worry about changing file paths.

Great for reading and writing datasets!

Installation

pip

pip install pyprojroot

conda

https://anaconda.org/conda-forge/pyprojroot

conda install -c conda-forge pyprojroot 

Usage

from pyprojroot import here

here()

Example

Load the packages

In [1]: from pyprojroot import here
In [2]: import pandas as pd

The current working directory is the "notebooks" folder

In [3]: !pwd
/home/dchen/git/hub/scipy-2019-pandas/notebooks

In the notebooks folder, I have all my notebooks

In [4]: !ls
01-intro.ipynb  02-tidy.ipynb  03-apply.ipynb  04-plots.ipynb  05-model.ipynb  Untitled.ipynb

If I wanted to access data in my notebooks I'd have to use ../data

In [5]: !ls ../data
billboard.csv  country_timeseries.csv  gapminder.tsv  pew.csv  table1.csv  table2.csv  table3.csv  table4a.csv  table4b.csv  weather.csv

However, with there here function, I can access my data all from the project root. This means if I move the notebook to another folder or subfolder I don't have to change the path to my data. Only if I move the data to another folder would I need to change the path in my notebook (or script)

In [6]: pd.read_csv(here('./data/gapminder.tsv'), sep='\t').head()
Out[6]:
       country continent  year  lifeExp       pop   gdpPercap
0  Afghanistan      Asia  1952   28.801   8425333  779.445314
1  Afghanistan      Asia  1957   30.332   9240934  820.853030
2  Afghanistan      Asia  1962   31.997  10267083  853.100710
3  Afghanistan      Asia  1967   34.020  11537966  836.197138
4  Afghanistan      Asia  1972   36.088  13079460  739.981106

By the way, you get a pathlib object path back!

In [7]: here('./data/gapminder.tsv')
Out[7]: PosixPath('/home/dchen/git/hub/scipy-2019-pandas/data/gapminder.tsv')