Awesome
Project-oriented workflow in Python
Finding project directories in Python (data science) projects.
This library aims to provide both
the programmatic functionality from the R rprojroot
package
and the interactive functionality from the R here
package.
Motivation
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:
- Run my python scripts without having to specify a series of
../
to get to thedata
folder. 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.- 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.Path
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!
Further reading:
Installation
pip
python -m pip install pyprojroot
conda
https://anaconda.org/conda-forge/pyprojroot
conda install -c conda-forge pyprojroot
Example Usage
pyprojroot
looks for certain files like .here
or .git
to identify the here
directory. To make any of the following examples work, you'll need one of those files in the current directory or one of its parents. (For the complete list of files, see here.py.)
Interactive
This is based on the R here
library.
from pyprojroot.here import here
here()
Programmatic
This based on the R rprojroot
library.
import pyprojroot
base_path = pyprojroot.find_root(pyprojroot.has_dir(".git"))
Demonstration
Load the packages
In [1]: from pyprojroot.here 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.Path
object path back!
In [7]: here('data/gapminder.tsv')
Out[7]: PosixPath('/home/dchen/git/hub/scipy-2019-pandas/data/gapminder.tsv')