Project-oriented workflow in Python
Project description
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
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')
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