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from hansel import Crumb to find your file path.

Project description


Flexible parametric file paths to make queries, build folder trees and smart folder structure access.

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Quick Intro

Imagine this folder tree:

└── raw
    ├── 0040000
    │   └── session_1
    │       ├── anat_1
    │       └── rest_1
    ├── 0040001
    │   └── session_1
    │       ├── anat_1
    │       └── rest_1
    ├── 0040002
    │   └── session_1
    │       ├── anat_1
    │       └── rest_1
    ├── 0040003
    │   └── session_1
    │       ├── anat_1
    │       └── rest_1
    ├── 0040004
    │   └── session_1
    │       ├── anat_1
    │       └── rest_1
from hansel import Crumb

# create the crumb
crumb = Crumb("{base_dir}/data/raw/{subject_id}/{session_id}/{image_type}")

# set the base_dir path
crumb = crumb.replace('base_dir', '/home/hansel')

assert str(crumb) == "/home/hansel/data/raw/{subject_id}/{session_id}/{image_type}"

# get the ids of the subjects
subj_ids = crumb['subject_id']

assert subj_ids == ['0040000', '0040001', '0040002', '0040003', '0040004', ....]

# get the paths to the subject folders, the output can be strings or crumbs, you select
subj_paths ='subject_id', make_crumbs=True)

# set the image_type
anat_crumb = crumb.replace(image_type='anat_1')

# get the paths to the anat_1 folders
anat_paths ='image')

Long Intro

I often find myself in a work related with structured folder paths, such as the one shown above.

I have tried many ways of solving these situations: loops, dictionaries, configuration files, etc. I always end up doing a different thing for the same problem over and over again.

This week I grew tired of it and decided to make a representation of a structured folder tree in a string and access it the most easy way.

If you look at the folder structure above I have:

  • the root directory from where it is hanging:,
  • many identifiers (in this case a subject identification), e.g., 0040000,
  • session identification, session_1 and
  • a data type (in this case an image type), anat_1 and rest_1.

With hansel I can represent this folder structure like this:

from hansel import Crumb

crumb = Crumb("{base_dir}/data/raw/{subject_id}/{session_id}/{image_type}")

Let’s say we have the structure above hanging from a base directory like /home/hansel/.

I can use the replace function to make set the base_dir parameter:

crumb = crumb.replace('base_dir', '/home/hansel')

assert str(crumb) == "/home/hansel/data/raw/{subject_id}/{session_id}/{image_type}"

if you don’t need a copy of crumb, you can use the [] operator:

crumb['base_dir'] = '/home/hansel'

Now that the root path of my dataset is set, I can start querying my crumb path.

If I want to know the path to the existing subject_ids folders:

subject_paths ='subject_id')

The output of ls can be str or Crumb or pathlib.Path. They will be Path if there are no crumb arguments left in the crumb path. You can choose this using the make_crumbs argument:

subject_paths ='subject_id', make_crumbs=True)

If I want to know what are the existing subject_ids:

subject_ids ='subject_id', fullpath=False)


subject_ids = crumb['subject_id']

Now, if I wanted to get the path to all the anat_1 images, I could do this:

anat_crumb = crumb.replace(image_type='anat_1')

anat_paths ='image')


crumb['image_type'] = 'anat_1'

anat_paths ='image')

There are more features such as creating folder trees with a value of maps for the crumbs and also check the feasibility of a crumb path.

More functionalities, ideas and comments are welcome.


Please see the requirements.txt file. Before installing this package, install its dependencies with:

pip install -r requirements.txt


I am only testing this tool on Python 3.4 and 3.5. Maybe it works on Python 2.7 as well as for the parts related with strings (very few) I am using six.

This package uses setuptools. You can install it running:

python install

If you already have the dependencies listed in requirements.txt installed, to install in your home directory, use:

python install –user

To install for all users on Unix/Linux:

python build
sudo python install

You can also install it in development mode with:

python develop




You can check the latest sources with the command:

git clone

or if you have write privileges:

git clone

If you are going to create patches for this project, create a branch for it from the master branch.

We tag stable releases in the repository with the version number.


We are using py.test to help us with the testing.

Otherwise you can run the tests executing:

python test



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