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Parametric file paths to access and build structured folder trees.
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It almost doesn't have Dependencies, check how to Install it.
Github repository: https://github.com/alexsavio/hansel
Imagine this folder tree:
::
data
└── 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
.. code:: python
>>> from pprint import pprint
>>> from hansel import Crumb
# create the crumb
>>> crumb = Crumb("{base_dir}/raw/{subject_id}/{session_id}/{image_type}/{image}")
# set the base_dir path
>>> crumb = crumb.replace(base_dir='/tmp/hansel/data')
>>> print(str(crumb))
/tmp/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}
# get the ids of the subjects
>>> subj_ids = crumb['subject_id']
>>> print(subj_ids)
['0040000', '0040001', '0040002', '0040003', '0040004', '0040005', ...
# get the paths to the subject folders, the output can be strings or crumbs,
# you choose with the ``make_crumbs`` boolean argument. Default: True.
>>> subj_paths = crumb.ls('subject_id', make_crumbs=True)
>>> pprint(subj_paths)
[Crumb("/tmp/hansel/data/raw/0040000/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040001/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040002/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040003/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040004/{session_id}/{image_type}/{image}"),
...
# set the image_type
>>> anat_crumb = crumb.replace(image_type='anat_1')
>>> print(anat_crumb)
/tmp/hansel/data/raw/{subject_id}/{session_id}/anat_1/{image}
# get the paths to the images inside the anat_1 folders
>>> anat_paths = anat_crumb.ls('image')
>>> pprint(anat_paths)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040002/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040003/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040004/session_1/anat_1/mprage.nii.gz"),
...
# get the ``session_id`` of each of these ``anat_paths``
>>> sessions = [cr['session_id'][0] for cr in anat_paths]
>>> print(sessions)
['session_1', 'session_1', 'session_1', 'session_1', 'session_1', ...
# if you don't want the the output to be ``Crumbs`` but string paths:
>>> anat_paths = anat_crumb.ls('image', make_crumbs=False)
>>> pprint(anat_paths)
['/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz',
'/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz',
'/tmp/hansel/data/raw/0040002/session_1/anat_1/mprage.nii.gz',
'/tmp/hansel/data/raw/0040003/session_1/anat_1/mprage.nii.gz',
'/tmp/hansel/data/raw/0040004/session_1/anat_1/mprage.nii.gz',
...
# you can also use a list of ``fnmatch`` expressions to ignore certain files patterns
# using the ``ignore_list`` argument in the constructor.
# For example, the files that start with '.'.
>>> crumb = Crumb("{base_dir}/data/raw/{subject_id}/{session_id}/{image_type}/{image}", ignore_list=['.*'])
Once you have a fully defined Crumb, you can use its path for operations with the corresponding file.
For that you have to convert it to string by using str(crumb) or crumb.path.
See more quick examples after the Long Intro_ check More features and tricks_.
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:
...data/raw,0040000,session_1 andanat_1 and rest_1.With hansel I can represent this folder structure like this:
.. code:: python
>>> from hansel import Crumb
>>> crumb = Crumb("{base_dir}/data/raw/{subject_id}/{session_id}/{image_type}/{image}")
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:
.. code:: python
>>> crumb = crumb.replace(base_dir='/home/hansel')
>>> print(str(crumb))
/home/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}
if I don't need a copy of crumb, I can use the [] operator:
.. code:: python
>>> crumb['base_dir'] = '/tmp/hansel'
>>> print(str(crumb))
/tmp/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}
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_id folders:
We can use the ls function. Its output can be str or Crumb.
I can choose this using the make_crumbs argument (default: True):
.. code:: python
>>> subj_crumbs = crumb.ls('subject_id')
>>> pprint(subj_crumbs)
[Crumb("/tmp/hansel/data/raw/0040000/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040001/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040002/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040003/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/0040004/{session_id}/{image_type}/{image}"),
...
>>> subj_paths = crumb.ls('subject_id', make_crumbs=False)
>>> pprint(subj_paths)
['/tmp/hansel/data/raw/0040000/{session_id}/{image_type}/{image}',
'/tmp/hansel/data/raw/0040001/{session_id}/{image_type}/{image}',
'/tmp/hansel/data/raw/0040002/{session_id}/{image_type}/{image}',
'/tmp/hansel/data/raw/0040003/{session_id}/{image_type}/{image}',
'/tmp/hansel/data/raw/0040004/{session_id}/{image_type}/{image}',
...
If I want to know what are the existing subject_id:
.. code:: python
>>> subj_ids = crumb.ls('subject_id', fullpath=False)
>>> print(subj_ids)
['0040000', '0040001', '0040002', '0040003', '0040004', '0040005', ...
or
.. code:: python
>>> subj_ids = crumb['subject_id']
>>> print(subj_ids)
['0040000', '0040001', '0040002', '0040003', '0040004', '0040005', ...
Now, if I wanted to get the path to all the images inside the anat_1 folders,
I could do this:
.. code:: python
>>> anat_crumb = crumb.replace(image_type='anat_1')
>>> print(anat_crumb)
/tmp/hansel/data/raw/{subject_id}/{session_id}/anat_1/{image}
or if I don't need to keep a copy of crumb:
.. code:: python
>>> crumb['image_type'] = 'anat_1'
# get the paths to the images inside the anat_1 folders
>>> anat_paths = crumb.ls('image')
>>> pprint(anat_paths)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040002/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040003/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040004/session_1/anat_1/mprage.nii.gz"),
...
Remember that I can still access the replaced crumb arguments in each of the previous
crumbs in anat_paths.
.. code:: python
>>> subj_ids = [cr['subject_id'][0] for cr in anat_paths]
>>> print(subj_ids)
['0040000', '0040001', '0040002', '0040003', '0040004', ...
>>> files = [cr['image'][0] for cr in anat_paths]
>>> print(files)
['mprage.nii.gz', 'mprage.nii.gz', 'mprage.nii.gz', 'mprage.nii.gz', ...
There are more possibilities such as:
Creating folder trees
Use `mktree` and `ParameterGrid` to create a tree of folders.
.. code:: python
>>> from hansel import mktree
>>> from hansel.utils import ParameterGrid
>>> crumb = Crumb("/tmp/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}")
>>> session_ids = ["session_{}".format(i) for i in range(2)]
>>> subject_ids = ["subj_{}".format(i) for i in range(3)]
>>> values_map = dict(session_id=session_ids, subject_id=subject_ids)
>>> crumbs = mktree(crumb, list(ParameterGrid(values_map)))
>>> pprint(crumbs)
[Crumb("/tmp/hansel/data/raw/subj_0/session_0/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/subj_1/session_0/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/subj_2/session_0/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/subj_0/session_1/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/subj_1/session_1/{image_type}/{image}"),
Crumb("/tmp/hansel/data/raw/subj_2/session_1/{image_type}/{image}")]
Check the feasibility of a crumb path
.. code:: python
>>> crumb = Crumb("/tmp/hansel/raw/{subject_id}/{session_id}/{image_type}/{image}")
# ask if there is any subject with the image 'lollipop.png'.
>>> crumb['image'] = 'lollipop.png'
>>> assert not crumb.exists()
Check which subjects have 'jujube.png' and 'toffee.png' files
.. code:: python
>>> crumb = Crumb("/tmp/hansel/raw/{subject_id}/{session_id}/{image_type}/{image}")
>>> toffee_crumb = crumb.replace(image='toffee.png')
>>> jujube_crumb = crumb.replace(image='jujube.png')
# using sets functionality
>>> gluttons = set(toffee_crumb['subject_id']).intersection(set(jujube_crumb['subject_id']) # doctest: +SKIP
>>> print(gluttons) # doctest: +SKIP
['gretel', 'hansel']
Use the `intersection` function
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Use it for comparisons on more than one crumb argument.
This can be used to compare datasets with the same structure in different folders.
*One argument*
Imagine that we have two working folders of subjects for two different projects: `proj1` and `proj2`.
If I want to check what subjects are common to both projects:
.. code:: python
>>> from hansel import intersection
# using one argument
>>> cr_proj1 = Crumb("/tmp/hansel/data/proj1/{subject_id}/{session_id}/{image_type}/{image}")
>>> cr_proj2 = Crumb("/tmp/hansel/data/proj2/{subject_id}/{session_id}/{image_type}/{image}")
# set the `on` argument in `intersection` to specify which crumb arguments to merge.
>>> merged = intersection(cr_proj1, cr_proj2, on=['subject_id'])
>>> pprint(merged)
[(('subject_id', '0040006'),),
(('subject_id', '0040007'),),
(('subject_id', '0040008'),),
(('subject_id', '0040009'),)]
# I can pick these subject crumbs from this result using the `build_paths` function.
>>> proj1_merged_paths = cr_proj1.build_paths(merged, make_crumbs=True)
>>> type(proj1_merged_paths)
<class 'generator'>
>>> pprint(list(proj1_merged_paths))
[Crumb("/tmp/hansel/data/proj1/0040006/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj1/0040007/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj1/0040008/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj1/0040009/{session_id}/{image_type}/{image}")]
>>> pprint(list(cr_proj2.build_paths(merged, make_crumbs=True)))
[Crumb("/tmp/hansel/data/proj2/0040006/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj2/0040007/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj2/0040008/{session_id}/{image_type}/{image}"),
Crumb("/tmp/hansel/data/proj2/0040009/{session_id}/{image_type}/{image}")]
*Two arguments*
Now, imagine that I have different sets of `{image}` for these subjects.
I want to check which of those subjects have exactly the same images.
Let's say that the subject `0040000` has a `anatomical.nii.gz` instead of `mprage.nii.gz`.
.. code:: python
>>> from hansel import intersection
# using one argument
>>> cr_proj3 = Crumb("/tmp/hansel/data/proj3/{subject_id}/{session_id}/anat_1/{image}")
>>> cr_proj4 = Crumb("/tmp/hansel/data/proj4/{subject_id}/{session_id}/anat_1/{image}")
# set the `on` argument in `intersection` to specify which crumb arguments to merge.
>>> merged = intersection(cr_proj3, cr_proj4, on=['subject_id', 'image'])
>>> pprint(merged)
[(('subject_id', '0040001'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040002'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040003'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040004'), ('image', 'mprage.nii.gz')),
...
# I can pick these image crumbs from this result using the `build_paths` function.
>>> pprint(list(cr_proj3.build_paths(merged, make_crumbs=True)))
[Crumb("/tmp/hansel/data/proj3/0040001/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj3/0040002/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj3/0040003/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj3/0040004/{session_id}/anat_1/mprage.nii.gz"),
...
>>> pprint(list(cr_proj4.build_paths(merged, make_crumbs=True)))
[Crumb("/tmp/hansel/data/proj4/0040001/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj4/0040002/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj4/0040003/{session_id}/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/proj4/0040004/{session_id}/anat_1/mprage.nii.gz"),
...
# adding 'mod' to the intersection would be:
>>> common_values = intersection(cr_proj3, cr_proj4, on=['subject_id', 'session_id', 'image'])
>>> pprint(common_values, width=120)
[(('subject_id', '0040001'), ('session_id', 'session_1'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040002'), ('session_id', 'session_1'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040003'), ('session_id', 'session_1'), ('image', 'mprage.nii.gz')),
(('subject_id', '0040004'), ('session_id', 'session_1'), ('image', 'mprage.nii.gz')),
...
The `unfold` and `ls` functions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Unfold the whole crumb path to get the whole file tree in a list of paths:
.. code:: python
>>> all_images = Crumb("/tmp/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}")
>>> all_images = all_images.unfold()
>>> pprint(all_images)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040000/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040002/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040002/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040003/session_1/anat_1/mprage.nii.gz"),
...
# and you can ask for the value of the crumb argument in each element
>>> print(all_images[0]['subject_id'])
['0040000']
Note that `unfold` is the same as calling `ls` function without arguments.
Use regular expressions
~~~~~~~~~~~~~~~~~~~~~~~
Use ``re.match`` or ``fnmatch`` expressions to filter the paths:
The syntax for crumb arguments with a regular expression is: ``"{<arg_name>:<arg_regex>}"``
.. code:: python
# only the session_1 folders
>>> session1_cr = Crumb("/tmp/hansel/data/raw/{subject_id}/{session_id:*_1}/{image_type}/{image}")
>>> session1_imgs = session1_cr.ls()
>>> pprint(session1_imgs)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040000/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/rest_1/mprage.nii.gz"),
...
The default is for ``fnmatch`` expressions. If you prefer using ``re.match`` for filtering,
set the ``regex`` argument to ``'re'`` or ``'re.ignorecase'`` in the constructor.
.. code:: python
# only the rest images from the subject ``040000``
>>> s0_rest_cr = Crumb("/tmp/hansel/data/raw/{subject_id:.*00$}/{session_id}/{image_type:rest.*}/{image}", regex='re')
>>> s0_rest_imgs = s0_rest_cr.ls()
>>> print(s0_rest_imgs)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/rest_1/mprage.nii.gz")]
The regular expressions can be checked with the `patterns` property.
.. code:: python
>>> pprint(s0_rest_cr.patterns)
{'image_type': 'rest.*', 'subject_id': '.*00$'}
And can be also modified with the `set_pattern` function.
.. code:: python
>>> s0_rest_cr.set_pattern('session_id', '.*_1$')
>>> pprint(s0_rest_cr.patterns)
{'image_type': 'rest.*', 'session_id': '.*_1$', 'subject_id': '.*00$'}
>>> s0_rest_cr.path
'/tmp/hansel/data/raw/{subject_id:.*00$}/{session_id:.*_1$}/{image_type:rest.*}/{image}'
A regular expression can be temporarily set with the `ls` function and the `[]`
operator.
.. code:: python
>>> crumb = Crumb("/tmp/hansel/data/raw/{subject_id}/{session_id}/{image_type}/{image}")
>>> mprage_crumb = crumb.ls('image:mprage.*')
>>> pprint(mprage_crumb)
[Crumb("/tmp/hansel/data/raw/0040000/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040000/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/anat_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040001/session_1/rest_1/mprage.nii.gz"),
Crumb("/tmp/hansel/data/raw/0040002/session_1/anat_1/mprage.nii.gz"),
...
>>> pprint(crumb['image:mprage.*'])
['mprage.nii.gz',
'mprage.nii.gz',
'mprage.nii.gz',
'mprage.nii.gz',
'mprage.nii.gz',
'mprage.nii.gz',
...
Copy and modify folder structure with `crumb_copy`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Copy a folder structure from one crumb to the other. The source crumb
must be fully specified, i.e., all crumb arguments must get an existing value.
In addition the destination crumb can only have a subset of the crumb arguments
of the source crumb.
.. code:: python
>>> from hansel import Crumb, crumb_copy
>>> src_cr = Crumb("/tmp/hansel/data/raw/{subj_id}/{sess}/{type}/{img}")
>>> dst_cr = Crumb("/tmp/hansel/data/copy/{subj_id}/{sess}/{type}")
>>> crumb_copy(src_cr, dst_cr)
More functionalities, ideas and comments are welcome.
Command Line
============
`hansel` will install a command called `crumb`.
This CLI has been made with `Click <http://click.pocoo.org/>`__,
so try `crumb -h` to see more details.
You can use `Crumb.ls`:
.. code:: bash
crumb ls "/data/hansel/cobre/{sid:4*100}/{session}/{img}"
Copy one file tree to another file tree with `crumb copy`:
.. code:: bash
crumb copy "/data/hansel/cobre/{sid}/{session}/{img}" "/data/hansel/cobre2/{sid}/{img}"
Link one file tree to another file tree with `link`:
.. code:: bash
crumb link "/data/hansel/cobre/{sid}/{session}/{img}" "/data/hansel/cobre2/{sid}/{img}"
Return the intersection between crumb1 and crumb2 on a given argument with the `intersect` function:
.. code:: bash
crumb intersect --on "sid" "/data/hansel/cobre/{sid}/{session}/{img}" "/data/hansel/cobre2/{sid}/{img}"
Return the difference `crumb1 - crumb2` on a given argument with the `diff` function:
.. code:: bash
crumb diff --on "sid" "/data/hansel/cobre/{sid}/{session}/{img}" "/data/hansel/cobre2/{sid}/{img}"
Dependencies
============
Please see the requirements.txt file. Before installing this package,
install its dependencies with:
.. code:: bash
pip install -r requirements.txt
Install
=======
It works on Python 3.4, 3.5 and 2.7. For Python 2.7 install `pathlib2` as well.
This package uses setuptools. You can install it running:
.. code:: bash
python setup.py install
If you already have the dependencies listed in requirements.txt
installed, to install in your home directory, use:
.. code:: bash
python setup.py install --user
To install for all users on Unix/Linux:
.. code:: bash
python setup.py build
sudo python setup.py install
You can also install it in development mode with:
.. code:: bash
python setup.py develop
Development
===========
Code
----
Github
~~~~~~
You can check the latest sources with the command:
.. code:: bash
git clone https://www.github.com/alexsavio/hansel.git
or if you have write privileges:
.. code:: bash
git clone git@github.com:alexsavio/hansel.git
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.
Testing
-------
We are using `py.test <http://pytest.org/>`__ to help us with the testing.
Otherwise you can run the tests executing:
.. code:: bash
python setup.py test
or
.. code:: bash
py.test
or
.. code:: bash
make test
.. |PyPI| image:: https://img.shields.io/pypi/v/hansel.svg
:target: https://pypi.python.org/pypi/hansel
.. |Build Status| image:: https://travis-ci.org/alexsavio/hansel.svg?branch=master
:target: https://travis-ci.org/alexsavio/hansel
.. |Coverage Status| image:: https://coveralls.io/repos/alexsavio/hansel/badge.svg?branch=master&service=github
:target: https://coveralls.io/github/alexsavio/hansel?branch=master
.. |Code Health| image:: https://landscape.io/github/alexsavio/hansel/master/landscape.svg?style=flat
:target: https://landscape.io/github/alexsavio/hansel/master
:alt: Code Health
Changelog
=========
Version 2.0.1 (25.02.2018)
--------------------------
- Add type annotations accross all code base.
- Fixed documentation. Now it README example code snippets are tested.
Version 2.0.0 (24.02.2018)
--------------------------
- Drop support for Python 2.7. Add support for Python 3.6.
Version 1.0.0 - Version 1.0.2
-----------------------------
- add CLI docs to README.
- set in `ls` function `make_crumbs` to False if `fullpath` is also False.
- make in `ls` function `arg_name` parameter mandatory when `fullpath` is False.
Version 0.9.0 - 0.9.6
---------------------
- "cli diff" and "cli intersect" have the same interface.
- changed how "cli intersect" prints results. Added 'base_crumb' option.
- added to CLI default ignore list for crumbs: `['.*']`.
- add `crumb diff` to CLI.
- add `difference` utility function with test.
- add `test__utils.py` as a WIP.
- move CLI to click.
- Annoying bug fixed.
- Add `crumb_copy`.
- Now it doesn't bother with relative paths.
- Fix `crumb_copy` for existing paths and linking relative paths.
- Add `crumb_copy` CLI.
- Make `click` a dependency and move `crumb_copy` to `crumb copy`.
- Add `crumb ls` and `crumb intersect` CLI.
- Add `is_crumb_arg` function to utils.
- Fix error in `crumb copy` parameter names.
Version 0.8.0 - 0.8.3
---------------------
- Set to True the default value for `check_exists` in `Crumb.ls` function.
I don't think anybody is interested in non-existing paths.
- Now it is possible to set a non-open item in a Crumb, i.e., I can replace the value for an already set crumb argument.
- Update README.rst
- Code clean-up.
- Replace dict to OrderedDict output in `valuesmap_to_dict` function.
- Add regex option within `arg_name` argument of `ls` and `__get_item__`.
Version 0.7.0 - 0.7.5
---------------------
- Refactoring of how Crumb works, now using string.Formatter.
This will help with new features due to simpler logic.Now it is not possible to change the syntax of the Crumbs,
although I guess nobody is interested in that.
- Fixed a few bugs from previous versions.
- Now `copy` function is not a classmethod anymore, so you can do `crumb.copy()` as well as `Crumb.copy(crumb)`.
- `patterns` is not a dictionary anymore, the regexes are embedded in the `_path` string.
The property `patterns` returns the dictionary as before. The function `set_pattern` must be used instead to set a different pattern to a given argument.
- Update README.rst
- Fix README.rst because of bad syntax for PyPI.
- Fix bug for Python 2.7
- Fix the bug in .rst for PyPI.
- Code cleanup
Version 0.6.0 - 0.6.2
---------------------
- Added `intersection` function in `utils.py`.
- Change of behaviour in `__getitem__`, now it returns a list of values even if is only the one replace string from `_argval`.
- General renaming of the private functions inside Crumbs, more in accordance to the `open_args`/`all_args` idea.
- Fixed a few bugs and now the generated crumbs from `unfold` and `ls` will have the same parameters as the original Crumb.
- Change the behaviour or `intersection` with `len(arg_names) == 1` for compatibility with `crumb.build_path` function.
- Improve README, update with new examples using `intersection`.
- Add `pandas` helper functions.
- Add `utils` to convert from values_maps to dicts.
- Improve docstrings.
Version 0.5.0 - 0.5.5
---------------------
- Add Python 2.7 compatibility. Friends don't let friends use Python 2.7!
- Add 're.ignorecase' option for the `regex` argument in the constructor.
- Add `utils.check_path` function.
- Fix `Crumb.split` function to return the not defined part of the crumb.
- Add `Crumbs.keys()` function.
- Rename `utils.remove_duplicates()` to `utils.rm_dups()`.
- Deprecating `Crumbs.keys()` function.
- Renamed `Crumbs.keys()` to `Crumbs.open_args()` and added `Crumbs.all_args()`.
- Substitute the internal logic of Crumbs to work with `Crumbs.open_args()`, made it a bit faster.
- Added CHANGES.rst to MANIFEST.in
Version 0.4.0 - 0.4.2
---------------------
- Fill CHANGES.rst.
- All outputs from `Crumb.ls` function will be sorted.
- Add regular expressions or `fnmatch` option for crumb arguments.
- Change `exists` behaviour. Now the empty crumb arguments will return False when `exist()`.
- Code clean up.
- Fix bugs.
- Fix CHANGES.rst to correct restview in PyPI.
- Thanks to restview: https://pypi.python.org/pypi/restview.
Use: ``restview --long-description``
- Improve documentation in README.
- Rename member `_argreg` to `patterns`, so the user can use it to manage the argument patterns.
Version 0.3.0 - 0.3.1
---------------------
- Add `_argval` member, a dict which stores crumb arguments replacements.
- Add tests.
- Remove `rm_dups` option in `Crumb.ls` function.
- Remove conversion to `Paths` when `Crumb` has no crumb arguments in `Crumb.ls`.
- Fix README.
- Code clean up.
Version 0.2.0
-------------
- Add `ignore_list` parameter in `Crumb` constructor.
Version 0.1.0 - 0.1.1
---------------------
- Simplify code.
- Increase test coverage.
- Add `exist_check` to `Crumb.ls` function.
- Fix bugs.
- Add `Crumb.unfold` function.
- Move `mktree` out of `Crumb` class.
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