semvec/pypi-packages huggingface dataset:
nikmas 0.1.1
Collection of useful utils for python projects.
Requires Python: >=3.9,<4.0
Keywords: utils

# Nikmas' library

Collection of useful utils for python projects.

## Installation

```
pip install nikmas
```

## Get started

### Get all custom class attribute names

```Python
from nikmas.utils import get_custom_attribute_names


class Custom:
    a = 1
    b = 2
    c = 3


attrs_from_class_object_itself = get_custom_attribute_names(Custom)
# result -> ["a", "b", "c"]

instance = Custom()
attrs_from_class_instance = get_custom_attribute_names(instance)
# result -> ["a", "b", "c"]
```
dkube-cli 0.1.1
CLI tool to operate dkube from command line
Requires Python: >=3.5
Keywords: dkube_cli

=========
DKube CLI
=========






CLI tool to operate dkube from command line



Features
--------

* TODO

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2021-01-08)
------------------

* First release on PyPI.
aimsprop 0.2.2
A repository for the representation and manipulation of AIMS-type trajectories.
Requires Python: >=3.6

# aimsprop

To use aimsprop, check out the documentation [here](https://mtzgroup.github.io/aimsprop/)!

To develop / contribute to the aimsprop code,
see [CONTRIBUTING.md](https://mtzgroup.github.io/aimsprop/CONTRIBUTING/) to get your environment and branch set up.

For a tutorial on the basic functionality of aimsprop, go [here](https://mtzgroup.github.io/aimsprop/tutorial/).

## Description

A repository for the representation and manipulation of AIMS-type trajectories, particularly for use in computing
time-dependent properties (bond lengths, angles, torsions, X-ray scattering, UED, photoelectron, UV-Vis, etc) in a
semi-uniform manner.

## Directories

- aimsprop - the Python AIMS trajectory/property code
- docs - mkdocs documentation that is published [here](https://mtzgroup.github.io/aimsprop/)
- tests - unit tests for aimsprop code using pytest
- notes - notes used in implementing
- literature - key papers/book chapters used in implementing certain properties.
- scripts - utility scripts for common ops like plotting absorption spectra, generating difference densities from Molden
  files, etc (no warrenty on these - the usual workflow is to copy these into your own project directories and modify
  until they work)
- examples - examples of use cases of property computations (these are not the most helpful, better to look at
  the [tutorial](https://github.com/mtzgroup/aimsprop/blob/develop/docs/tutorial.md)).

## Todos

- H-Bond coordinates
- Better UED cross sections
- OOP angles
- Update examples
- Adiabatic dynamics are weirdly done in 0.5 fs, non-adiabatic dynamics are in 20 au. These are not the same. We should
  fix/accomodate this.

## Authors

Rob Parrish, Monika Williams, Hayley Weir, Colton Hicks, Alice Walker, Alessio Valentini
matrix-odin-morphology 0.0.1
A software for inferring morphological rules from linguistically annotated data
Requires Python: >=3.6

# README #


### What is this repository for? ###

* This repo hosts a version of MOM sofware, originally developed by David Wax in 2014.
* It was later significantly changed by Olga Zamaraeva.
* It is part of the AGGREGATION project
* The software helps infer morphological position classes (slots) from interlinearized data.


### What to cite if I use MOM for my research? ###
* [Wax, David Allen. Automated grammar engineering for verbal morphology. Diss. 2014.](https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/25373/Wax_washington_0250O_12899.pdf?sequence=1&isAllowed=y)
* [Zamaraeva, Olga. Inferring Morphotactics from Interlinear Glossed Text: Combining Clustering and Precision Grammars. SIGMORPHON 2016 (2016): 141.](http://www.anthology.aclweb.org/W/W16/W16-20.pdf#page=153)

### How do I get set up? ###

* Please see the [Wiki](https://bitbucket.org/olzama/mom/wiki/). Most of the info is there, some may be outdated.

* There are dependencies; you should be able to easily install them by pip, but you may need to manually install Graphviz.

* You will need a config file. Please see a sample eng_config under config_files, ass well as documented_config for comments.

* You will need some files, particularly files containing what the program will treat as gloss grams and POS tags. See mom/util/collect_tags_xigt.py

* For morphosyntactic features, the program relies on FeatDict.py. mom/util/collect_tags_xigt.py will report if it finds grams that are not yet mapped to anything in FeatDict.py. Please enter them there manually, all lowercased, to whichever dictionary you think they should belong.

### Who do I talk to? ###

* Please contact Emily M. Bender about the AGGREGATION project and ask who is currently working on MOM. 
* You can also contact olga.zamaraeva@ (geeeeemail), who may or may not be able to help you at this point (she will try).