semvec/pypi-packages huggingface dataset:
tox2travis 1.1
Automatically generate .travis.yml or GitHub actions workflow .yml from tox.ini
License: MIT
Requires Python: >=3.6

# tox2travis

![Python package](https://github.com/mineo/tox2travis/workflows/Python%20package/badge.svg)
[![Build Status](https://travis-ci.org/mineo/tox2travis.svg?branch=master)](https://travis-ci.org/mineo/tox2travis)

After installing, simply call `tox2travis` in a directory that
contains a `tox.ini` file. A `.travis.yml` file will be generated.

`tox2travis` will be able to map environment names using tox's
[default
environments](https://tox.readthedocs.io/en/latest/example/basic.html#a-simple-tox-ini-default-environments)
to the correct python version on Travis automatically.

## Non-standard environment names

If an environment name does not match one of the default environments
provided by tox, tox2travis will simply ignore it. To specify a python
version for such environments, use the `--fallback-python` command line
argument:

```
tox2travis --fallback-python pythonx.y
```

The value passed to the argument must be a valid
[basepython](https://tox.readthedocs.io/en/latest/config.html#conf-basepython).

## Custom basepython

If environments specified in `tox.ini` use a
[basepython](https://tox.readthedocs.io/en/latest/config.html#conf-basepython)
that can not be automatically mapped to one of the supported python
versions on Travis, use the `--custom-mapping` command line argument:

```
tox2travis --custom-mapping <basepython> <travis-python>
```

## GitHub Actions

Despite the name, `tox2travis` can also generate a configuration file
for [GitHub Actions](https://github.com/features/actions). Simply call
`tox2travis --output=actions` in a directory that contains a
`tox.ini` file. A new file `.github/workflows/tox.yml` will be
generated.
blob-cli 0.0.2
Azure Blob Shell Command
License: MIT
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*

=======================================
blob-cli: Azure Blob Shell Command
=======================================

.. image:: https://img.shields.io/pypi/v/blob-cli.svg
   :target: https://pypi.org/project/blob-cli/
   :alt: Latest Release

========
Overview
========

+ Wapper azure-storage-blob for help you operate blob
+ Operate blob by set environment variables(AZURE_STORAGE_ACCOUNT, AZURE_CONTAINER_NAME, AZURE_ACCESS_KEY)
+ AZURE_ACCESS_KEY can be Access Key or Shared Access Signature
+ provide shell commands: blob_list, blob_tier, blob_upload, blob_download, blob_delete

$ export AZURE_STORAGE_ACCOUNT=azureblobcliaccounttest  

$ export AZURE_CONTAINER_NAME=azureblobclicontainertest  

$ export AZURE_BLOB_KEY=azureblobcliaccounttest_SAS_token  

$ blob_list  

$ # upload and set archive tier  

$ ls -l | awk 'NR>3{print $9}' | xargs -n 1 -P 4 -I filename blob_upload -f filename -bf archive_folder -t archive

=======
License
=======

blob-cli is distributed under the `MIT license <http://www.opensource.org/licenses/mit-license.php>`_.
imagecaptioning-aeye 0.1.6
The Image Captioning module for the A-eye project.
License: MIT
Requires Python: >=3.6

imagecaptioning-aeye
==============================

The Image Captioning module for the A-eye project.

Project Organization
------------

    ├── LICENSE
    ├── Makefile           <- Makefile with commands like `make data` or `make train`
    ├── README.md          <- The top-level README for developers using this project.
    ├── data
    │   ├── external       <- Data from third party sources.
    │   ├── interim        <- Intermediate data that has been transformed.
    │   ├── processed      <- The final, canonical data sets for modeling.
    │   └── raw            <- The original, immutable data dump.
    │
    ├── docs               <- A default Sphinx project; see sphinx-doc.org for details
    │
    ├── models             <- Trained and serialized models, model predictions, or model summaries
    │
    ├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
    │                         the creator's initials, and a short `-` delimited description, e.g.
    │                         `1.0-jqp-initial-data-exploration`.
    │
    ├── references         <- Data dictionaries, manuals, and all other explanatory materials.
    │
    ├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
    │   └── figures        <- Generated graphics and figures to be used in reporting
    │
    ├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
    │                         generated with `pip freeze > requirements.txt`
    │
    ├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
    ├── src                <- Source code for use in this project.
    │   ├── __init__.py    <- Makes src a Python module
    │   │
    │   ├── data           <- Scripts to download or generate data
    │   │   └── make_dataset.py
    │   │
    │   ├── features       <- Scripts to turn raw data into features for modeling
    │   │   └── build_features.py
    │   │
    │   ├── models         <- Scripts to train models and then use trained models to make
    │   │   │                 predictions
    │   │   ├── predict_model.py
    │   │   └── train_model.py
    │   │
    │   └── visualization  <- Scripts to create exploratory and results oriented visualizations
    │       └── visualize.py
    │
    └── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io


--------

<p><small>Project based on the <a target="_blank" href="https://drivendata.github.io/cookiecutter-data-science/">cookiecutter data science project template</a>. #cookiecutterdatascience</small></p>