semvec/pypi-packages huggingface dataset:
aligned-bert-embedder 0.81
Module for generating aligned contextualized bert embeddings using different strategies

# get_aligned_BERT_emb
Get the aligned BERT embedding for sequence labeling tasks 
## Installing as a dependency
```shell script
pip install aligned-bert-embedder
```
## Installing dependencies
```shell script
conda env create -f environment.yml
```
## Example of usage from cmd (not recommended):
```shell script
python -m aligned_bert_embedder embed aligned_bert_embedder/configs/snip.yml aligned_bert_embedder/texts/triple.txt
```
## Example of usage from code (preferable)
```shell script
from aligned_bert_embedder import AlignedBertEmbedder

embeddings = AlignedBertEmbedder(config).embed(
  (
    (
      'First', `sentence`, `or`, `other`, `context`, `chunk`
    ),
    (
      `Second`, `sentence`
    )
  )
)
```

**The following is the content of the original `README.md` file from the developer repo.**

## Why this repo?

In the origin script [extract_features.py](https://github.com/google-research/bert/blob/master/extract_features.py) in BERT, tokens may be splited into pieces as follows:

```python
orig_tokens = ["John", "Johanson", "'s",  "house"]
bert_tokens = ["[CLS]", "john", "johan", "##son", "'", "s", "house", "[SEP]"]
orig_to_tok_map = [1, 2, 4, 6]
```
We investigate 3 align strategies (`first`, `mean` and `max`) to maintain an original-to-tokenized alignment. Take the "`Johanson` -> `johan`, `##son`" as example:

+ `first`: take the representation of `johan` as the whole word `Johanson`
+ `mean`: take the reduce_mean value of representations of `johan` and `##son` as the whole word `Johanson`
+ `max`: take the reduce_max value of representations of `johan` and `##son` as the whole word `Johanson`


## How to use this repo?

```shell
sh run.sh input_file outout_file BERT_BASE_DIR
# For example:
sh run.sh you_data you_data.bert path/to/bert/uncased_L-12_H-768_A-12 
```
You can modify `layers` and `align_strategies` in the `run.sh`.


## How to load the output embeddings?

After the above procedure, you are expected to get a output file of contextual embeddings (e.g., your_data_6_mean). Then you can load this file like conventional word embeddings. For example in a python script:
```python
with open("your_data_6_mean", "r", encoding="utf-8") as bert_f"
    for line in bert_f:
        bert_vec = [[float(value) for value in token.split()] for token in line.strip().split("|||")] 
```
hex-gym 1.0.0
A OpenAi Gym Environment for a hexapod

<h1>Hexapod OpenAi Gym environment</h1>
<p>Uses an urdf file to import the pod in an GUI environment</p>
* Used fuzzy logic for the reward.<br>
* The reward function was calculated as the ratio of other observations with the displacement in x direction.<br>
<i>author: unicorn-io
mox3 1.1.0
Mock object framework for Python
Requires Python: >=3.6

=========================================
Mox3 - Mock object framework for Python 3
=========================================

.. image:: https://governance.openstack.org/tc/badges/mox3.svg
    :target: https://governance.openstack.org/tc/reference/tags/index.html

Mox3 is an unofficial port of the Google mox framework
(http://code.google.com/p/pymox/) to Python 3. It was meant to be as compatible
with mox as possible, but small enhancements have been made. The library was
tested on Python version 3.2, 2.7 and 2.6.

Use at your own risk ;)

To install:

  $ python setup.py install

Running Tests
-------------
The testing system is based on a combination of tox and testr. The canonical
approach to running tests is to simply run the command `tox`. This will
create virtual environments, populate them with depenedencies and run all of
the tests that OpenStack CI systems run. Behind the scenes, tox is running
`testr run --parallel`, but is set up such that you can supply any additional
testr arguments that are needed to tox. For example, you can run:
`tox -- --analyze-isolation` to cause tox to tell testr to add
--analyze-isolation to its argument list.

It is also possible to run the tests inside of a virtual environment
you have created, or it is possible that you have all of the dependencies
installed locally already. In this case, you can interact with the testr
command directly. Running `testr run` will run the entire test suite. `testr
run --parallel` will run it in parallel (this is the default incantation tox
uses.) More information about testr can be found at:
https://wiki.openstack.org/wiki/Testr

Basic Usage
-----------

The basic usage of mox3 is the same as with mox, but the initial import should
be made from the mox3 module:

  from mox3 import mox

To learn how to use mox3 you may check the documentation of the original mox
framework:

  http://code.google.com/p/pymox/wiki/MoxDocumentation

Original Copyright
------------------

Mox is Copyright 2008 Google Inc, and licensed under the Apache
License, Version 2.0; see the file COPYING.txt for details.  If you would
like to help us improve Mox, join the group.

OpenStack Fork
--------------

* Free software: Apache license
* Documentation: https://docs.openstack.org/mox3/latest/
* Source: https://opendev.org/openstack/mox3
* Bugs: https://bugs.launchpad.net/python-mox3
aioelasticsearch 0.7.0
elasticsearch-py wrapper for asyncio
Requires Python: >=3.5.3
Keywords: elasticsearch,asyncio,aiohttp

aioelasticsearch
================

:info: elasticsearch-py wrapper for asyncio

.. image:: https://img.shields.io/travis/aio-libs/aioelasticsearch.svg
    :target: https://travis-ci.org/aio-libs/aioelasticsearch

.. image:: https://img.shields.io/pypi/v/aioelasticsearch.svg
    :target: https://pypi.python.org/pypi/aioelasticsearch

.. image:: https://codecov.io/gh/aio-libs/aioelasticsearch/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/aio-libs/aioelasticsearch

Installation
------------

.. code-block:: shell

    pip install aioelasticsearch

Usage
-----

.. code-block:: python

    import asyncio

    from aioelasticsearch import Elasticsearch

    async def go():
        es = Elasticsearch()

        print(await es.search())

        await es.close()

    loop = asyncio.get_event_loop()
    loop.run_until_complete(go())
    loop.close()

Features
--------

Asynchronous `scroll <https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-scroll.html>`_

.. code-block:: python

    import asyncio

    from aioelasticsearch import Elasticsearch
    from aioelasticsearch.helpers import Scan

    async def go():
        async with Elasticsearch() as es:
            async with Scan(
                es,
                index='index',
                doc_type='doc_type',
                query={},
            ) as scan:
                print(scan.total)

                async for doc in scan:
                    print(doc['_source'])

    loop = asyncio.get_event_loop()
    loop.run_until_complete(go())
    loop.close()

Thanks
------

The library was donated by `Ocean S.A. <https://ocean.io/>`_

Thanks to the company for contribution.
kivyIsoDatepicker 1.0.2
Python 3.3+ version of Oleg Kozlov KivyCalandar in ISO 8601 date format
Requires Python: >=3.3

# datepicker
DatePicker for Kivy - Python 3.3+

Adaptation of [Skucul/datepicker](https://github.com/Skucul/datepicker) to use the ISO 8601 date format, which is an adaptation of [KivyCalendar](https://bitbucket.org/xxblx/kivycalendar) to work on Python 3.3+. 
Credits to  [Oleg Kozlov (xxblx)](https://xxblx.bitbucket.org)
v13r93w1nn7 0.0.6
extended version of the board game «Vier gewinnt»
Requires Python: >=3.8

# v13r93w1nn7

Extended version of the board game «Vier gewinnt» (four in a row).

Run the default version:

    ./v13r93w1nn7/game.py

Run an extended version with additional neutral stones being placed at random positions:

    ./v13r93w1nn7/game.py --neutral

Run an extended version that allows the field to be rotated by 90°:

    ./v13r93w1nn7/game.py --rotate

Run an extended version that adds both features:

    ./v13r93w1nn7/game.py --neutral --rotate
moic 1.3.1
My Own Issue CLI (Jira, Gitlab etc...)
Requires Python: >=3.7,<4.0

# MOIC : My Own Issue CLI

> Freely inspired by https://pypi.org/project/jira-cli/

Command line inteface to interact with issue manager such as Jira, Gitlab, etc...

**Highlights**
* Modern CLI based on [Click](https://click.palletsprojects.com/en/7.x/) and [Rich](https://github.com/willmcgugan/rich)
* Context management
* Multiple tracker plugin
* Uniformed display

## Getting Started

* Install moic
```bash
> pip install moic
```

* Configure moic
```bash
> moic configure
```

* Commands
```bash
> moic
Usage: moic [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  config    Configure Jira cli, setting up instance, credentials etc...
  issue     Create, edit, list Jira issues
  list      List projects, issue_types, priorities, status
  rabbit    Print an amazing rabbit: Tribute to @fattibenji...
  sprint    Create, edit, list Jira Sprints
  template  List, edit templates
  version   Provide the current moic installed version
```

## Contribute

Feel free [open issues on Gitlab](https://gitlab.com/brice.santus/moic/-/issues) or propose Merge Requests

## Documentation

Full documentation is available at https://moic.readthedocs.io/en/latest/
minegen 2.0.3
Minecraft achievement generator
Keywords: minecraft achievement generator

# minegen

![](https://img.shields.io/badge/version-2.0-lightgrey) ![](https://img.shields.io/badge/python-3%2B-blue) ![](https://img.shields.io/badge/pillow-5.4.1%2B-orange) ![](https://img.shields.io/badge/license-MIT-green)

**MINE**craft achievement **GEN**erator with Python.</br>
For information on achievement: [minecraft.gamepedia.com/Achievements](https://minecraft.gamepedia.com/Achievements)

### Availability
Only GNU/Linux

## Installing
```sh
git clone https://github.com/adlgrbz/minegen
```

Install via pip:
```sh
cd minegen
pip3 install .
```

## Usage
To generate achievement:
```sh
minegen -t Diamonds! -b "Acquire diamonds" -i diamond
```
output.png
> ![output.png](https://raw.githubusercontent.com/adlgrbz/minegen/master/minegen/data/output.png)

To get the Item list:
```sh
minegen -l
```

You can get more information by doing:
```sh
minegen --help
```

Modular use:
```py
>>> import mingen
>>> items = minegen.items
>>> minegen.generate(["Monsters Hunted", "Kill one of every hostile monster"], "sword")
Successful!
```

## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details