semvec/pypi-packages huggingface dataset:
pyjstage 0.0.2
J-STAGE API wrapper for Python
License: MIT

# pyjstage
![GitHub Workflow Status](https://img.shields.io/github/workflow/status/matsurih/pyjstage/Python%20package)
![PyPI version](https://img.shields.io/pypi/v/pyjstage)

## Overview
[J-STAGE WebAPI](https://www.jstage.jst.go.jp/static/pages/OtherJstageServices/TAB2/-char/ja) Wrapper for Python3.
- J-STAGE is an electronic journal platform for science and technology information in Japan, developed and managed by the Japan Science and Technology Agency (JST). 

## Prerequisites
- Python >= 3.6

## Setup
```shell script
$ pip install pyjstage
```

## Usage
You can try this library like this:

```python
from pyjstage.pyjstage import Pyjstage


jstage = Pyjstage()

ret_search = jstage.search(issn='2186-6619', count=1)
ret_list = jstage.list(issn='2186-6619')

# ret_(search/list) is a (Search/List)Result Object.
```

If you need more information, see function-definitions in jstage/jstage.py (Sorry for no documentation... I'll write later.)

## License
- MIT License, see [LICENSE](https://github.com/matsurih/pyjstage/blob/master/LICENSE) file.
PyEvalJS 1.0.0
Run JavaScript Code in Python through the Microsoft Chakra engine
License: MIT
Requires Python: >2.6, !=3.0.*, !=3.1.*, !=3.2.*
Keywords: Python JavaScript js-engine Chakra ChakraCore V8

# PyEvalJS

PyEvalJS is a python wrapper for [Microsoft Chakra](https://github.com/Microsoft/ChakraCore) engine, it act as a bridge between the Python and JavaScript objects, and with this module you can easily run JavaScript Code in Python without having to install nodejs.

## Installation

    pip install PyEvalJS

## Usage

### Execute a script

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.eval("'red yellow blue'.split(' ')")
['red', 'yellow', 'blue']
```

### Call a function

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.compile("""
...     function add(x, y) {
...         return x + y;
...     }
... """)
>>> runtime.call("add",1,2)
3
```

or just put args into the script

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.eval("""
...     function add2(num) {
...         return num+2;
...     } add2(8);""")
10
```

or by passing parameters

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.set_variable("a",8)
True
>>> runtime.eval("""
...     function add2(num) {
...         return num+2;
...     } add2(a);""")
10
```

### Passing parameters

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.set_variable("name", ['Jim','Bob','Tour'])
True
>>> runtime.get_variable("name")
['Jim', 'Bob', 'Tour']
```

### Use a JavaScript module

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.require("./js/crypto-js.js")  #import CryptoJS
>>> runtime.compile("""
...     function encryptByDESModeCBC(key,message) {
...         var keyHex = CryptoJS.enc.Utf8.parse(key);
...         var ivHex = CryptoJS.enc.Utf8.parse(key);
...         encrypted = CryptoJS.DES.encrypt(message, keyHex, {
...                 iv:ivHex,
...                 mode: CryptoJS.mode.CBC,
...                 padding:CryptoJS.pad.Pkcs7
...             }
...         );
...         return encrypted.ciphertext.toString();
...     }""")
>>> runtime.call("encryptByDESModeCBC",'1234','this is a test')
'94b7b0cc2b71165ea067868f595fc03a'
```

### Call the same function for each item in the list

```python
>>> from PyEvalJS import Runtime
>>> runtime = Runtime()
>>> runtime.compile("""
...     function add2(num) {
...         return num+2;
... }""")
>>> runtime.call_for_each("add2",[1,2,4,6,5])
[3, 4, 6, 8, 7]

```

## Supports

- Python2 >= 2.7
- Python3 >= 3.4

## Platform

- macOS x64
- Linux x64
- Windows x86/x64 (tested on Windows 10 x64, Python 3.7)

## Contributing

1. Fork it!
2. Create your feature branch: `git checkout -b my-new-feature`
3. Commit your changes: `git commit -am 'Add some feature'`
4. Push to the branch: `git push origin my-new-feature`
5. Submit a pull request :D

## Licence

Code released under [the MIT license](https://github.com/Satireven/PyEvalJS/blob/master/LICENSE)
keepthis 0.0.4
KeepThis - helper tool for Data Scientists collaborative work. Cache artifacts and share them with your teammates.
License: MIT
Requires Python: >=3.5

# KeepThis

## About project

Scientific toolkit which will inspire you and your team to work with more collaboration than ever before.

It works almost like LRU Cache but allows you:
1. Use same cache in different processes;
2. Use same cache at the different moments of time;
3. Easily share your local runtime's results with your teammates!  

Using [memcached](https://memcached.org) as a backend allows you to cache really large things.

## Try it!

### How to install

Install the package.

1. Clone this repo
2. Open repo's root path in terminal
3. Install package using `pip install -e .`

Please ensure that you have memcached instance. 
I recommend you to use docker image for your first-time interactions with library:
```bash
docker run -d --rm -p 11211:11211 memcached
```
[More information about docker image](https://hub.docker.com/_/memcached)


### More examples

You can find out usages of KeepThis in `examples/` and `notebooks/`
flask-crontab 0.1.2
Simple Flask scheduled tasks without extra daemons
License: MIT
Requires Python: >=3.5

# flask-crontab

> Simple Flask scheduled tasks without extra daemons

[![PyPI](https://img.shields.io/pypi/v/flask-crontab)](https://pypi.org/project/flask-crontab) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/flask-crontab)](https://pypi.org/project/flask-crontab) [![Github Action](https://github.com/frostming/flask-crontab/workflows/Continuous%20Integration/badge.svg)](https://github.com/frostming/flask-crontab/actions?query=workflow%3A%22Continuous+Integration%22) ![Supported Platforms](https://img.shields.io/badge/platform-Linux%20%7C%20macOS-lightgrey)

This project is strongly inspired by [django-crontab](https://github.com/kraiz/django-crontab), and only works on Python 3.5+.
Due to the coming EOL of Python 2 on 2020/01/01, there is no plan for Python 2 support.

## Quick Start

Install via `pip`:

```bash
$ pip install flask-crontab
```

Instantiate the extension in your `app.py` after the creation of Flask app:

```python
from flask import Flask
from flask_crontab import Crontab

app = Flask(__name__)
crontab = Crontab(app)
```

If you are using App Factory pattern, you can also register the extension later:

```python
crontab = Crontab()

def create_app():
    ...
    crontab.init_app(app)
```

Now create a scheduled job:

```python
@crontab.job(minute="0", hour="6")
def my_scheduled_job():
    do_something()
```

An app context is automatically activated for every job run, so that you can access objects that are attached to app context.
Then add the job to crontab:

```bash
$ flask crontab add
```

That's it! If you type in `crontab -l` in your shell, you can see some new lines created by `flask-crontab`.

Show jobs managed by current app:

```bash
$ flask crontab show
```

Purge all jobs managed by current app:

```bash
$ flask crontab remove
```

Run a specific job given by hash:

```bash
$ flask crontab run <job_hash>
```

See supported options via `--help` for every commands.

## Decorator API

```python
def job(
    minute: str = "*",
    hour: str = "*",
    day: str = "*",
    month: str = "*",
    day_of_week: str = "*",
    args: Tuple[Any, ...] = (),
    kwargs: Optional[Dict[str, Any]] = None,
) -> Callable:
```

The decorator accepts five arguments `minute`, `hour`, `day`, `month`, `day_of_month`, which are the same as crontab 5-parts time format. Any part that is not given defaults to `*`.
Besides, `job` decorator accepts `args` and `kwargs` which will be passed to the decorated function as positional arguments and keywords arguments, respectively.

## Configuration

| Config item        | Description                    | Default value      |
| ------------------ | ------------------------------ | ------------------ |
| CRONTAB_EXECUTABLE | The absolute path of `crontab` | `/usr/bin/crontab` |
| CRONTAB_LOCK_JOBS  | Whether lock jobs when running | `False`            |

## License

This project is publised under [MIT](LICENSE) license.
mcafee-mwgapi 0.3
Mcafee Web Gateway API functionality
License: MIT
Requires Python: >=3.4
Keywords: mcafee webgateway api development

# Overview: 

This is an open source project to help developers working on the McAfee Web Gateway product, 
Since McAFee lacks a pre-developed code package. 
Package is written in reference of MWG Version 8.2. 



# Usage:  

~~~~
from webgatewayapi.authenticate import authenticate

MWG_SERVER = input("Enter MWG Server")
PORT = input("Enter API Port")

authServer = authenticate(hostname=MWG_SERVER, port=PORT)
auth = authServer.createSession(username="something", password="something")
print(auth.session) 

from webgatewayapi.appliances import appliances
appliance = appliances(auth=auth.session, hostname=MWG_SERVER, port=PORT)
listappliance = appliance.listAppliances()
print(listappliance)

from webgatewayapi.listdata import listdata
list = listdata(auth.auth.session, hostname=MWG_SERVER, port=PORT)
getalllists = listdata.listdata()
print(getalllists)

trustedsoruce:
publichostvalidation = trustedsource()
print(publichostvalidation.lookup(data=test.setup()))

~~~~

# Contribution:
This is an Open Source Project, Contributions are welcome. 

#License: 
MIT License
__
chatbot-nlu 1.0.3
nlu of classifiers detection、name entity recognition、classification of chinese text
License: MIT

一、Chatbot_NLU
==========================

**Chatbot_NLU** 是一个基于 `RASA <https://rasa.com/docs/rasa/user-guide/installation/>`_ 的自定义中文语言理解组件，他可以替换掉RASA中本身的nlu模块，可以使nlu的准确率有较大提升，目前
引入了 **bert** ，后续将引入 **xlnet** 。

同时，`RASA <https://rasa.com/docs/rasa/user-guide/installation/>`_ 的自定义组件可以参考 `Custom NLU Components <https://rasa.com/docs/rasa/api/custom-nlu-components/>`_

目前 **Chatbot_NLU** 支持的功能有：

    1、bert vector

    2、bert intent

    3、bert slot


二、安装使用
============

1、安装
>>>>>>>>>>>>>>>>>>

.. code:: python

    pip install chatbot_nlu

2、使用
>>>>>>>>>>>>>>>>>>>

**Chatbot_NLU** 的使用是在 **config.yml** 文件中修改配置，常见的使用方法请参考：

.. code:: python

    language: "zh"

    pipeline:
    - name: "JiebaTokenizer"
    - name: "chatbot_nlu.extractors.crf_entity_extractor.CRFEntityExtractor"

    # ner
    - name: "chatbot_nlu.extractors.jieba_pseg_extractor.JiebaPsegExtractor"
      part_of_speech: ["nr"]

    - name: "chatbot_nlu.extractors.bilstm_crf_entity_extractor.BilstmCRFEntityExtractor"


    # Word Embedding
    - name: "chatbot_nlu.featurizers.bert_vectors_featurizer.BertVectorsFeaturizer"
      ip: "172.18.103.43"
      port: 5555
      port_out: 5556
      show_server_config: True
      timeout: 10000
      check_version: False





三、Update News
======================

    * 2020.1.7  接入钉钉群，支持主动推送消息、outgoing交互

    * 2020.1.9  接入微信



四、Resources
======================

.. _`Dingtalk_README`: https://github.com/charlesXu86/Chatbot_Help/blob/master/Dingtalk_README.rst