semvec/pypi-packages huggingface dataset:
xhpubqt 0.0.2
a pub library for PyQt5 to implement some cool controls
Requires Python: >=3.6

# UE4滑动条

1. 如果没有设置范围不显示百分比，设置了才会显示
2. 单机鼠标长按拖动可以调整数值，不可超过最大最小值，拖动时会隐藏鼠标箭头
3. 单机鼠标可以手动输入数值，手动输入时可超过设定范围
4. 无范围限制时会根据当前数值智能调整大小
vitaoptimum 1.5.8
Global Optimum Search Algorithms Python Interface Package
Keywords: algorithms optimization global metaheuristic evolutionary genetic evolution swarm

The python interface classes for VitaOptimum
============================================

VitaOptimum is a library which solvers are designed to find a globally best solution of non-linear models in the possible or known presence of multiple local optima and constraints. The python package contains interface classes for the library. VitaOptimum Library efficiently handles any type of arguments to optimize including continuous, mixed-variables, combinatorial permutations, integer or binary. It can deal with any type of constraints: boundary, equality or inequality ones. The library gives freedom to express models in a language that are closer to reality, which makes the final solution closer to reality.

There are many fields of their application, for example:

* Advanced Engineering Design
* Data Analysis
* Financial Forecasting
* Portfolio and Risk Management
* Process Control
* Robot Design
* Packing
* Logistics
* Telecommunications
* System Biology
* Computational Physics and Chemistry
* Biotechnology
* Advanced Statistics
* Scientific Modeling
* Artificial Intelligence
* Machine and Deep Learning
* etc.

In order to use the python interface VO or VOPlus library is needed. It can be downloaded from the official web site (see links below). Also a license file is needed in order to use the library. The license file can be requested via email vo@skyworkflows.com along with a short description of your research.

Requirements
------------
* VitaOptimum library 1.x
* Python 3.7 and higher
* Python packages: numpy, matplotlib, retrying

Links
-----
* The official web site: http://skyworkflows.com/vo
* The pip web page: https://pypi.org/project/vitaoptimum
datelibrary-javis 0.1.0
date package for parsing dates
Requires Python: >=3.6

# Package Info

Date Extraction library built on top of Python native date libraries to support business vocabularies.

# Installation
```
 pip install datelibrary-javis
```

# Usage

```python
 import datelibrary
 from datelibrary.dates import DateData
 text = "my sales from june to aug'
 date_obj = DateData(text)
 print(date_obj.comile_dates())
 >>>['2018-06-01', '2018-08-31'] #list of strings
```

# Scope

>	current date = 5th November 2019

> current day = Tuesday


| Type | Parsed Date |
| ---- | ---- |
| ytd (year to date) | ['2019-01-01', '2019-11-05'] |
| mtd (month to date) | ['2019-11-01', '2019-11-05'] |
| qtd (quarter to date) | ['2019-10-01', '2019-11-05'] |
| l3m (last 3 months) | ['2019-07-01', '2019-10-30'] |
| june to august | ['2019-06-01', '2019-08-31'] |
| june 2018 to august 2018 | ['2018-06-01', '2018-08-31'] |
| june 2018 | ['2018-06-01'] |
|  1/6/2019 to 2/6/2019 | ['2019-06-01', '2019-06-02'] |
|  last month | ['2019-10-01', '2019-10-31'] |
|  last week | ['2019-10-27', '2019-10-03'] |
|  last year | ['2019-01-01', '2019-01-31'] |
moln 0.0.1a1
Stupid, simple Azure client library built for the rest of us
Requires Python: >=3.6

# moln {/mo:ln/}
Stupid simple access to [Microsoft Azure](https://azure.microsoft.com) services using Python. Built for the rest of us.

This is very much a work in progress. Feedback is welcome.

To install:
```bash
pip install moln
```

```python
import pathlib

import moln.storage

# Authentication is done using the azure-identity package.
# By default, it will use the azure.identity.DefaultAzureCredential
account = moln.storage.attach(account_url='https://molntest.blob.core.windows.net')

# Creating containers - just like you create directories!
container = account / 'jabbadabbadoo'
container.mkdir(exists_ok=True)

local_file = pathlib.Path('./stuff.json')
remote_file = container / 'stuff.json'

# Upload blobs like you would upload files - with the option to
# specify metadata like Content-Type headers for the uploaded blob.
if not remote_file.exists():
    with local_file.open(mode='rb') as lf:
        with remote_file.open(mode='wb', content_settings=azure.storage.blob.ContentSettings(content_type='application/json')) as rb:
            rb.write(lf.read())

# Work with the blob as if you opened a local file
with remote_file.open(mode='r') as rb:
    import json
    data = json.load(rb)
    print(data)
```