semvec/pypi-packages huggingface dataset:
randSelector 1.0.3
random value selector with associated probability package

Description: 
..\randSelector\randSelector\rand_selector module contains a function select_rand_item,
that can select a random a item from a data set with its associated probability



pip instalattion:
give the following command to add the module to your environment:
	 'pip install randSelector' 

get access to the functions by adding the following to the top of your script:
	 'from  randSelector import rand_selector'

to test, run command:
	select_rand_item( ((1, 0.6), (3, 0.4))), seed_num=10) from any script 

	OR

	run ..\MsAssesment\randSelector\unitTest\test_rand_selector.py from the zipped folder after installing pip package above
	this will unit test the module.Also, additional tests can be written to extend test covergage
MediaWiki-Tools 0.1.1
Tools for getting data from MediaWiki websites
Requires Python: >=3.8

# MediaWiki Tools

[![Coverage Status](https://coveralls.io/repos/github/nick-robo/MediaWiki-Tools/badge.svg?branch=main)](https://coveralls.io/github/nick-robo/MediaWiki-Tools?branch=main)

A high level library containing set of tools for for filtering pages using the rich data available in MediaWikis such as categories and info boxes. Uses both web-scraping and API methods (where available and feasible) to gather information.

# Goals

- Generate useful data (and datasets) from a wiki.
- To work on any MediaWiki (including `fandom.com`) with or without api.
- Get arbitrary subsets of pages based on categories and template parameters (todo).
- Be very robust to variations and inconsistencies in user input.
- Be efficient.


# Installation

Install it using pip.

```
pip install mediawiki-tools
```

Requires python `>3.8` because I like the walrus operator.

# Usage

Check out the [basic usage](https://nick-robo.github.io/MediaWiki-Tools/mwtools.html) guide and detailed [API documentation](https://nick-robo.github.io/MediaWiki-Tools/mwtools/mediawikitools.html).

# Example

Question: Which countries in Asia use english as spoken Language?

Answer:
```python
import mwtools

wiki = MediaWikiTools('en.wikipedia.org')

wiki.get_set(['Countries in Asia', 
              'English-speaking countries and territories'], 
             'and')
# ['Philippines', 'Pakistan', 'Bahrain', 'Singapore', 'Brunei', 'India']
```

Question: Which countries in Asia or Europe use english as spoken Language?

Answer:
```python
wiki.get_set(['Countries in Asia', 'Countries in Europe',
              'English-speaking countries and territories'], 
             ['or','and'])
# ['Philippines',
#  'United Kingdom',
#  'Brunei',
#  'Malta',
#  'India',
#  'Pakistan',
#  'Scotland',
#  'Republic of Ireland',
#  'Singapore',
#  'Bahrain']
```

Question: Which of these countries are not island nations?

Answer:
```python
wiki.get_set(['Countries in Asia', 'Countries in Europe',
              'English-speaking countries and territories',
              'Island countries'], 
             ['or', 'and', 'not'])
# ['Pakistan', 'India']
```
dssm 0.1.3
An industrial-grade implementation of DSSM
Keywords: dssm semantic-retrieval text-matching

# DSSM
An industrial-grade implementation of the paper: [Learning Deep Structured Semantic Models for Web Search using Clickthrough Data](https://dl.acm.org/citation.cfm?id=2505665)


Latent semantic models, such as LSA, intend to map a query to its relevant documents at the semantic level where keyword-based matching often fails. DSSM project queries and documents into a common low-dimensional space where the relevance of a document given a query is readily computed as the distance between them.

This model can be used as a search engine that helps people find out their desired document even with searching a query that:
1. is abbreviation of the document words;
2. changed the order of the words in the document;
3. shortened words in the document;
4. has typos;
5. has spacing issues.



## Install

DSSM is dependent on PyTorch. Two ways to install DSSM:

**Install DSSM from Pypi:**

```
pip install dssm
```



**Install DSSM from the Github source:**

```
git clone https://github.com/Chiang97912/dssm.git
cd dssm
python setup.py install
```



## Usage

### Train

```python
from dssm.model import DSSM

queries = ['...']  # query list, words need to be segmented in advance, and tokens should be spliced with spaces.
documents = ['...']  # document list, words need to be segmented in advance, and tokens should be spliced with spaces.
model = DSSM('dssm-model', device='cuda:0', lang='en')
model.fit(queries, documents)
```



### Test

```python
from dssm.model import DSSM
from sklearn.metrics.pairwise import cosine_similarity

text_left = '...'
text_right = '...'
model = DSSM('dssm-model', device='cpu')
vectors = model.encode([text_left, text_right])
score = cosine_similarity([vectors[0]], [vectors[1]])
print(score)
```



## Dependencies

* `Python` version 3.6
* `Numpy` version 1.19.5
* `PyTorch` version 1.9.0
stream-source 0.0.1
A python API to find streaming sources of any movie or Television show
Requires Python: >=3.6

# <b><font color="dodgerblue">stream-source 0.0.1</font></b>
 A python API to locate streaming sources for all movies and television shows
 ## <font color="dodgerblue">How to install ?</font>
 Open the terminal and type in the command
  > pip install whereisit
 ## <font color="dodgerblue">How to use ?</font>
 To find the streaming source of movies call find_movie
 ### <font color="lawngreen">Movies</font>
  >import whereisit as wit <br>sources = wit.find_movie(title)
  #### find_movie(title) will return a list of streaming sources of the movie title passed as argument
   <font color="red">If there are no streaming sources available then the function will return False</font>
   ### <font color="lawngreen">Television shows</font>
   >import whereisit as wit <br>sources = wit.find_tvseries(title)
  #### find_tvseries(title) will return a list of streaming sources of the television show title passed as argument
   <font color="red">If there are no streaming sources available then the function will return False</font>
easyserializationlanguage 1.0.4
A parser for ESL (Easy Serialization Language)!.

# Easy Serialization Language
ESL (Easy Serialization Language) it's a language for storing data easily.<br>
Although ESL has strict rules, it is easier to read than JSON, XML, and others.

# How-to Install
```sh
git clone https://github.com/zsendokame/Easy-Serialization-Language && cd Easy-Serialization-Language && pip install .

# Or

pip install easyserializationlanguage
```

# Syntax
```yaml
description = This is an ESL example.
someData = [ESL supports arrays., add the values you wan't!.]
```

# How-to Use
```py
import esl

code = """
variable = it's value.
array = [firstValue, secondValue, thirdValue]
"""
load = esl.loads(code)

print(load)
"""
{
    'variable': "it's value.",
    'array': [
        'firstValue',
        'secondValue',
        'thirdValue'
    ]
}
"""

eslDict = load
dump = esl.dumps(eslDict)

print(dump)
"""
variable = it's value.
array = [firstValue, secondValue, thirdValue]
"""
```


# News
- Dump function added.