semvec/pypi-packages huggingface dataset:
nlp2cron 0.1.4
Nature language to cron
Requires Python: >=3.9,<4.0

## 中文自然语言转CRON

pip install nlp2cron

```python
from nlp2cron import nlp2cron
cron = nlp2cron("每天10点25分叫我去买菜")

```

你会得到一个`cron`表达式. 目前代码写的有点乱, 但只要不太随意的自然语言都可以解决
代码里面有一些例子, 详细看代码啦. 代码写的比较随意, 如果要求高请不要用啦.
pyranker 0.1.3
A Python based package consisiting of BM25 and         Vector Space Rankers for Information Retrieval
Requires Python: >=3.8

PyRanker
====================

<p>
<img src="https://img.shields.io/pypi/v/pyranker.svg?style=for-the-badge" alt="PyPI Shield">
<img src="https://img.shields.io/badge/License-MIT-green.svg?style=for-the-badge" alt="MIT License">
<img src="https://img.shields.io/badge/code%20style-black-000000.svg?style=for-the-badge" alt="Code Format">
</p>

___

A Python based package consisiting of BM25 and Vector Space Rankers for Information Retrieval
fsoft-diff-patch 0.1.1
Deep compare two objects and produces a diffData to transform object1 to object2

# diff-patch

## Introduction

diff-patch is a library that exposes two functions, `diff` and `patch`.

The library does not have any dependencies.

The `diff` function takes two objects (`obj1` and `obj2`) and deep compares them, returning an object that represents the difference between the two (the `diffData`).
`diffData` is an object that can be used to apply the diff to `obj1` to get an object that is the same as `obj2`.

The `patch` function takes an `obj` and a `diffData` object and applies the diff to the object, returning a new object.

The `diff` and `patch` functions are implemented in the following languages:

  * TypeScript
  * Python3

The `diffData` object **can be used interchangeably between the languages**.\
This makes this library very useful for networked applications, where the client and server are written in different languages.

`diffData` can be serialized to JSON and deserialized back to an object. It aims to be as small as possible, and is designed to be used in a networked environment.

More languages will be added in the future, contributions are welcome.

## Usage

To install the Python3 version of diff-patch, run:

```bash
pip install fsoft-diff-patch
```

Then, in your Python code:

```python

from fsoft_diff_patch import diff, patch

obj1 = {
  'a': 1,
  'b': 2,
  'c': {
    'd': 3,
    'e': 4,
  },
}

obj2 = {
  'a': 1,
  'b': 2,
  'c': {
    'd': 3,
    'e': 5,   # changed
  },
}

# create the diff data
diff_data = diff(obj1, obj2)

# show the diff data for debugging
print("diff_data: ", diff_data)

# apply the diff data to obj1 to get an object that is the same as obj2
obj3 = patch(obj1, diff_data)

# show the result for debugging
print("obj3: ", obj3)
```

### Hint

The `diff` function can be used to see if two objects are the same, by comparing the result of `diff` to an empty object.

```python
from diff_patch import diff

obj1 = {
  'a': 1,
  'b': 2,
  'c': {
    'd': 3,
    'e': 4,
  },
}

obj2 = {
  'a': 1,
  'b': 2,
  'c': {
    'd': 3,
    'e': 4,
  },
}

diff_data = diff(obj1, obj2)

# if the objects are the same, diff_data will be an empty object
if not diff_data:
  print("The objects are the same")
```

## Contributors

This library was created by [Fabio Rotondo](https://github.com/fsoft72).

New language implementations are more than welcome.\
Please open an issue or a pull request if you want to contribute.

**Collaborators**:

  * [Nikola Gluhovic](https://github.com/nini-os)


The official repository for this library is [here](https://github.com/fsoft72/diff-patch).

## License

This library is licensed under the MIT License.\
See the [LICENSE](LICENSE) file for details.
escodegen 1.0.11
ECMAScript code generator
Requires Python: >=3.6
Keywords: ast,ecmascript,escodegen,generate,generator,javascript

**Escodegen** ([escodegen](http://github.com/estools/escodegen)) is an
[ECMAScript](http://www.ecma-international.org/publications/standards/Ecma-262.htm)
(also popularly known as [JavaScript](http://en.wikipedia.org/wiki/JavaScript))
code generator from [Mozilla's Parser API](https://developer.mozilla.org/en/SpiderMonkey/Parser_API)
AST. See the [online generator](https://estools.github.io/escodegen/demo/index.html)
for a demo. This repository contains the Python translation of Escodegen.


## Install

    pip install escodegen

## Usage

### Example:
```python
import escodegen

escodegen.generate({
    'type': 'BinaryExpression',
    'operator': '+',
    'left': { 'type': 'Literal', 'value': 20 },
    'right': { 'type': 'Literal', 'value': 2 }
})
```
*produces the string: `'20 + 2'`*

### Example:
```python
import escodegen
import esprima

escodegen.generate(esprima.parse('let a=10;let b=20'))
```
*produces the string: `'let a = 10;\nlet b = 20;'`*

See the [API page](https://github.com/estools/escodegen/wiki/API) for
options.
pshmodule 0.1.14
Modules related to preprocessing, crawling, collection, database, data load & save
Requires Python: >=3.8

# 🤖 AI Module

### 👉🏻 데이터 수집, 전처리, DB 관련 패키지
#### pshmodule  https://pypi.org/project/pshmodule/
<br>
db :  sqlalchemy, pymysql excutemany query
<br>
processing : data 정규표현식 전처리
<br>
selenium : selenium 크롤링
<br>
utils : filemanager 파일 load, save 및 전반 utils
<br>

## 👉🏻 use to
test directory의 test 파일로 예시 참고 ex) alchemy_test, selenium_test
<br>
https://github.com/hipster4020/pshmodule/tree/master/test
<br>


## 👉🏻 install
pip3 install pshmodule
<br>


## 👉🏻 tree
 * [src]
   * [pshmodule] 
     * [db]
       * [__init__.py]
       * [alchemy.py]
       * [config.py]
     * [processing]
       * [__init__.py]
       * [processing.py]
     * [selenium]
       * [__init__.py]
       * [helper.py]
     * [utils]
       * [__init__.py]
       * [filemanager.py]
     * [__init__.py]
 * [test]
   * [selenium_test.py] 
 * [README.md]
 * [setup.py]


## 👉🏻 regist
python3 setup.py sdist bdist_wheel
twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
pycachera 4.5.1
A powerfull python caching tool

# PyCachera
A powerful python decorator to cache functions

[![Tests](https://github.com/antolonappan/pycachera/actions/workflows/test.yml/badge.svg)](https://github.com/antolonappan/pycachera/actions/workflows/test.yml)
[![PyPI / GitHub](https://github.com/antolonappan/pycachera/actions/workflows/publish.yml/badge.svg)](https://github.com/antolonappan/pycachera/actions/workflows/publish.yml)
[![CodeQL](https://github.com/antolonappan/pycachera/actions/workflows/codeql.yml/badge.svg)](https://github.com/antolonappan/pycachera/actions/workflows/codeql.yml)
[![Docker](https://github.com/antolonappan/pycachera/actions/workflows/docker-publish.yml/badge.svg)](https://github.com/antolonappan/pycachera/actions/workflows/docker-publish.yml)
[![wakatime](https://wakatime.com/badge/user/e4d61f54-a71a-4db6-81a9-edbb50ce497f/project/49c3495a-f7c4-416b-92b9-2f80ef1b43d2.svg)](https://wakatime.com/badge/user/e4d61f54-a71a-4db6-81a9-edbb50ce497f/project/49c3495a-f7c4-416b-92b9-2f80ef1b43d2)
[![Documentation Status](https://readthedocs.org/projects/pycachera/badge/?version=latest)](https://pycachera.readthedocs.io/en/latest/?badge=latest)

## Installation

In command line:

`pip install pycachera`

## Usage

Import the pycachera as:

```
from pycachera import cache
```

For caching a function
```
@cache()
def sum(a,b):
   return a+b
```

For caching a class attributes.

```
class Math:
   def __init__(self):
       pass
   
   @cache()
   def sum(a,b):
      return a + b  
```

For caching to a specific directory.

```
@cache(cachefolder='/home/user/scratch')
def sum(a,b):
   return a+b
```

For caching with a specific key

```
@cache(cachekey='This a custom cache')
def sum(a,b):
   return a+b
```

For printing the info

```
@cache(verbose=True)
def sum(a,b):
   return a+b
```

While debugging your script if you want to ignore the cached values you can recache
```
@cache(recache=True)
def sum(a,b):
   return a+b
```

When you use cache with a class attribute, and if you want to consider some attributes of that class for caching,

```
class Math:
   def __init__(self,c):
       self.c = c
   
   @cache(extrarg=['c'])
   def sum(a,b):
      return a + b  
```

To cache a class property,
```
class math:
    def __init__(self,a,b):
        self.a = a
        self.b = b
    
    @property
    @cache(extrarg=['a','b'],verbose=True)
    def add(self):
        return self.a + self.b
```

When using mpi4py.MPI,
```
@cache(with_mpi=True)
def sum(a,b):
   return a+b
```



## API

visit [pycachera.readthedocs.io](https://pycachera.readthedocs.io/en/latest/)
faker-marketdata 0.4
Sample market data for Faker
Requires Python: >=3.6
Keywords: faker,testdata,financedata,python,marketdata,isin,sedol,cusip,ticker,figi

# faker_marketdata
Generates random, valid market identifiers following most common formats in the industry.

## Installation

``` bash
pip install faker_marketdata
```

## Usage

Add as a provider to your [Faker](https://faker.readthedocs.io/en/master) instance:
``` python
>>> from faker import Faker
>>> from faker_marketdata import MarketDataProvider
>>> fake = Faker()
>>> fake.add_provider(MarketDataProvider)
```
Optionally you can define a seed value to have repeatable identifiers: 
``` python
>> Faker.seed(123)
>> fake.add_provider(MarketDataProvider())
```

Now you can start to generate market identifiers, some examples:
``` python
>> fake.isin()   # "GTYMQXUIYPB6"
>> fake.sedol()  # "NKDEKC8"
>> fake.cusip()  # "Z57XGDJW7"
>> fake.ticker() # "GRTT"
```

## Documentation
Supported market data formats:
* ISIN
* SEDOL
* MIC
* LEI
* CUSIP
* RIC
* TICKER
* NSIN
* FIGI
* Market type (e.g. "bond", "commodity", "otc")