semvec/pypi-packages huggingface dataset:
colorlog-jawide 0.0.1
Enable the default logging to output with color
Requires Python: >=3.6

# colorlog

## example

```python
from colorlog import logging

logging.basicConfig(level=logging.DEBUG)

logging.debug("jawide")
logging.info("jawide")
logging.warning("jawide")
logging.error("jawide")
logging.critical("jawide")
```

## setup

```bash
pip install colorlog-jawide
```

## custom

```python
from colorlog import init, Config, LogLevel, Color, Fore, Back, Style
import logging

init(logging, Config({
    LogLevel.DEBUG    : Color(Fore.GREEN, Style.BRIGHT),
    LogLevel.CRITICAL : Color(Fore.YELLOW, Back.RED, Style.NORMAL)
}))

logging.basicConfig(level=logging.DEBUG)

logging.debug("jawide")
logging.info("jawide")
logging.warning("jawide")
logging.error("jawide")
logging.critical("jawide")
```

## build

```bash
rm -r ./build ./dist
python setup.py sdist bdist_wheel
```

## test upload

```bash
python -m twine upload --repository testpypi dist/*
```

## test pip

```bash
python -m pip install --index-url https://test.pypi.org/simple/ --no-deps colorlog-jawide
```

## upload

```bash
python -m twine upload dist/*
```
sqllite3tools1 0.0.7
SQLITE tools
Keywords: execute,commit,fetchone,fetchall,create_table,info,select

# sqllite3tools1

**sqllite3tools1** a simple library that connects to a database.

```python
>>> data1={
      "name":"John",
      "email":"John@gmail.com"
}
>>> from sqllite3tolls1 import dataBase
>>>
>>> db=dataBase('path') #by default main.db
>>> db.create_table('Students',id='INTEGER PRIMARY KEY AUTOINCREMENT',name='varchar(255)',email="varchar(255)")
>>> #create_table(table_name:str,**kwargs) 
>>> db.info('Students')
'|| 0, id, INTEGER, 0, None, 1 ||'
'|| 1, name, varchar(255), 0, None, 0 ||'
'|| 2, email, varchar(255), 0, None, 0 ||'
>>> #info(table_name:str) return table info,cols,data types
>>> db.add_to_table('Students',data1) #parametrs: <table_name:str>,<data:dict>
'Executing:'
"INSERT INTO Users5('name', 'email') VALUES('John','John@gmail.com')"
>>> db.drop_table('Studets') #drop_table(table_name:str)
```


## Installing sqllite3tools1 and Supported Versions

sqllite3tools1 is available on PyPI:

```console
$ python -m pip install sqllite3tools1
```

sqllite3tools1 officially supports Python 3.7+.



## Cloning the repository


```shell
git clone https://github.com/SanjarbekDev/sqllite3tools1.git
```



---

[![Python Software Foundation](https://raw.githubusercontent.com/psf/requests/main/ext/psf.png)](https://www.python.org/psf)
resparser 0.6
Extract Resume Entities Using NER

# `pyresparser`
## Extract Resume Entities Using NER



![Build Status](https://travis-ci.org/joemccann/dillinger.svg?branch=master)

Resparser is a cloud-enabled resume entities extractor
Examples
- Name
- Email
- Location
- Etc

## Tech Stack

Resparser uses a number of open source projects to work properly:

- Spacy - It is an open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more.
- Google Cloud Vision - The Vision API can detect and extract text from images
- Django Rest Framework - It is used to building Web API

## Installation

Install the dependencies 

```sh
pip install reuqests
pip install resparser
```

## Use

`resparser` is very easy to install and use.

Follow the below code

```sh
#import resprser
from resparser import resumeparser

#provide your text resume 
with open(r"C:\Projects\Resume\Resume_Parser\output\1.txt", 'r') as f:   
    data = f.read()
#
#pass the text to the resumeparser 
result=resumeparser(data)
print(result)
.
```

You will receive output in json 

```sh
{'NAME': 'Mukesh Ambani', 'LOCATION': 'Kolkata', 'Email': 'mukeshambin@gmail.com', 'Mobile': '983468633'}
```
cfan-2015-part6 2022.4.30.0
电脑爱好者2015合订本（中）第二部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（中）第二部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part6
docker run -tid -p <port>:80 apachecn0/cfan-2015-part6
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part6
cfan-2015-part6 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part6
cfan-erlingyiwu-part6 <port>
# 访问 http://localhost:{port} 查看文档
```
cachecore 0.4.0
A low level cache library.
Requires Python: >=3.9

# cachecore
A low-level caching library with multiple implementations.

Can be used as a stand-alone cacheing library or can be used to create higher level caching libraries.

## Basics
Get, set, delete, and check for the existence of a key using the following.

```
>>> import cachecore
>>> cache = cachecore.LocalCache()
>>> cache.set('a', 1)
>>> cache.get('a')
1
>>> cache.exists('a')
True
>>> cache.delete('a')
True
>>> cache.exists('a')
False
>>> cache.get('a')
None
```


## Complete API
```
    __getitem__(self, key: str) -> Any:

    __setitem__(self, key: str, value: Any):

    __delitem__(self, key: str):

    __contains__(self, key: str):

    __iter__(self):

    __len__(self):

    keys(self, pattern: str = None):

    get(self, key: str, default: Any = None) -> Any:

    set(self, key: str, value: Any, ttl: Optional[int] = None):

    add(self, key: str, value: Any, ttl: Optional[int] = None) -> bool:

    replace(self, key: str, value: Any, ttl: Optional[int] = KEEP_TTL) -> bool:

    delete(self, key: str) -> bool:

    pop(self, key: str, default: Any = None):

    exists(self, key: str) -> bool:

    get_many(self, keys: Iterable[str], default: Any = None) -> Iterable[Any]:

    set_many(self, mapping: Iterable[tuple[str, Any]], ttl: Optional[int] = None):

    delete_many(self, keys: Iterable[str]) -> Iterable[bool]:

    get_ttl(self, key: str, default: int = 0) -> Optional[int]:

    set_ttl(self, key: str, ttl: Optional[int] = None) -> bool:

    incr(self, key, delta=1) -> int:

    decr(self, key, delta=1) -> int:

    clear(self):
```


## Cache Implementations
- Redis
- Memcached
- File System
- Local Memory
- Dummy
cfan-2015-part5 2022.4.30.0
电脑爱好者2015合订本（中）第一部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（中）第一部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part5
docker run -tid -p <port>:80 apachecn0/cfan-2015-part5
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part5
cfan-2015-part5 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part5
cfan-erlingyiwu-part5 <port>
# 访问 http://localhost:{port} 查看文档
```
cfan-2015-part4 2022.4.30.0
电脑爱好者2015合订本（下）第二部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（下）第二部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part4
docker run -tid -p <port>:80 apachecn0/cfan-2015-part4
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part4
cfan-2015-part4 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part4
cfan-erlingyiwu-part4 <port>
# 访问 http://localhost:{port} 查看文档
```
cfan-2015-part3 2022.4.30.0
电脑爱好者2015合订本（下）第一部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（下）第一部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part3
docker run -tid -p <port>:80 apachecn0/cfan-2015-part3
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part3
cfan-2015-part3 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part3
cfan-erlingyiwu-part3 <port>
# 访问 http://localhost:{port} 查看文档
```
cfan-2015-part2 2022.4.30.0
电脑爱好者2015合订本（上）第二部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（上）第二部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part2
docker run -tid -p <port>:80 apachecn0/cfan-2015-part2
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part2
cfan-2015-part2 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part2
cfan-erlingyiwu-part2 <port>
# 访问 http://localhost:{port} 查看文档
```
cfan-2015-part1 2022.4.30.0
电脑爱好者2015合订本（上）第一部分
Requires Python: >=3.6

# 电脑爱好者2015合订本（上）第一部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2015-part1
docker run -tid -p <port>:80 apachecn0/cfan-2015-part1
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2015-part1
cfan-2015-part1 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyiwu-part1
cfan-erlingyiwu-part1 <port>
# 访问 http://localhost:{port} 查看文档
```
cfan-2014-part4 2022.4.30.0
电脑爱好者2014合订本（下）第二部分
Requires Python: >=3.6

# 电脑爱好者2014合订本（下）第二部分

## 下载

### Docker

```
docker pull apachecn0/cfan-2014-part4
docker run -tid -p <port>:80 apachecn0/cfan-2014-part4
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install cfan-2014-part4
cfan-2014-part4 <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g cfan-erlingyisi-part4
cfan-erlingyisi-part4 <port>
# 访问 http://localhost:{port} 查看文档
```