semvec/pypi-packages huggingface dataset:
gt-pdf-extraction 0.0.1.1
A python pdf extraction package.
Requires Python: >=3.10

# PDF Extraction

**Internal Usage only.**

A pdf text/table extraction package for python.

## Installation

### via Bitbucket

```bash
pip install git+https://bitbucket.org/guangyuhe/pdf-extraction/src/main/
```

### via PyPI

```bash
pip install gt-pdf-extraction
```

## Usage

- initializing pdf extraction instance
- use method to get the result

## Arguments

- **file_path**: the path the pdf document

## Methods

- **extract_text**(_page_): extract text, _page_: int-like argument, a single page extraction or 'all' for all pages,
  default is 'all'
- **extract_table**(_mp_on_): extract table, _mp_on_: bool, whether to use multiprocess to extract tables, default is
  False
- **nr_pages**, *without ()*, return the number of pages

## Sub-methods

### extract_text

- **.apply(_func_,_args_)**: apply a function to the text, details see examples
- **str()**: return the text
- **.text**: *without ()*, return the text
- **bool()**: return True if the text is not empty

### extract_table

- **.df**: *without ()*, return the table as a pandas dataframe
- **.to_list()**: return the table as a list of list
- **.to_csv(_output_folder_)**: save the table as a csv file in the output folder

## Examples

### extract text

```python
from gt_pdf_extraction import PDFE

path: str = "/path/to/pdf"

# initialize the instance
instance = PDFE(path)

# declaring a function
extract_text = instance.extract_text(page="all")


# optional, apply a function to the text
def a_func(text, arg):
    return text.replace(arg, "")


extract_text.apply(a_func, args="a_string")

# get the text
the_text = extract_text.text  # or str(extract_text)

```

### extract table

```python
from gt_pdf_extraction import PDFE

path: str = "/path/to/pdf"

# initialize the instance
instance = PDFE(path)

# declaring a function with multiprocess enabled
extract_table = instance.extract_table(mp_on=True)

# get the table in df
the_df = extract_table.df
# get the table in list
the_list = extract_table.to_list()
# save the table as csv
extract_table.to_csv("/path/to/output/folder")

```

## Updates Log

### v0.0.1

#### initial upload

- first version

### v0.0.1.1

#### bug fix

- fix the long desc error in setup.py causing installation failed

## Support

2023&copy;GoldenTech, for further support please contact author. <br>
Email: <a href="mailto:guangyu.he@golden-tech.de">guangyu.he@golden-tech.de</a>
universal-date-parser 0.0.2.1
A universal date parser to parse any kind of (possible) date strings.
Requires Python: >=3.7

# Universal Date Parser

an universal date parser for python, which can parse date string from different formats and localization (including
Excel dates) into datetime object and more.

## Installation

### via Github

```bash
pip install git+https://github.com/guangyu-he/universal_date_parser
```

### via PyPI

```bash
pip install universal-date-parser
```

## Usage

- initializing parser instance
- use method to get the result

## Arguments

- **date_in_str**: the date string to be parsed
- **date_format** (optional): the format of the date string, default is "guess", which means it will guess the format
    - "guess": guess the format
    - others: date formats supported by datetime.strptime()
- **locale** (optional): the locale of the date string, default is None, which means it will guess the localization
  format

## Methods

- **to_datetime**(): return datetime object
- **to_date**(): return date object
- **to_time**(): return time object
- **to_date_str**(_date_format_): return date string, by default, the format is "YYYY-MM-DD"
- **to_str**(_date_format_): return the date time string, by default, the format is "YYYY-MM-DD HH:MM:SS"
- **to_timestamp**(): return the timestamp object

## Examples

```python
from universal_date_parser import DateParser

date_string = "06/07/1995"
a = DateParser(date_string, locale="de_DE")
print(a.to_date_str())
# >>> 1995-07-06
print(a.to_str())
# >>> 1995-07-06 00:00:00
print(a.to_date_str(date_format="%d.%m.%Y"))
# >>> 06.07.1995

date_string = "06/07/1995"
a = DateParser(date_string, locale="en_US")
print(a.to_date_str())
# >>> 1995-06-07

date_string = "06/07/1995"
a = DateParser(date_string, date_format="%d/%m/%Y")
print(a.to_date_str())
# >>> 1995-07-06

date_string = "Jun/06/1995"
a = DateParser(date_string)
print(a.to_date_str())
# >>> 1995-06-06

date_string = "06/Juni/1995"
a = DateParser(date_string, locale="de_DE")
print(a.to_date_str())
# >>> 1995-06-06
```

## Updates Log

### v0.0.1

#### initial upload

- first version

### v0.0.2

#### update

- description and setup updates

### v0.0.2.1

#### bug fix

- fix long desc error in setup.py while installing 

## Support

feel free to check source code in <a href="https://github.com/guangyu-he/universal_date_parser">GitHub</a>, you are
welcome
to leave any comments.

2022&copy;Guangyu He, for further support please contact author. <br>
Email: <a href="mailto:me@heguangyu.net">me@heguangyu.net</a>
localizedpydantic 0.3.0
Library to validate localized data with pydantic
Requires Python: >=3.7

# LocalizedPydantic - UNDER CONSTRUCTION

LocalizedPydantic is a Python library for validating localized data, such as Brazilian CEPs and CPFs. The library is designed to be extensible, so that other developers can contribute validation rules for their own countries.

## Installation

Install with pip:

```bash 
    pip install localizedpydantic
```

## Usage

Here's an example of how to use LocalizedPydantic to validate a Brazilian CEP:

```python
from localizedpydantic.models.brazil import CPF
from pydantic import ValidationError

try:
    cpf = CPF(cpf='123.456.789-00')
    print(cpf.cpf)  # '123.456.789-00'
except ValidationError as e:
    print(e)

try:
    cpf = CPF(cpf='12345678900')
    print(cpf.cpf)  # raises ValidationError
except ValidationError as e:
    print(e)

```

## Contributing
Contributions are welcome! To contribute, please submit a pull request.

## License
LocalizedPydantic is licensed under the MIT license
PyLanguageEasySeperated 1.0.1
PyLanguageEasySeperated
Keywords: python,Pylan,pylan,EasyPython,EasyPyLan,easypylan,pygame,game,image


Easy Python Language

Helps you to make python easier and more understandable

some example:
you can change color of text, print on same line, delete and re-output again and many others, image process.
It makes making 2d game easier you can scroll background with just one line of code, check user input, collide and many others.
put image, and many others
calculate any number like using calculate("2+2*4/5") and builtin bot

turn text to speech and speech to text just on one of code

some function

Bot()
calculate()
re_output()
resizeImage() 
and many others

join on discord (Shiva321#1848) for update and help.
PyLanguageEasy 1.0.1
PyLanguageEasy
Keywords: python,Pylan,pylan,EasyPython,EasyPyLan,easypylan,pygame,game,image


Easy Python Language

Helps you to make python easier and more understandable

some example:
you can change color of text, print on same line, delete and re-output again and many others, image process.
It makes making 2d game easier you can scroll background with just one line of code, check user input, collide and many others.
put image, and many others
calculate any number like using calculate("2+2*4/5") and builtin bot

turn text to speech and speech to text just on one of code

some function

Bot()
calculate()
re_output()
resizeImage() 
and many others

join on discord (Shiva321#1848) for update and help.
pipeline-core 0.0.0
The PipelineCore CLI.
Requires Python: >=3.10,<4.0

# pipeline-core
The PipelineCore repo.

# commands

## auth
- `pcore credentials|credential add|rm|ls|get|use gcp <credentials-name>`

## create radish deployment
- `pcore clusters|cluster create|rm pcloud|gcp|aws|azure <cluster-name>`

## radish cluster management
- `pcore clusters|cluster config <cluster-alias> [sub command]`:
    - `scaling-strategy|caching-strategy|routing-strategy set|get|list`
    - `gpu-pools add|rm|list|get`