semvec/pypi-packages huggingface dataset:
PyPreprocess 1.0.0
Preprocess SDK
Keywords: python,python3,preprocess,chunks,paragraphs,chunk,paragraph,llama,llamaondex,langchain


# Preprocess SDK
_**This is a repository for sdk for preprocess that will be used to interact with the system.**_

## Initialise a connection
>First, you should have an api key to use it, otherwise you'll not be allowed to connect/interact with preprocess system
To get an api key, feel free to send a request to [Support](mailto:support@preprocess.co) asking for an api key.

```
1- preprocess = Preprocess(api_key=YOUR_API_KEY, filepath="path/for/file")
2- preprocess = Preprocess(api_key=YOUR_API_KEY, process_id="id_of_the_process")
3- preprocess = Preprocess(api_key=YOUR_API_KEY, process=ProcessResponse)
```

## Chunk
>Here you have to pass the filepath then call chunk method for chunking and it'll return to you a ProcessResponse object containing all info you'll need.

```
1- response = preprocess.chunk()
```

## Getting the results
>You can directly call one of those methods that'll be listed to get the result after getting a success chunk call, or whenever you want call them after initialise the Preprocess object with either `process_id` or `process` which is a PreprocessResponse object, and the result will be always a PreprocessResponse containing the chunks inside data parameter.

- If you want to wait until it finish use `wait()` method
    ```
    1, 2 and 3- result = preprocess.wait()
    - print(result.data['chunks'])
    ```
- If you don't want to wait consider calling `result()` and check the status if it's not FINISHED or OK, so it's still chunking.
    ```
    1, 2 and 3- result = preprocess.result()
    - if result.status in ["FINISHED", "OK"]: 
    -   print(result.data['chunks'])
    ```
## Other methods
>This part will containing some existing function may help you 

- `set_filepath(path)` setting the file path after initialise the object.
- `set_process_id(id)` setting the process_id param by id.
- `set_process(process)` setting the process_id param by PrepreocessResponse object.
- `set_info(dict)` info for handle the chunking based on your needs.
- `to_json()` returning a json str representing the current object.
edvinspythonlib 0.2.0
My first Python library

# Edvins Python Library
My library for personally coded python functions and classes
<br> Is sorted into my courses right now
<br> The library isn't superrr useful, but it's fun

### Installation
```
pip install edvinspythonlib
```

### Get started
How to use one of my functions or classes in your own code

```Python
# Import one of the modules
from edvinspythonlib import machinelearning as ml

# Call the method you wish to use
model = ml.linearRegression()
model.fit(X,y)
model.residualPlot(X,y)
```

### Documentation
Currently the three working modules are:
* machinelearning
* imageanalysis
* algodata

Later I hope to also add funtionality for:
* mathstat
* computervision
* reinforcementlearning
* activemachinelearning

Testing is currently sparse, but I hope to work on that soon

### machinelearning
Some functions and classes for my course "Machine learning and data mining"
Current implementations:
* function standardizedata
* function PCAe
* function kFoldCV
* function nestedCV
* class linearRegression
* class baselineRegression

### algodata
Some functions and classes for my course "Algorithms and data structures"
Current implementations:
* class Stack
* class Queue
* function SA

### imageanalysis
Some functions and classes for my course "Image analysis"
Current implementations:
* function plotimg
* function todecimal
* function tobin
* function histogram
* function changevectorbasis
* function thinlensequation
* function runlengthencoding
* function chaincode
* function stretchimage
* function stretchfunction
* function gammamapping
* function logmapping
* function bilinear
* function calculateR
* function calculateentropy
sphinx-jupyterbook-latex 1.0.0
Latex specific features for jupyter book
Requires Python: >=3.9

# sphinx-jupyterbook-latex

[![Documentation Status](https://readthedocs.org/projects/sphinx-jupyterbook-latex/badge/?version=latest)](https://sphinx-jupyterbook-latex.readthedocs.io/en/latest/?badge=latest)

Sphinx extension to support LaTeX infrastructure for Jupyter Book.

This repository is a **development** project to improve LaTeX support
in `Jupyter Book`.

## Get started

To get started with `sphinx-jupyterbook-latex`, first install it through `pip`:

```
pip install sphinx-jupyterbook-latex
```

then, add `sphinx_jupyterbook_latex` to your extensions,
in a Sphinx `conf.py`:

```python
extensions = ["sphinx_jupyterbook_latex"]

# autoload the sphinx.ext.imgconverter extension, optional (default is True)
# jblatex_load_imgconverter = True
# turn root level toctree captions into top-level `part` headings, optional (default is to auto-infer)
#  jblatex_captions_to_parts = True
```

OR in the jupyterbook `config.yml`:

```yaml
sphinx:
    extra_extensions:
    - sphinx_jupyterbook_latex
    # config:
    #   jblatex_load_imgconverter: true
    #   jblatex_captions_to_parts: true
```

## Extension Details

This extension does not provide an actual Sphinx LaTeX theme,
instead it instantiates a number of transforms (for LaTeX builders only) that manipulate the AST into the required format:

1. Overrides some configuration:

- ``latex_engine`` -> ``xelatex``
- ``latex_theme`` -> ``jupyterBook``
- appends necessary LaTeX commands to the preamble

2. When a latex builder is specified:

- Set's up `sphinx.ext.imgconverter` (if `jblatex_load_imgconverter`)
- Replace sub-headers in the root document
- Create headings from the root-level toctree captions (if `jblatex_captions_to_parts`)
- Move bibliographies to the bottom of the document

Issues
------

A list of issues that need to be addressed:

https://github.com/executablebooks/meta/issues/169

Developer Notes
---------------

A [repository that contains many different project configurations](https://github.com/mmcky/ebp-test-projectstructure)
for testing and development is available, along with implementation
idea and notes