semvec/pypi-packages huggingface dataset:
pyqode3-core 4.0.1
The core package contains the core components needed for writing a pyqode based
Requires Python: >=3.7
Keywords: CodeEdit,PyQt,editor,widget,qt

.. image:: https://raw.githubusercontent.com/pyQode/pyQode/master/media/pyqode-banner.png

About
-----


This is a fork of PyQode, which is now developed as the editor component for Rapunzel_ and OpenSesame_. The original PyQode repository (<= v2) is no longer maintained.

**pyqode.core** is the core framework of the `pyQode` project.

It contains the base classes and a set of extensions (modes/panels/managers)
needed to develop a specialised code editor.

It also provides a basic generic code editor that you can use as a fallback
when there is no specialised editor for a given language.

.. _OpenSesame: https://osdoc.cogsci.nl/
.. _Rapunzel: https://rapunzel.cogsci.nl/


License
-------

pyQode is licensed under the **MIT license**.


Requirements
------------

pyqode.core depends on the following libraries:

- Python 3 (>= 3.7)
- PyQt5 or PyQt6 or PySide
- pygments
- pyqode.qt
- future
- qtawesome (optional)
sklearn-cv-pandas 0.0.12
RandomizedSearchCV/GridSearchCV with pandas.DataFrame interface
Requires Python: >=3.6

# sklearn-cv-pandas
RandomizedSearchCV/GridSearchCV with pandas.DataFrame interface

## Why do I want this?

- I usually prepare features as pandas.DataFrame
- Scikit learn input should be `array-like`. https://scikit-learn.org/stable/glossary.html#term-array-like.
- Although it includes pandas.DataFrame, there are some issues;
    - It does not support `Int64` data type
    - Output model does not remember which columns should be used

## Solution

- Provide GridSearchCV / RandomizedSearchCV with pandas.DataFrame interface
    - Internally preprocess DataFrame to be applicable for sklearn
- Output of `fit` command is now original `Model` object, which
    - stores column name information
    - provides pandas.DataFrame interface for prediction


## Installation
```
pip install sklearn_cv_pandas
```

## Usage

### Configure CV object

Instantiate CV in the same manner as original ones.
```
from scipy import stats
from sklearn import linear_model
from sklearn_cv_pandas import RandomizedSearchCV

estimator = linear_model.Lasso()
param_dist = dict(alpha=stats.loguniform(1e-5, 10))
cv = RandomizedSearchCV(estimator, param_dist, scoring="mean_absolute_error")
```

### `fit` with pandas.DataFrame

Our CV object has new methods `fit_holdout_pandas` and `fit_cv_pandas`.
Original ones requires `x` and `y` as `numpy.array`.
Instead of numpy array, you can specify one `pandas.DataFrame` 
and column names for `x` (`feature_columns`), and column name of `y` (`target_column`).
```
model = cv.fit_cv_pandas(
    df, target_column="y", feature_columns=["x{}".format(i) for i in range(100)], n_fold=5
)
```

### `predict` with pandas.DataFrame

You can run prediction with pandas.DataFrame interface as well.
Output of `fit_holdout_pandas` and `fit_cv_pandas` stores `feature_columns` and `target_column`.
You can just input `pandas.DataFrame` for prediction into the method `predict`.

```
model.predict(df)
```
boofoo 1.6
Get cli commands
Requires Python: >=3.6

# BooFoo 1.3

Obtain your openai API key from https://platform.openai.com/account/api-keys

Sotre API key in config.cfg file
CHATGPT_API_KEY: [Your API key]

Support: naif@naif.io

MIT License

Copyright (c) 2023 Naif Alshaye

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.