semvec/pypi-packages huggingface dataset:
render-html 1.0.1
Python library that provides a simple way to render HTML content in a web browser.
Requires Python: >=3.10

# render_html

`render_html` is a Python library that provides a simple way to render HTML content in a web browser. 
It allows you to open HTML content directly from a string or save it to a file and open it from the file.
You can also specify the name of a browser to use a non-default browser. Please refer to [webbrowser documentation](https://docs.python.org/3/library/webbrowser.html) for the complete list of predefined browsers.
This library is especially useful for quickly visualizing and testing HTML content in a web browser environment.

## Installation

You can install `render_html` using pip:

pip install render-html

NOTE: the library requires Python 3.10 or newer

## Usage

```python
from render_html import render_in_browser as ren
import requests

# Making a request with the requests library
response = requests.get('https://example.com')

# Rendering the HTML response in the default browser
html_content = response.text
ren(html_content)
```

## Documentation

### `render_in_browser(html_string, save_path=None, browser=None)`

Render the HTML content in a web browser.

- `html_string` (str): The HTML content as a string.
- `save_path` (str, optional): The path to save the HTML content as a file.
  If provided, the HTML content will be saved to the specified file and opened from it.
  If not provided or set to `None`, a temporary file will be created in the operating 
  system's default temporary directory. The temporary file will be removed once the rendering 
  is complete.
- `browser` (str, optional): The name of the web browser to use (i.e., "chrome", "safari").
  If provided, the HTML content will be opened using the specified browser.
  If not provided or set to None, the default browser will be used.


## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
createai 0.1.2.1
Easy tool for creating AI in python
Requires Python: >=3.6


# CreateAI v0.1.2.1
It's easy tool to create ai in python easy and fast.
You can look at source code of CreateAI on [Create AI's github](https://github.com/R0fael/CreateAI)

# WARNING!
On my PC python can't find this module.
I am using source code from github.

## Dependencies
 - numpy
 - knowledge of python
 - our documentation
 - your motivation
 - your brain

## Authors

 - [@R0fael](https://www.github.com/R0fael) - main programmer

## Features
 - Custom function activations
 - Neuron creating in one line of code
 - absolutly open sourse

## Installation

Installing project with pip

Windows:
```bash
pip install createai
```

MacOS:
```bash
pip3 install createai
```

Linux:
```bash
sudo pip install createai
```

Or if you don't have pip :
download sourse code and editing examples files

## Example
```python
# importing CreateAI
from createai import *

n = Neuron(weights(3, 1), inputs([
    [0, 0, 1],
    [1, 1, 1],
    [1, 0, 1],
    [0, 1, 1]
]), outputs([[0, 1, 1, 0]]),save_path="my_save.cns")  # Neuron creating with saving
#.cns -> file extension -> neuron weight save

n.learn(20_000)  # Neuron learning

print(n.process([1, 1, 0]))  # Neuron test
print(n.process([0, 1, 0]))  # Neuron test
```

## Change log

-0.1.0 - first version

-0.1.1 - speed up and little bug fix

-0.1.2 - without numpy - error

-0.1.2.1 - big bugfix

## Plans

-0.1.3 - More metods of learning

-0.1.4 - Multi neurons update
pyconju 0.1.2
Python package for merging multiple files
Requires Python: >=3.7
Keywords: python3,excel,xls,csv,xlsx,merge

# PyConju 

A python package for merging multiple files into a single file. File types supported include: .xlsx, .xls, and .csv.

`PDF` support coming soon!


## Installation on Windows
---
### 1. Create a Project folder
```
mkdir project-folder
cd project-folder
```
### 2. Create a virtual environment
```
python -m venv venv
```
### 3. Activate the virtual environment
```
./venv/Scripts/activate
```
### 4. Install package from PyPi
```
pip install pyconju
``` 

### 5. Usage / Examples

### Example 1
```python
from pyconju.xlsx import Excelx
```
```python
# Initialize object
merger = Excelx
path = "path/to/files/to/merge"
fileList = ["file1.xlsx","file2.xlsx","file3.xlsx"]
merger.merge_xlsx(fileList,path)
```

Out of the box you may encounter this error:

```
ImportError: Pandas requires version '2.0.1' or newer of 'xlrd' (version '1.2.0' currently installed).
```
Don't panic, Uninstall the current version of `xlrd`:

```
(.venv) $ pip uninstall xlrd

   Found existing installation: xlrd 1.2.0
   Uninstalling xlrd-1.2.0:


   Proceed (Y/n)? y
   Successfully uninstalled xlrd-1.2.0
```

Install `xlrd` version `2.0.1`:

```
(.venv) $ pip install xlrd==2.0.1
```

**Try the merging process again; it will work**🤩



###  Example 2
```python
from pyconju.xls import Excel
```
```python
# Initialize object
merger = Excel
path = "path/to/files/to/merge"
fileList = ["file1.xls","file2.xls","file3.xls"]
merger.merge_xls(fileList,path)
```

###  Example 3
```python
from pyconju.csv import Csv
```
```python
# Initialize object
merger = Csv
path = "path/to/files/to/merge"
fileList = ["file1.xlsx","file2.xlsx","file3.xlsx"]
merger.merge_csv(fileList,path)
```
## Contributing
You are welcome to contribute to the repo as you like

## Authors and acknowledgment
Agee Aondo

Email: ageeaondo45@gmail.com

Website: https://linktr.ee/dyagee

## License
See LICENSE file
niota 0.8.0
Numbers IOTA tool
Requires Python: >=3.6

# NIOTA

Make IOTA to be an integrity chain.

Niota registers Asset history records to the integrity chain.

## Installation

```shell
python3 -m pip install niota
 ```

## Unit Testing

```shell
make test
```

## Usage

### Iota Client

The `IotaClient` class is a client to interact with [IOTA REST API](https://editor.swagger.io/?url=https://raw.githubusercontent.com/rufsam/protocol-rfcs/master/text/0026-rest-api/0026-rest-api.yaml).

Below is a minimal example for connecting to an IOTA hornet node with JWT authentication enabled, and create a message.

```python
from niota import IotaClient

iota = IotaClient(base_url='https://example.iota.hornet.node', jwt_token='enter JWT token here')
create_message_resp = iota.create_message('example-index', 'example-data')
message_id = create_message_resp.data.messageId
```


### Niota client

The `Niota` class can be used as a client to interact with IOTA Tangle messages with Numbers Protocol integrity record format.

```python

example_integrity_info = {
    'raw_cid': 'bafkreihdwdcefgh4dqkjv67uzcmw7ojee6xedzdetojuzjevtenxquvyku',
    'ida_cid': 'bafkreihdwdcefgh4dqkjv67uzcmw7ojee6xedzdetojuzjevtenxquvyku',
    'ida_mid': 'c7dfa6e5-346d-4b4d-a663-a421e7f9171f',
    'ida_sha256sum': 'e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855',
    'metadata_cid': 'bafkreidgkmzpzvot7a5r2iy44tmcojuvoyjgbwi5udldfisbvn4lnfrmoq',
    'service_message': 'Create test data',
}

niota = Niota(
    base_url='https://example.iota.hornet.node',
    jwt_token='enter JWT token here'
    private_key=private_key,
    public_key=public_key,
)
message_id, index = niota.create_message(**message_data_fixture)

```