semvec/pypi-packages huggingface dataset:
nester2023 1.1.0
A simple printer of nested lists



1) This function takes a positional arguments called "the_list","indent" and "level", 'the_list' is
any Python list (of - possibly - nested lists). Each data item in the 
provided list is (recursively) printed to the screen on it's own line.
2) A second argument 'indent' is set to default value 'False', which means indentation or tab-stops are not required
by default. If user wants to add indentation while printing the nested list it should be set to 'True'.
3) A Third argument 'level' is used to insert required number of tab_stops when nested list is encountered.
4) Fourth argument 'fh' is used to specify where the output of this function should write (place to write your
data to), a default value of this argument is sys.stdout so that it continues to write to the screen if no file object
is specified when the function is invoked.
flask-rules 0.1.0
Access rules for Flask applications, inspired by django-rules.
Requires Python: >=3.10,<4.0

# Flask-Rules

Forked from django-rules by Akis Kesoglou.

The original project is available at: <http://github.com/dfunckt/django-rules>.


## Licence

`flask-rules` is distributed under the MIT licence.

> Copyright (c) 2023 Stefane Fermigier / Abilian SAS
> Copyright (c) 2014 Akis Kesoglou

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.
KrakenPythonM-R 0.1.0
A streamlit tool for rendering kraken data
Requires Python: >=3.6

Python Data Analysis Project

This project is a tool for analyzing currency pairs on the Kraken cryptocurrency exchange. It uses the Kraken API to fetch real-time price data for various currency pairs and visualizes this data using the Plotly library. Additionally, it calculates technical analysis indicators such as the stochastic oscillator and its moving average, which can assist in trading decisions.

The project is written in Python and uses several libraries, including pandas for data manipulation, plotly for data visualization, and krakenex for interacting with the Kraken API. It also uses Streamlit for the web application functionality.
Project Structure

The main code for the project is located in main.py, which imports and uses functions and classes defined in other modules. These modules include graphs.py, which contains the Graph class for creating candlestick charts and stochastic oscillators, and front.py, which contains the Front class for handling the user interface of the application.

The project also includes a requirements.txt file that lists the Python packages required to run the project. The project can be run in a Docker container using the provided Dockerfile.

The project includes a tests.py file for unit testing and integration testing. The tests cover the initialization of the Front and Graph classes, the retrieval of currency pairs from the Kraken API, and the creation of Plotly graphs.
How to Run the Project

To run the project, you need to have Python installed on your machine. You can then install the required packages using pip:

$pip install -r requirements.txt

After installing the required packages, you can run the project using the following command:

$streamlit run main.py

This will start the Streamlit app and open it in your web browser.
Documentation

The project includes a docs folder that contains several text files providing more details about the project and its requirements. The enunciado.txt file contains the details of the project statement, and the memoria_kraken.lyx file contains the project report.

Authors

This project was created by Rodrigo de la Nuez Moraleda and Marcos Castro Cacho.