semvec/pypi-packages huggingface dataset:
gpx-renamer 0.0.2
File renamer for GPX traces
Requires Python: >=3.6
Keywords: GIS,GPS,gpx,trace,track,rename,script

# gpx-renamer

File renamer for GPX traces


### Description

Small script to parse and rename GPX file based on its data like start date, recorded length, GPS bound coordinates, towns passed through (using offline reverse-geocode module).


### General workflow

    # move gpx files out of subdirectories (Like OSMTracker structure)
    mv */*.gpx .

    # delete empty folders
    find . -type d -delete

    # simulate renaming
    gpx-renamer-short -s *.gpx

    # rename for real
    gpx-renamer-short -r *.gpx


### CLI help


    usage: gpx-renamer [-h] [-c] [-d] [-f FORMAT] [-l] [-t] [-r] [-s] files [files ...]

    File renamer for GPX traces.

    positional arguments:
      files                 files to be processed

    optional arguments:
      -h, --help            show this help message and exit
      -c, --copy            copy instead of rename/move
      -d, --debug           activate debug output, can be used to see all Format keywords
      -f FORMAT, --format FORMAT
                            use custom format
      -l, --long            use long format for name: {startdate}-{starttime}_{minlat},{minlon}-{maxlat},{maxlon}_{cities}_{length}_{points}
      -t, --short           use short format for name: {startdate}-{starttime}_{minlat},{minlon}-{maxlat},{maxlon}_{edges}_{length}
      -r, --rename          rename, defaut is using minimum format: {startdate}-{starttime}_{edges}
      -s, --simulate        dry run

    Helper proxies: gpx-renamer-min same as using -r, gpx-renamer-short same as using -r -t, gpx-renamer-long same as using -r -l


### Why need such tool?

- When using multiple recording devices, each has its own trace naming convension. Seems more effective to keep file in chronical order. Ex: `YYYYMMDD` is sortable better than other date formats.
- Categorize GPX based on covered location (city, town, geocode) in automated way.
- Easier to tag when uploading to Open Street Map OSM.


### Dependencies

- `gpxpy`  
- `reverse-geocode`


### Installation from source

    #day1
    pip3 install -q build

    #day2
    python3 -m build
    pip3 install dist/gpx-renamer-0.0.1.tar.gz


### PyPI upload new modified source

    #day1
    pip3 install twine

    #day2
    twine upload dist/*

### Related Resources


- [Best practices file naming](https://library.stanford.edu/research/data-management-services/data-best-practices/best-practices-file-naming)


### Useful tools

- [Validation](https://www.topografix.com/gpx_validation.asp)

        saxcount -v=always -n -s -f file.gpx

- Validation using `gpxpy`

        gpxinfo file.gpx

- Split tracks using `gpxutils`

        gpxclean -n -s 1000 file.gpx

- Generate map using `papermap`

        papermap -sc 10000 wgs84 36.78189 5.90056 Taher.pdf`

- Splice and clean GPX using GPSPrune (GUI tool)
oneNeuron-pypi-ShrutiV01 0.0.2
Its a description of Perceptron
Requires Python: >=3.7

# oneNeuron_pypi
oneNeuron_pypi



## How to use this

```python
from oneNeuron.perceptron import Perceptron

## get X and y and then use below commands
model = Perceptron(eta=eta, epochs=epochs)
model.fit(X, y)
```
# Reference -
[Official Python Docs](https://packaging.python.org/tutorials/packaging-projects/)

[Github docs for github actions](https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python#publishing-to-package-registries)

![GIF FILE]()
suntransit 0.1.0
Simple, fast approximation of sunrise, sunset time on Earth
Requires Python: >=3.5

suntransit
==========

**Simple, fast approximation of sunrise, sunset time on Earth.**

[![DOI](https://zenodo.org/badge/414701058.svg)](https://zenodo.org/badge/latestdoi/414701058)


Installation
------------

It is recommended to install with `pip`:

```sh
pip install suntransit
```

The only dependency is `numpy`.


Documentation
-------------

[Online documentation can be found here.](https://arthur-e.github.io/suntransit/)


Testing
-------

```sh
python tests/tests.py
```


References
----------

Meeus, Jean. "Astronomical Algorithms." 1991. William-Bell Inc. Richmond, Virginia, U.S.A.

U.S. Naval Observatory. "Almanac for Computers." 1990. Reproduced by
    Ed Williams. https://www.edwilliams.org/sunrise_sunset_algorithm.htm
iotnode 0.1.2
Framework for running embedded code with multiple modular sources of data input/output

# IoT Node Framework
This code provides a framework for running embedded code with multiple modular sources of data input/output.

## Installation
```pip install iotnode```

## Changes
0.1.2 - Added data store with lock for sharing data between threads
0.1.0 - Switched to using threading rather than multiprocessing

## Contributors
Ben Hussey (<a href="mailto:ben@blip2.net">ben@blip2.net</a>)
perceptron-pypi-saiprasad-reddy 0.0.2
Its an implementation of perceptron
Requires Python: >=3.7

# perceptron_pypi
perceptron_pypi

## How to use this package
```python
from oneNeuron.perceptron import Perceptron

## get X and y and then use below commands
model = Perceptron(eta=eta, epochs=epochs)
model.fit(X, y)
```

# refernce
[official python doc](https://packaging.python.org/tutorials/packaging-projects/)

[git docs for git actions](https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python#publishing-to-package-registries)
pyaltiforce 1.1.0
Python Parsing for AltiForce GoPro Backpack CSVs.
Requires Python: >=3.8,<3.11

# pyAltiForce
Python Parsing for AltiForce GoPro Backpack CSVs

The CSV file is processed and a plot of time vs. total acceleration is displayed.

## Usage
Calling `pyAltiForce` from the command line with no arguments opens a file selection GUI for the user to select a single CSV file to process and display.

Calling `pyAltiForce` with the optional `-f` or `--file` flag will allow the user to specify a single CSV file to process.

Examples Include:

    python pyAltiForce -f './Data/GOPR0024.CSV'
    python pyAltiForce --file 'C:/My Data/GOPR0024.CSV'
BubbleTea-py 0.0.7
BubbleTea enables developers to quickly build any data applications on the emerging Web3 infrastructure.
Requires Python: >=3.6

Bubbletea
--

A python library which enables developers and data scientists to quickly build any data applications on top of The Graph network. Whether you are building dashboards to visualize protocol data or leveraging existing machine learning models to do some data science work, we hope this library will be the fastest way to get what you want.

This project is made possible by a grant (wave 2) from The Graph foundation. 

### What problems are we solving
- An improved way to query data from The Graph network
- A set of handy functions for common data transformations (built on Pandas)
- A set of out-of-box charting components to make visualizations effortless (built on Altair)
- A simple templating system to build dashboards (built on Streamlit)

### Install
pip install BubbleTea-py

### [Demos](https://bubbletea-demo.herokuapp.com/?demo=demo_1.py)


### [Documentation](https://scout-1.gitbook.io/bubbletea/)



### Get in touch
https://twitter.com/scout_cool