semvec/pypi-packages huggingface dataset:
seing4python 0.0.1
Python implementation of the SEING package
Keywords: python,molecular fingerprinting,molecular dynamics,machine learning

SEING is a C/C++ package for fingerprint calculations suitable for machine learning studies of molecular systems.

SEING was developed in the Clancy Group by Mardochee Reveil (mr937@cornell.edu). The Python implementation is done by Man Kit Ao (mao2@jh.edu) and Divya Sharma (dsharm23@jh.edu).

Fingerprints (in this context) are numerical representations of chemical environments designed to be invariant under property-perseving operations such as permutation of atoms of the same nature, geometric rotation, etc. For more information on fingerprints in general and the ones currently implemented in SEING, please see the official documentation and user-guide.
termaths-ROUX-BENOIT 0.0.1
Un module de maths pour des élèves de terminales en spécialité maths ou en maths expertes.
Requires Python: >=3.6

# Termaths

Termaths est un module qui est précu pour les élèves de terminale en spécialité maths ou en maths experts.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install foobar.

```bash
pip install foobar
```

## License
[MIT](https://choosealicense.com/licenses/mit/)
lazy-table 0.2.1
A python-tabulate wrapper for producing tables from generators
Requires Python: >=3.6

[![](https://static.pepy.tech/personalized-badge/lazy-table?period=total&units=international_system&left_color=grey&right_color=blue&left_text=pypi%20downloads)](https://pepy.tech/project/lazy-table)
[![](https://badge.fury.io/py/lazy-table.svg)](https://badge.fury.io/py/lazy-table)
![](https://img.shields.io/pypi/pyversions/lazy-table.svg)

<p align="center">
  <img alt="lazy_table" src="https://raw.githubusercontent.com/parsiad/lazy-table/master/logo.png">
</p>

A [python-tabulate](https://github.com/astanin/python-tabulate) wrapper for producing tables from generators.

## Motivation

lazy_table is useful when (*i*) each row of your table is generated by a possibly expensive computation and (*ii*) you want to print rows to the screen as soon as they are available.

For example, the rows in the table below correspond to [numerically solving an ordinary differential equation](https://en.wikipedia.org/wiki/Numerical_methods_for_ordinary_differential_equations) with progressively more steps. See [examples/euler_vdp.py](https://raw.githubusercontent.com/parsiad/lazy-table/master/examples/euler_vdp.py) for the code to generate this table.

![](https://github.com/parsiad/lazy-table/blob/main/examples/euler_vdp.gif?raw=true)

Here is the same example with a progress bar.

![](https://github.com/parsiad/lazy-table/blob/main/examples/euler_vdp_with_progress.gif?raw=true)

## Installation and usage

Install lazy_table via pip:

```console
$ pip install lazy_table
```

In your Python code, add

```python
import lazy_table as lt
```

Now, generating your own lazy table is as simple as calling `lt.stream` on a generator that yields one or more lists, where each list is a row of your table (see the example below).

## Example

As a toy example, consider printing the first 10 [Fibonacci numbers](https://en.wikipedia.org/wiki/Fibonacci_number) in a table.
Since this is a relatively cheap operation, we will pretend it is expensive by adding an artificial `sleep(1)` call beteween Fibonacci numbers.

```python
import time
import lazy_table as lt

def fib_table(n):
     x0, x1 = 0, 1
     yield [0, x0]
     yield [1, x1]
     for i in range(2, n + 1):
         time.sleep(1)  # Simulate work
         x0, x1 = x1, x0 + x1
         yield [i, x1]

lt.stream(fib_table(10), headers=['N', 'F_N'])
```

Your final table should look like this:

```
  N    F_N
---  -----
  0      0
  1      1
  2      1
  3      2
  4      3
  5      5
  6      8
  7     13
  8     21
  9     34
 10     55
```

You can also specify an "artist" that determines how the table is rendered.
For example, the `ConsoleWithProgress` artist displays a progress bar alongside the table indicating the percentage of rows completed:

```python
n = 10
artist = lt.artists.ConsoleWithProgress()
lt.stream(fib_table(n), headers=['N', 'F_N'], n_rows=n + 1, artist=artist)
```
autowallpaper 0.0.2
Package that helps you create your own wallpaper changing service
Requires Python: >=3.6

# autowallpaper

A python module that allows you to create your own wallpaper setting service.

## Installation

```shell
$ pip install autowallpaper
```

## Basic Usage

1. Create a new Python file.
1. In the file, write your own function (say, `my_image_function()`).This function should return the URL or file path of the image to be set as wallpaper. This function will be called every time the wallpaper is to be changed.
2. Create an object of `AutoWallpaper` with your function as the argument.
3. Run it with
    ```python
    from autowallpaper import AutoWallpaper

    autowallpaper = AutoWallpaper(
        my_image_function,
        # other arguments
    )

    autowallpaper.start()   # Starts the daemon
    autowallpaper.restart() # Restarts the daemon
    autowallpaper.stop()    # Stops the daemon
    ```
4. _(OPTIONAL)_ You can extend class `AutoWallpaper` and override `run()` to make your own scheduler, that changes wallpaper more frequently, less frequently, etc.

You can change where downloaded images and logs are stored using arguments to `AutoWallpaper`.

## Demo - NASA APOD

A working demo implementation is available in `demo/nasa_wallpaper.py`. This changes the wallpaper every 24 hours to the image featured on [NASA's Astronomy Picture of the Day](https://apod.nasa.gov/).

### Usage
1. Get an API key from [the NASA API website](https://api.nasa.gov). Save it in a file or just copy it.
2. Move `demo/nasa_wallpaper.py` in the parent directory (so the imports work fine).
3. Run using\
`$ python nasa_wallpaper.py -k [KEY | PATH_TO_KEYFILE] start|stop|restart`
4. Use `$ python nasa_wallpaper.py -h` to see additional options



---

## TODOs

- Add support to source automatically from a folder
- Simplify command for demo
- Add option to save all downloaded images instead of only the latest one
- Make logging optional
- Change paths for Windows
- Test Windows and Linux environments
- Add support for more environments
- ???