semvec/pypi-packages huggingface dataset:
skycord 0.4.1
An easy-to-use extension for the Pycord library
License: MIT
Requires Python: >=3.9
Keywords: discord,pycord,py-cord

[![skycord](https://skycord.readthedocs.io/en/latest/_static/skycord.png)](https://github.com/svtano/skycord3)

[![](https://img.shields.io/discord/1010915072694046794?label=discord&style=for-the-badge&logo=discord&color=5865F2&logoColor=white)](https://discord.gg/zfvbjTEzv6)
[![](https://img.shields.io/pypi/v/skycord.svg?style=for-the-badge&logo=pypi&color=yellow&logoColor=white)](https://pypi.org/project/skycord/)
[![](https://img.shields.io/pypi/l/skycord?style=for-the-badge)](https://github.com/svtano/skycord3/blob/main/LICENSE)
[![](https://aschey.tech/tokei/github/tibue99/skycord?style=for-the-badge)](https://github.com/svtano/skycord3)

An easy-to-use extension for the [Pycord](https://github.com/Pycord-Development/pycord) library with some utility functions.

## ⚠️ Note
Please use this library with the [Pycord master branch](https://github.com/Pycord-Development/pycord).

## Features
- Easy cog loading
- Automatic error handling
- Error report webhooks
- Embed templates
- Beautiful ready event
- Custom logging
- Automated help command
- Datetime and file utilities
- Wrapper for [aiosqlite](https://github.com/omnilib/aiosqlite)

While this library can be installed with any Discord library, most features will only work with Pycord.

## Installing
Python 3.9 or higher is required.
```
pip install skycord
```
You can also install the latest version from GitHub. Note that this version may be unstable
and requires [git](https://git-scm.com/downloads) to be installed.
```
pip install git+https://github.com/svtano/skycord3
```
If you need the latest version in your `requirements.txt` file, you can add this line:
```
skycord @ git+https://github.com/svtano/skycord3
```

## Useful Links
- [Documentation](https://skycord.readthedocs.io/)
- [Getting started](https://skycord.readthedocs.io/en/latest/pages/getting_started.html)
- [PyPi](https://pypi.org/project/skycord/)
- [Pycord Docs](https://docs.pycord.dev/)

## Example
- For more examples, see the [example repository](https://github.com/svtano/skycord3_template)
or the [sample code](https://skycord.readthedocs.io/en/latest/examples/examples.html).

```py
import skycord
import discord

bot = skycord.Bot(
    intents=discord.Intents.default()
)

if __name__ == "__main__":
    bot.load_cogs("cogs")  # Load all cogs in the "cogs" folder
    bot.run("TOKEN")
```
**Note:** It's recommended to [load the token](https://guide.pycord.dev/getting-started/creating-your-first-bot#protecting-tokens) from a `.env` file instead of hardcoding it.
skycord can automatically load the token if a `TOKEN` variable is present in the `.env` file.

## Contributing
I am always happy to receive contributions. Here is how to do it:
1. Fork this repository
2. Make changes
3. Create a pull request

You can also [create an issue](https://github.com/svtano/skycord3/issues/new) if you find any bugs.
properties.py 1.2.1
Module for reading/writing properties-files.
License: MIT
Requires Python: >=3.7
Keywords: properties,java,io,file,read,write

# properties.py
## Description
Module for reading/writing properties-files.

## Installation
```shell
pip install -U properties.py
```

## Usage
#### Code
```python
import properties

user = {"name": "NoName", "age": -1, "sex": "M", "data": {"region": 39, "keywords": ["man", "human", 14.88]}}

with open("test.properties", "w", encoding="utf-8", errors="ignore") as file:
    properties.dump(user, file)

with open("test.properties", "r", encoding="utf-8", errors="ignore") as file:
    data = properties.load(file)

print(data)
```
#### Output
```python
{'name': 'NoName', 'age': -1, 'sex': 'M', 'data': {'region': 39, 'keywords': ['man', 'human', 14.88]}}
```
psfmachine 1.1.4
Tool to perform fast PSF photometry of primary and background targets from Kepler/K2 Target Pixel Files
License: MIT
Requires Python: >=3.8,<4.0
Keywords: NASA, Kepler, Astronomy

# PSFMachine

*PRF photometry with Kepler*

<a href="https://github.com/ssdatalab/psfmachine/workflows/tests.yml"><img src="https://github.com/ssdatalab/psfmachine/workflows/pytest/badge.svg" alt="Test status"/></a>
<a href="https://pypi.python.org/pypi/psfmachine"><img src="https://img.shields.io/pypi/v/psfmachine" alt="pypi status"></a>
<a href="https://zenodo.org/record/4784073"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.4784073.svg"></a>

Check out the [documentation](https://ssdatalab.github.io/psfmachine/).
Check out the [paper](#)

`PSFMachine` is an open source Python tool for creating models of instrument effective Point Spread Functions (ePSFs), a.k.a Pixel Response Functions (PRFs). These models are then used to fit a scene in a stack of astronomical images. `PSFMachine` is able to quickly derive photometry from stacks of *Kepler* images and separate crowded sources.

# Installation

```
pip install psfmachine
```

# Example use

Below is an example script that shows how to use `PSFMachine`. Depending on the speed or your computer fitting this sort of model will probably take ~10 minutes to build 200 light curves. You can speed this up by changing some of the input parameters.

```python
import psfmachine as psf
import lightkurve as lk
tpfs = lk.search_targetpixelfile('Kepler-16', mission='Kepler', quarter=12, radius=1000, limit=200, cadence='long').download_all(quality_bitmask=None)
machine = psf.TPFMachine.from_TPFs(tpfs, n_r_knots=10, n_phi_knots=12)
machine.fit_lightcurves()
```

Funding for this project is provided by NASA ROSES grant number 80NSSC20K0874.