semvec/pypi-packages huggingface dataset:
pyspaceaware 0.2.41
A package for Space Domain Awareness simulation, including orbit and attitude propagation, catalog management, with a focus on generating light curves for human-made satellites and debris
Requires Python: >=3.8,<3.12

# PyLightCurves
 Light curve inversion in python with OpenGL simulator backend

# Installation

## Mac (Intel or Apple CPU)
- Prerequisites: 
    - `clang` C compiler from XCode Command Line Tools. If installed, running `clang -v` in Terminal should return version information. If that errors, install directly via `xcode-select --install` or through the web at https://developer.apple.com/download/all/
    - `python3` should be installed by default on all Macs
    - `OpenGL` installed by default
- Clone repository to local folder
- Open terminal at repository top-level folder
- Run `source init_venv` to create and activate a python virtual environment, install dependencies, compile C executables for OpenGL light curve simulation, and run unit tests
- If all tests pass, the repository is fully initialized and all functions work as expected!
- Run `shape_invert_script.py` to perform a sample convex shape inversion

## Windows
- TBD, working on this on Friday with Alex
- Prerequisites:
    - A C compiler, follow this guide: https://learn.microsoft.com/en-us/cpp/build/walkthrough-compile-a-c-program-on-the-command-line?view=msvc-170 to download a compiler and compile a basic `hello_world.c` executable
    - Python 3.10, download through https://www.python.org/downloads/windows/

    - User `bash` through WSL to run `init_venv`
    - `source bin/activate` should be `source Scripts/activate`
    - Still not sure how exactly to compile with `cl` correctly

# Configuration
- The `MODELDIR` path set within `init_venv` can be set to a new directory containing `.obj` and `.mtl` files

# Error Handling
- If you see a `KeyError` for `os.environ['MODELDIR']`, simply run `source init_venv` again to redefine the environment variable
secmarker 0.4.1
secmarker description
Requires Python: >=3.6

# secmarker
Secmarker is a search tool for selenocysteine tRNA (tRNA-Sec) identification. 
The presence of tRNA-Sec in a genome indicates the use of selenocysteine by the organism. 
Old version was written in python2 and now it's written in python3

## SECMARKER 0.4

* Web server
  A SecMarker web server is available for online analysis:
  http://secmarker.crg.es/

* Publication
 Didac Santesmasses, Marco Mariotti and Roderic Guigó. Computational identification of the selenocysteine tRNA (tRNASec) in genomes. PLoS Comput Biol. 2017 Feb 13;13(2):e1005383. doi: 10.1371/journal.pcbi.1005383. 

* Dependencies
  cmsearch and esl-sfetch from the Infernal package (http://infernal.janelia.org/), specifically, version => 1.1 is required.
  RNAplot from ViennaRNA package (http://www.tbi.univie.ac.at/RNA/), version >= 2.0 is known to work fine.

* Installation:
  In order to use Secmarker run the following comands (where x.x corresponds to the current version):

  tar xfz secmarker-x.x.tar.gz
  cd secmarker-x.x
  ./setup.py
  ./run_test.py


* Running Secmarker.py
usage: Secmarker.py [-h] -t TARGET [-o O] [-plot] [-T T] [-F F] [-cpu CPU]
                    [-cca] [-AT12] [-O O]

search for selenocysteine tRNA (tRNA-Sec), marker of Sec trait

optional arguments:
  -h, --help            show this help message and exit
  -t TARGET, --target TARGET
                        target nucleotide sequence
  -o O                  output folder
  -plot                 generate the tRNA plot(s). For each tRNA prediction,
                        two files (.png and .ps) will be generated in the
                        folder images/
  -T T, --infernal_score T
                        score threshold used by cmsearch (Infernal score)
  -F F, --filtering_score F
                        score threshold used to filter tRNAs. If the tRNA has
                        the UCA anticodon or a G73, -T is used for filtering
  -cpu CPU              number of available CPUs [default 1]
  -cca                  include the 3 residues downstream the discriminator
                        base if available (to check if the CCA sequence is
                        encoded in the sequence)
  -AT12                 force a 12 bp AT-stem, that is a 7/5 fold tRNA
  -O O, --options O     additional options for cmsearch