pansapiens

# Build like:
#   docker buildx build -t acestep-cuda -f Dockerfile .
#
# Run like:
#   docker run --gpus all -p 8085:8085 acestep-cuda
#
# With custom options:
#   docker run --gpus all -p 8085:8085 \
#     -e ACE_PORT=8085 \
#     -e ACE_MAX_BATCH=2 \

pansapiens

# /// script
# requires-python = ">=3.11"
# dependencies = [
#     "mido",
#     "python-rtmidi",
# ]
# ///

import mido
import argparse

pansapiens

#!/bin/bash

set -euo pipefail

function show_usage() {
    echo "Usage: $0 <input.sif> [docker_image_name:tag]"
    echo
    echo "Converts a Apptainer/Singularity SIF file to a Docker image."
    echo
    echo "Arguments:"

pansapiens

#!/usr/bin/env python
# MIT License
# Copyright (c) 2022 Zebulun Arendsee (rhmmer code)
# Copyright (c) 2025 Andrew Perry (port to Python)

# 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

pansapiens

pansapiens

#!/bin/bash
# Ollama Model Export Script
# Usage: bash ollama-export.sh vicuna:7b
# License: MIT (https://ncurl.xyz/s/o_o6DVqIR)
# https://gist.github.com/supersonictw/f6cf5e599377132fe5e180b3d495c553

set -e

echo "Ollama Model Export Script"
echo "License: MIT (https://ncurl.xyz/s/RD0Yl5fSg)"

pansapiens

#!/usr/bin/env python2.7

# Export from Google App Engine Datastore Backup LevelDB format to JSON flat file
# Based on: https://gist.github.com/xlfe/af25f160256e4d52f499dee7e8fa212f

##
# 2024 instructions:
##
# Using the Google Cloud console (https://console.cloud.google.com), find "Firestore"
# and export your database to a Cloud Storage "Bucket". Download the content of the Bucket.

pansapiens

#!/usr/bin/env python

###
# bam2fq_softclip.py
###
# A script for exploring soft-clipping of aligned reads.
# Extracts mapped reads from a BAM file as a FASTQ, but encodes 'soft-clipped' regions
# as lowercase. Soft-clipped regions can be quickly visualized in the terminal like:
# 
# ./bam2fq_softclip.py aligned.bam | grep --color=always [atcg] |less -R

pansapiens

A simple Docker Compose recipe for schollz/hostyoself.

pansapiens

#!/usr/bin/env python

import argparse
import pandas as pd
import re
import sys
from typing import Optional, List
import logging
import glob
import io