natefoo

name: galaxy_training_material
channels:
  - conda-forge
  - defaults
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=2_gnu
  - binutils_impl_linux-64=2.36.1=h193b22a_2
  - ca-certificates=2022.6.15=ha878542_0
  - gcc=12.1.0=h9ea6d83_10

natefoo

#!/bin/bash
# stopgap to build mod_zip DSO for nginx-galaxy before that package goes away entirely
set -euo pipefail

nginx_version='1.12.2'
upload_module_version='2.255-nfs'
auth_pam_module_version='1.4'
mod_zip_version='808fb55e7235a201ea862e02dab612b87787d5a4'
gid=$(id -g)
uid=$(id -u)

natefoo

---
# Manage static Galaxy configuration files

- name: Static config setup
  block:

    - name: Ensure Galaxy version is set
      include_tasks: _inc_galaxy_version.yml
      when: __galaxy_major_version is undefined

natefoo

import os
import subprocess
import time
from datetime import (
    date,
    datetime,
)

import click
import psutil

natefoo

#!/usr/bin/env python3
import os
import traceback

import click
from rich import progress
from tusclient.fingerprint import fingerprint

from bioblend import ConnectionError
from bioblend.galaxy import GalaxyInstance

natefoo

#!/usr/bin/env python3
# Quick and dirty script to update usegalaxy-tools with missing tools fron GTN trainings. Note that this installs the
# newest versions of things, not necessarily the version specified in the training json.
import argparse
import os
import pathlib
import string
import subprocess
import sys

natefoo

Manually mulling container images

This is occasionally necessary e.g. when trying to build images for old software or old versions that won't be supported by BioContainers, custom channels, etc.

Another common use case is for when you are trying to run a Galaxy tool that is missing a requirement specification for something it depends on (this is common especially with older tools that assumed Python would be present) or that requires older conda packages that did not fully specify their dependencies.

Prerequisites

You will need Docker on whatever host you plan to run on. Singularity is not required (even if building Singularity images) since the Singularity build occurs in Docker.

natefoo

#!/usr/bin/env python
"""
Finds datasets on disk that shouldn't be there.

This script is not object-store aware. You just point it at directories that are DiskObjectStore backends (e.g.
file_path in the Galaxy config by default).
"""
from __future__ import absolute_import, print_function

import sys

natefoo

run-pulsar-dev.sh

This script was prepared for development work at the Galaxy Community Conference 2021 CoFest. It has been superseded by a Docker Compose-based project at:

https://github.com/natefoo/galaxy-pulsar-dev/

natefoo

#!/usr/bin/env python3
# run with:
#    find topics -name \*.md -type f -print0 | xargs -0 python3 lamefix.py
import fileinput
import sys


def fix(mdfileobj):
    in_diff = False
    min_length = sys.maxsize