Matthew Feickert matthewfeickert

This got long, so TLDR: Micky's reactions are what I would call "correct". If people want reproducible environments that's great, but pip freeze is not going to get you there.

The answer is (like most things in life) it depends. What are you trying to do? I tend to split along this line into two idea groups: "libraries" and "applications".

At this point I'd suggest that you read the following to make sure that we're on the same page about these words.

setup.py vs requirements.txt by Donald Stufft (https://caremad.io/posts/2013/07/setup-vs-requirement/)
Pipfile vs setup.py section of the pipenv docs (https://pipenv-fork.readthedocs.io/en/latest/advanced.html#pipfile-vs-setup-py)

Hopefully you read them, but the TLDR on those is:

Libraries are supposed to work in an ecosystem of things and so should strive to only require the minimum restrictions on dependencies that will still gaurentee a stable API. Here you probably just want to have the core dependencies be specified with minimum version numbers or

Example of Python classes and the use of `self`

Click this button to run an example in Binder:

As you can see from requirements.txt I've added some fun Python libraries, that are available in the Binder instance so you can use them in this sandbox environment.

`MG5aMC_PythonMEs` Minimal Working Example

Kyle notified people over email and Twitter that Valentin Hirschi had gotten MadGraph to export matrix element codes for Feynman diagrams into a form that can be used by differentiable machine learning libraries (e.g., TensorFlow and PyTorch). The project is called MG5aMC_PythonMEs. This is a short walkthrough of doing the simplest possible thing: just running the code that MG5aMC_PythonMEs generates. As I don't have much experience with MadGraph5_aMC@NLO and its installation and use instructions are quite bad I threw together a Docker image that at leasts somewhat works. This walkthrough will use that.

To be clear, this is never how you would actually do anything with a Docker image. This is just throwing things against the wall at the moment.

Testing Python Docstrings with `doctest` and `pydocstyle`

Setup

Like any good project, we'll create a virtual environment for this example. You can use your virtual environment tool of choice, but I'm just going to show with Python's venv (and some help from venv-activate)

cd
mkdir venvs
cd venvs

	cmake_minimum_required (VERSION 3.14 FATAL_ERROR)
	set(CMAKE_CXX_STANDARD 14)
	project(testing_frugal)

	include(FetchContent)

	FetchContent_Declare(
	nlohmann_json
	GIT_REPOSITORY https://github.com/nlohmann/json.git
	GIT_TAG v3.8.0

	import numpy as np
	import pyhf

	stopRHadron_spec = {
	'channels': [
	{
	'name': 'channel1',
	'samples': [
	{
	'data': [1.364790054231882],

	*.pdf
	HistFactory/
	validation.txt
	.xml2json_output
	roundtrip.json

	# derived from Table 4 (page 58) of http://arxiv.org/pdf/1312.5353v3

	imax 3 number of bins
	jmax 2 number of samples minus one
	kmax * number of nuisance parameters
	--------------------------------------------------------
	bin bin4e bin2e2m bin4m
	observation 4 13 8
	--------------------------------------------------------
	bin bin4e bin2e2m bin4m bin4e bin2e2m bin4m bin4e bin2e2m bin4m

	FROM python:3.8

	MAINTAINER Matthew Feickert <[email protected]>

	USER root
	WORKDIR /root

	SHELL [ "/bin/bash", "-c" ]

	RUN apt-get -qq -y update && \

	*.asetup.save
	build/
	submitDir/

Matthew Feickert matthewfeickert

Example of Python classes and the use of self

MG5aMC_PythonMEs Minimal Working Example

Testing Python Docstrings with doctest and pydocstyle

Setup

Example of Python classes and the use of `self`

`MG5aMC_PythonMEs` Minimal Working Example

Testing Python Docstrings with `doctest` and `pydocstyle`