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astropy-sep-lambda

Build the astropy, sep, numpy, and scipy packages and strip them down to run in Lambda

This repo contains a build.sh script that's intended to be run in an Amazon Linux docker container, and build astropy, sep, numpy, and scipy for use in AWS Lambda. For more info about how the script works, and how to use it, see the blog post by ryansb on deploying sklearn to Lambda.

This repository is a fork of the excellent work by ryanb in https://github.com/ryansb/sklearn-build-lambda.

It has been updated to use Python 3.6 and a newer version of the Amazon Linux image.

To build the zipfile, pull the Amazon Linux image and run the build script in it.

$ docker pull amazonlinux:2018.03
$ docker run -v $(pwd):/outputs -it amazonlinux:2018.03 /bin/bash /outputs/build.sh

That will make a file called venv.zip in the local directory that's around 50MB.

Once you run this, you'll have a zipfile containing astropy, sep, numpy, scipy and their dependencies. This repository also contains a file called process.py which imports these packages and detects sources with SEP package (based on Source Extractor).

import logging
import os
libdir = os.path.join(os.getcwd(), 'lib')
import shutil
import warnings

from astropy.convolution import kernels
from astropy.stats import gaussian_sigma_to_fwhm
import astropy.io.fits as fits
from astropy.table import Table
from astropy import units as u
from astropy import wcs
from astropy.utils.data import CacheMissingWarning
warnings.simplefilter('ignore', CacheMissingWarning)
import boto3
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import numpy as np
import sep


GAUSS_3_7x7 = np.array(
[[ 0.004963,  0.021388,  0.051328,  0.068707,  0.051328,  0.021388,  0.004963],
 [ 0.021388,  0.092163,  0.221178,  0.296069,  0.221178,  0.092163,  0.021388],
 [ 0.051328,  0.221178,  0.530797,  0.710525,  0.530797,  0.221178,  0.051328],
 [ 0.068707,  0.296069,  0.710525,  0.951108,  0.710525,  0.296069,  0.068707],
 [ 0.051328,  0.221178,  0.530797,  0.710525,  0.530797,  0.221178,  0.051328],
 [ 0.021388,  0.092163,  0.221178,  0.296069,  0.221178,  0.092163,  0.021388],
[ 0.004963, 0.021388, 0.051328, 0.068707, 0.051328, 0.021388, 0.004963]])


logging.basicConfig(format='%(levelname)-4s '
                           '[%(module)s.%(funcName)s:%(lineno)d]'
                           ' %(message)s',
                    )
LOG = logging.getLogger('process')


def detect_with_sep(
        event,
        detect_thresh=2.,
        npixels=8,
        grow_seg=5,
        gauss_fwhm=2.,
        gsize=3,
        im_wcs=None,
):

...
...
...

Extra Packages

To add extra packages to the build, add them to the requirements.txt file alongside the build.sh in this repo. All packages listed there will be installed in addition to those already described in build.sh

Testing locally

Testing Lambda locally is a pain, but thanks to the efforts of the Lambci folks in https://github.com/lambci/docker-lambda, we can test a function locally as follows:

First, build the Lambda function locally with the command from above:

$ docker run -v $(pwd):/outputs -it amazonlinux:2018.03 /bin/bash /outputs/build.sh

This should leave you with a venv.zip file. Unzip this with:

$ unzip venv.zip -d venv

Next enter the venv directory and try running the command, passing in your AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY as environment variables:

$ cd venv
$ docker run --rm -e AWS_ACCESS_KEY_ID='XXXXXXXXX' -e AWS_SECRET_ACCESS_KEY='XXXXXXXXX' -v "$PWD":/var/task lambci/lambda:python2.7 process.handler '{"s3_output_bucket": "dsmo-lambda-test-outputs", "fits_s3_key":"hst/public/icsc/icsca0voq/icsca0voq_drz.fits", "fits_s3_bucket":"stpubdata"}'

Sizing and Future Work

In its current form, this set of packages weighs in at 50MB and could probably be reduced further by:

  1. Pre-compiling all .pyc files and deleting their source
  2. Removing test files
  3. Removing documentation

According to this article the size limit for a zipped Lambda package (the venv.zip file) is 50MB, however, reading around it seems like Lambda is tolerant of significantly larger packages when the zipped package is posted to S3.

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