SpaCy model won't load in AWS Lambda

Knew it was probably going to be something simple. The answer is that there wasn't enough allocated memory to run the Lambda function - I found that I had to minimally increase it to near the max 2816 MB to get the example above to work. It is notable that before last month it wasn't possible to go this high:

https://aws.amazon.com/about-aws/whats-new/2017/11/aws-lambda-doubles-maximum-memory-capacity-for-lambda-functions/

I turned it up to the max of 3008 MB to handle more text and everything seems to work just fine now.

To optimize model load you have to store it on S3, and download it using your own script to tmp folder in lambda and then load it into spacy from it.

It will take 5 seconds to download it from S3 and run. The good optimization here is to keep model on warm container and check if it was already downloaded. On warm container code takes 0.8 seconds to run.

Here is the link to the code and package with example: https://github.com/ryfeus/lambda-packs/blob/master/Spacy/source2.7/index.py

import spacy
import boto3
import os


def download_dir(client, resource, dist, local='/tmp', bucket='s3bucket'):
    paginator = client.get_paginator('list_objects')
    for result in paginator.paginate(Bucket=bucket, Delimiter='/', Prefix=dist):
        if result.get('CommonPrefixes') is not None:
            for subdir in result.get('CommonPrefixes'):
                download_dir(client, resource, subdir.get('Prefix'), local, bucket)
        if result.get('Contents') is not None:
            for file in result.get('Contents'):
                if not os.path.exists(os.path.dirname(local + os.sep + file.get('Key'))):
                     os.makedirs(os.path.dirname(local + os.sep + file.get('Key')))
                resource.meta.client.download_file(bucket, file.get('Key'), local + os.sep + file.get('Key'))

def handler(event, context):
    client = boto3.client('s3')
    resource = boto3.resource('s3')
    if (os.path.isdir("/tmp/en_core_web_sm")==False):
        download_dir(client, resource, 'en_core_web_sm', '/tmp','ryfeus-spacy')
    spacy.util.set_data_path('/tmp')
    nlp = spacy.load('/tmp/en_core_web_sm/en_core_web_sm-2.0.0')
    doc = nlp(u'Apple is looking at buying U.K. startup for $1 billion')
    for token in doc:
        print(token.text, token.pos_, token.dep_)
    return 'finished'

P.S. To package spacy within AWS Lambda you have to strip shared libraries.