Splitting a WARC file into chunks based on the header: WARC/1.0 Python

596 views Asked by At

I'm new to programming and am trying to process a WARC file by splitting it into chunks and then storing each chunk in a dictionary.

Each chunk should start with the WARC/1.0 header and is separated by 3 empty lines. I also would like to remove the first 2 paragraphs:

WARC/1.0
WARC-Type: warcinfo
WARC-Date: 2020-08-04T01:43:40Z
WARC-Record-ID: <urn:uuid:959ea654-33fd-466b-b1bf-f08aa8abe774>
Content-Length: 500
Content-Type: application/warc-fields
WARC-Filename: CC-MAIN-20200804014340-20200804044340-00045.warc.gz

isPartOf: CC-MAIN-2020-34
publisher: Common Crawl
description: Wide crawl of the web for August 2020
operator: Common Crawl Admin ([email protected])
hostname: ip-10-67-67-22.ec2.internal
software: Apache Nutch 1.17 (modified, https://github.com/commoncrawl/nutch/)
robots: checked via crawler-commons 1.2-SNAPSHOT (https://github.com/crawler-commons/crawler-commons)
format: WARC File Format 1.1
conformsTo: http://iipc.github.io/warc-specifications/specifications/warc-format/warc-1.1/

#Keep everything from here down:

WARC/1.0
WARC-Type: request
WARC-Date: 2020-08-04T03:25:25Z
WARC-Record-ID: <urn:uuid:6c0b749a-4d02-4a77-ab93-9bc4ba094cdc>
Content-Length: 303
Content-Type: application/http; msgtype=request
WARC-Warcinfo-ID: <urn:uuid:959ea654-33fd-466b-b1bf-f08aa8abe774>
WARC-IP-Address: 104.254.66.40
WARC-Target-URI: http://00.auto.sohu.com/d/details?cityCode=450100&planId=1450&trimId=145372

I've tried using a generator to group the chunks, but it's returning one group (the whole file). Is there a simple way to separate these?

I can't import any libraries.

Any help would be greatly appreciated!!

1

There are 1 answers

0
Greg Lindahl On

By far the best way to do this task is to use the warcio library, which knows how to properly parse warc files into records.

Barring that, I would copy the warcio code into yours (the license is permissive.)

Warc files are complicated, and using a fully tested and widely used library is the right way to parse them.

If you're downloading data from Common Crawl, I would also recommend checking out my python package cdx_toolkit. It uses warcio under the hood, and handles the downloading steps.