Demystifying Text Data with the Unstructured Python Library

https://saeedesmaili.com/demystifying-text-data-with-the-unstructured-python-library/

by saeedesmaili • 3 years ago

141 22 3 years ago

dogline• 3 years ago

I hadn't seen the unstructured python library before. Seems handy to parse personal text, like the author is doing.

It would help this article’s quality if the author had included an output example from each code snippet. As a reader I’m left to imagine what the output looks like.

saeedesmaili4• 3 years ago

Author here. That's a good point. I'll add output examples.

agadius• 3 years ago

If you accept running Java, the Apache Tika is extremely good at parsing content (https://tika.apache.org/)

convivialdingo3• 3 years ago

I second this suggestion. I tested numerous Python tools to extract text - nothing matches Tika for general extraction of just about any data format.

However - if you can expect a certain format beforehand - then Python is better since you can extract higher-quality data (tables, lists) with the appropriate tool.

saeedesmaili4• 3 years ago

Do you have any suggestions for Python libraries (other than what's mentioned in the post)?

mcswell3• 3 years ago

Tika can be used as a library in Python: https://pypi.org/project/tika/

ramraj07• 3 years ago

As is customary for all of Apache, I have no clue what I’m looking at after trying to read through the links in that page for ten minutes. Like who is this tool for? When should I use this vs any other competing tools? No clue. I suppose it can read documents of any type and give it out as a dictionary? Why would I use this vs pandas?

mbwgh• 3 years ago

I second this, there is absolutely no easily discoverable entry point to the documentation. In the end if you want to get a feeling of what this is you search for "tika tutorial" and get a rough idea via (in my case) some medium article I guess.

mcswell3• 3 years ago

I can't speak to the Apache documentation, but I once had the task of extracting plain text from many different document formats: Word, spreadsheets, PDFs, the EXIF information in JPEGs, and so on for a long list. I had written code with calls to extractor libraries for several of these formats, when I can across tika. Out when my if..then..elif..elif..elif.. code, to be replaced with a single (Python) call to tika.

I can't answer your question about pandas, though.

jghn• 3 years ago

I found myself today trying to parse a TSV and substituting a few fields with a different value, then writing the new file out.

Something that perl would excel at, although I used Python. Because Perl isn't as maintainable as Python

I was intrigued by this comment. A JVM solution would also be viable in my tech stack. Would Tika be easier than line processing compiled regexes in Python? I tried looking at the Usage examples but it wasn't clear.

CShorten• 3 years ago

Awesome!

oersted• 3 years ago

I have been using it extensively during the last few weeks. I've very thankful for such a clean and practical API, and I think it will become the central solution for ingesting heterogeneous text in the Python ecosystem.

However, I'm afraid it is not there yet. Other libraries like PDFMiner give higher quality outputs and specialized libraries like Camelot are still needed to extract tables as reasonably well formatted text. It also needs a lot of extra tooling for web scraping. Sure it can read plain HTML from a URL, but it cannot run JavaScript, or control things like User Agent. It could be argued that such features are not within the scope, but it is rather bothersome for a library that presents a magic `partition` function for most standard text sources.

I'm sure it will get there soon though. It shouldn't be hard to integrate with state-of-the-art parsers and tooling, and the simple API undoubtedly brings a lot of peace of mind.

froggychairs• 3 years ago

API looks very clean :) I’ve also been avoiding LangChain since it just seems too big for my tastes. Will give this a shot

raphman• 3 years ago

Another way to parse Markdown, HTML, or docx files would be pandoc [1]:

  pandoc --to json file.docx

or in Python:

  import json
  from sh import pandoc
  doc = json.loads(  pandoc("file.docx", to="json").stdout  )

Example output (reformatted slightly to reduce number of lines:

  {'pandoc-api-version': [1, 22, 2],
   'meta': {'title': {'t': 'MetaInlines',
     'c': [{'t': 'Str', 'c': 'The'}, {'t': 'Space'}, {'t': 'Str', 'c': 'Title'}]}},
   'blocks': [{'t': 'Header',
     'c': [1,
      ['first-chapter', [], []],
      [{'t': 'Str', 'c': 'First'}, {'t': 'Space'}, {'t': 'Str', 'c': 'Chapter'}]]},
    {'t': 'Para',
     'c': [{'t': 'Str', 'c': 'I'}, {'t': 'Space'}, {'t': 'Str', 'c': 'like'}, {'t': 'Space'},
      {'t': 'Emph', 'c': [{'t': 'Str', 'c': 'cursive'}]}, {'t': 'Space'}, {'t': 'Str', 'c': 'or'}, 
      {'t': 'Space'}, {'t': 'Strong', 'c': [{'t': 'Str', 'c': 'bold'}]}, {'t': 'Space'},
      {'t': 'Str', 'c': 'text.'}]},
    {'t': 'Para',
     'c': [{'t': 'Str', 'c': 'Here'}, {'t': 'Space'}, {'t': 'Str', 'c': 'is'}, {'t': 'Space'},
      {'t': 'Str', 'c': 'a'}, {'t': 'Space'}, {'t': 'Link',
       'c': [['', [], []], [{'t': 'Str', 'c': 'link'}], ['https://ix.de/', '']]},
      {'t': 'Str', 'c': '.'}]},
    {'t': 'BulletList',
     'c': [[{'t': 'Para', 'c': [{'t': 'Str', 'c': 'Item'}, {'t': 'Space'}, 't': 'Str', 'c': '1'}]}],
      [{'t': 'Para', 'c': [{'t': 'Str', 'c': 'Item'}, {'t': 'Space'}, {'t': 'Str', 'c': '2'}]}]]}]}

[1] https://pandoc.org/

Demystifying Text Data with the Unstructured Python Library

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