Added multiple document support to 26-persistent-tables #49
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Previous implementation ignored argv[1] after initial run, which led to the lack of support for adding and retrieving term frequency for multiple documents.
arthurtham
changed the title
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
The previous implementation ignored argv[1] after the initial run, which led to the lack of support for adding and retrieving term frequency for multiple documents.
Now, after the initial run, the program will successfully check if a document has been processed before. If it has been run, it will retrieve the already-processed words from the database. Otherwise, it will generate new words with a new doc_id.
As a consequence, the "load_file_into_database" should return the doc_id so that after the insertion of the new words, the program can re-use the doc_id to retrieve the top 25 words.
On line 79, the query now takes into account the doc_id instead of ignoring the filename provided after the initial runs.
This pull request only fixes the issue in Python 3.