hall-of-justice | Working with criminal justice data
kandi X-RAY | hall-of-justice Summary
kandi X-RAY | hall-of-justice Summary
hall-of-justice is a HTML library. hall-of-justice has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
Hall of Justice is a Sunlight Foundation Project working with criminal justice data. Hall of Justice was on Heroku while in development.
Hall of Justice is a Sunlight Foundation Project working with criminal justice data. Hall of Justice was on Heroku while in development.
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hall-of-justice has a low active ecosystem.
It has 14 star(s) with 6 fork(s). There are 9 watchers for this library.
It had no major release in the last 6 months.
There are 21 open issues and 23 have been closed. On average issues are closed in 16 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of hall-of-justice is current.
Quality
hall-of-justice has no bugs reported.
Security
hall-of-justice has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
hall-of-justice is licensed under the BSD-3-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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hall-of-justice releases are not available. You will need to build from source code and install.
Installation instructions are available. Examples and code snippets are not available.
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hall-of-justice Key Features
No Key Features are available at this moment for hall-of-justice.
hall-of-justice Examples and Code Snippets
No Code Snippets are available at this moment for hall-of-justice.
Community Discussions
No Community Discussions are available at this moment for hall-of-justice.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hall-of-justice
You can take a properly formatted (fits the data schema) xlsx file and collapse it to a single csv using scripts/collapse_xls_to_csv.py. This csv can be imported into a Django database (already created using python manage.py migrate) using the import_datasets management command, i.e.: python manage.py import_datasets /path/to/data.csv -v 3 2> import_errors.log. You can look for errors around datasets that failed to import (grep '^Failed to save dataset' import_errors.log | sort) or categories that don't exist (grep category$ import_errors.log | uniq | sort). There are also rows from the csv where there wasn't enough data to create a dataset (Not enough data to create a dataset!), but those are likely mostly empty rows from the input csv. Once you've imported data into the database, you should create (or recreate) the elasticsearch search index using python manage.py rebuild_index.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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