This repositiory should serve as a base for all the needed stuff for our database project of the database course at university Basel.
Our findings and information about the whole process can be found in our report here:
python -m pip install mysql-connector
-
"locally" running mysql instance
-
with a configured schema with the name
db_multiprocess
and following access parametersport = 3306 username = root password = db_project2019
(configured in the
database.py file
) -
-
Data source files are not included in the reporsitory, for more check out Data Files
Those need to be placed in the
data
folder ( Careful naming of the source files can change but needs to match our names so the integration process to run correctly)
The data can be integrated by running the .py
-files in following order:
- serializer.py
- splitter.py
- filter.py
- inserter.py
- report_inserter.py
- crime_serializer_filter.py
- crime_address.py
- yelp_filter.py
- yelp_address.py
- yelp_business.py
- yelp_review.py
- yelp_is_located.py
- yelp_add_info_business.py
Attention: Running the whole setup process in one go, can take a extremely long time depending on your setup
Our analysis results can be viewed here:
http://db-project-group-4.lengweiler.com
or by running the webapplication locally by moving into the web folder:
cd web
and then executing:
npm install
npm run serve
- https://www.phoenixopendata.com/dataset/crime-data
- https://www.kaggle.com/yelp-dataset/yelp-dataset/download
- https://www.kaggle.com/paultimothymooney/pain-pills-in-the-usa
- https://www.washingtonpost.com/graphics/2019/investigations/dea-pain-pill-database/
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MySQL - SQL dialect
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Python - Python 3.8
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MySQL Connector - Python Mysql connector
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VueJs - Progressive JavaScript Framework
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Tailwind - CSS Framework