Mohidul Islam
65c48ff334
Show graph for location user
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| review | %!s(int64=4) %!d(string=hai) anos | |
| review_automation | %!s(int64=4) %!d(string=hai) anos | |
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| review_automation.sql | %!s(int64=4) %!d(string=hai) anos | |
| review_data_set.csv | %!s(int64=5) %!d(string=hai) anos | |
| signature_care_review_url.json | %!s(int64=5) %!d(string=hai) anos |
README.md
Byte Trek Reputation Management
Installation:
1. Clone The reporsitory
➜ git clone http://bytetrek.com:30000/ByteTrek-Projects/review-automation-backend.git
2. Create a virtual environment and active it.
➜ python3 -m venv env
➜ source env/bin/activate
3. Create a mysql database and import the .sql file
(env) ➜ mysql -u root -h localhost -p # mysql -u user -h host -p
mysql> CREATE DATABASE review_automation;
mysql> SHOW DATABASES; # Make sure database is created or not.
exit # Exit out of the mysql prompt
(env) ➜ mysql -u root -p review_automation < review_automation.sql
# Make sure everything is just fine.
(env) ➜ mysql -u root -h localhost -p
mysql> USE review_automation;
mysql> SHOW TABLES;
4. Run the development server
(env) ➜ python manage.py runserver --settings=review_automation.settings.dev
5. Add all corn jobs
(env) ➜ python manage.py crontab add --settings=review_automation.settings.dev
# Make sure corn job has added successfully
(env) ➜ crontab -l # Return list of cronjobs
6. Some usefull management command
Store all un-recorded reviews to the database.
(env) ➜ python manage.py collect_reviews --settings=review_automation.settings.devGet model prediction report.
(env) ➜ python manage.py model_report n_days # Example for last 30 days: (env) ➜ python manage.py model_report 30 --settings=review_automation.settings.dev