aryangupta701 / django-monitoring-restro

Steps to Get Started

1. Clone Repo: git clone https://github.com/aryangupta701/django-monitoring-restro/

2. Switch to Project Directory: cd django-monitoring-restro

3. Activate Environment: source ../bin/activate

Pre-requisites

In the data folder add -

• Menuhours.csv

• storestatus.csv

• timezones.csv

Enable Environment by using the following command -

source ./bin/activate

Load data

python manage.py makemigrations

python manage.py migrate

python manage.py load_data

Runserver

python manage.py runserver

Trigger Report Generation

METHOD - POST

http://127.0.0.1:8000/trigger_report/

Get Report

METHOD - GET

http://127.0.0.1:8000/get_report/<report-id>

Logic for computing the hours overlap and uptime/downtime

1. Every time is converted into UTC before use

2. To get all the unique store_id the database table store_status is used

To Calculate uptime/downtime for each store_id the following logic is being used :

1. An interpolation curve is being formed with points defined as timestamps (in seconds) of the poll of previous 10 days using scipy using the following code

interp_func = interp1d(timestamps, states, kind='nearest', fill_value='extrapolate')

• On X-axis - Timestamp ( timestamps )

• On Y-axis - Either 0 (for inactive) or 1 (for active) is stored ( states )

2. Now to calculate last-hour uptime used the following logic :

• Iterated over each second in the last hour and checked if the timestamp of the second is within the range of working hours of that day or not.

• If it is in the range then append it to the interpolated_timestamps array

• Now pass this array to the interpolation object and it will return the predicted values of each timestamp in interpolated_states which consists of either 0 or 1.

• Now uptime can be calculated by adding the whole interpolated_states array

• To calculate the downtime we can be calculated by subtracting the uptime from the total length of interpolated_timestamps

3. The same logic is used for the calculation of last day and last week.

4. At the uptime and downtime which were calculated in seconds and converted into the required format (hours or minutes )