https://github.com/shikha-code36/restaurant-monitoring-system
Backend system for restaurant management
https://github.com/shikha-code36/restaurant-monitoring-system
backend backend-api cache cache-storage caching flask flask-api flask-backend flask-restful flask-sqlalchemy multithreading multithreading-library pandas pandas-dataframe pandas-python python python3 sqlalchemy-database-migrations sqlalchemy-python
Last synced: 7 months ago
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Backend system for restaurant management
- Host: GitHub
- URL: https://github.com/shikha-code36/restaurant-monitoring-system
- Owner: Shikha-code36
- License: mit
- Created: 2023-02-24T14:47:05.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-02-24T14:57:02.000Z (over 2 years ago)
- Last Synced: 2025-03-24T03:53:05.807Z (7 months ago)
- Topics: backend, backend-api, cache, cache-storage, caching, flask, flask-api, flask-backend, flask-restful, flask-sqlalchemy, multithreading, multithreading-library, pandas, pandas-dataframe, pandas-python, python, python3, sqlalchemy-database-migrations, sqlalchemy-python
- Language: Python
- Homepage:
- Size: 18.6 KB
- Stars: 6
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Restaurant Monitoring System
The Restaurant Monitoring System is a backend API that helps restaurant
owners track the online and offline status of their stores during
business hours. The system polls each store roughly every hour and
records whether the store was active or not in a CSV file. The system
also has data on the business hours of all the stores and the timezone
for each store.
The system provides two APIs:
1. /trigger_report endpoint that triggers the generation of a report
from the data provided (stored in the database). The API has no
input and returns a report ID (a random string). The report ID is
used to poll the status of report completion.
2. /get_report endpoint that returns the status of the report or the
CSV. The API takes a report ID as input and returns the following:
- If report generation is not complete, return "Running" as the
output
- If report generation is complete, return "Complete" along with
the CSV file with the following schema: store_id,
uptime_last_hour(in minutes), uptime_last_day(in hours),
update_last_week(in hours), downtime_last_hour(in minutes),
downtime_last_day(in hours), downtime_last_week(in hours) The
uptime and downtime reported in the CSV only include
observations within business hours. The system extrapolates
uptime and downtime based on the periodic polls we have ingested
to the entire time interval.
## Data Sources
The system has the following three sources of data:
1. A CSV file with three columns (store_id, timestamp_utc, status)
where status is active or inactive. All timestamps are in UTC.
2. A CSV file with data on the business hours of all the stores. The
schema of this data is store_id, dayOfWeek(0=Monday, 6=Sunday),
start_time_local, end_time_local. These times are in the local time
zone. If data is missing for a store, assume it is open 24\*7.
3. A CSV file with data on the timezone for each store. The schema is
store_id, timezone_str. If data is missing for a store, assume it is
America/Chicago. This is used so that data sources 1 and 2 can be
compared against each other.
**_NOTE:_** Data files cannot be pushed due to lfs issue
#### Files structure
```
data/
├── business_hours.csv
├── stores.csv
└── timezones.csv
```
## System Requirements
* The data sources are not static, and the system
should not precompute the answers. The system should keep updating the
data every hour.
* The system should store the CSVs into a relevant
database and make API calls to get the data.
## Installation
To install the required packages, run the following command in the project directory:
```
pip install -r requirements.txt
```
## Usage
To start the server, run the following command in the project directory:
```
python run.py
```
The server will start running on http://localhost:5000
Note: Remember to add url prefix in the api like http://localhost:5000/api
## API Documentation
- ### /trigger_report
This endpoint triggers the generation of a report from the data provided (stored in the database).
* Request
```
POST /api/trigger_report HTTP/1.1
```
* Response
```
HTTP/1.1 200 OK
Content-Type: application/json
{
'message': 'Success',
'error_code':200,
"report_id": "random_string"
}
```
- ### /get_report
This endpoint returns the status of the report or the CSV.
* Request
```
GET /api/get_report?report_id=random_string HTTP/1.1
```
* Response
```
HTTP/1.1 200 OK
Content-Type: text/csv
store_id, uptime_last_hour(in minutes), uptime_last_day(in hours), update_last_week(in hours), downtime_last_hour(in minutes), downtime_last_day(in hours), downtime_last_week(in hours)
1, 60,
```
## Functionalities
Used advance python features like -
- Multithreading
- Caching