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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

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Backend system for restaurant management

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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