connecting_flights

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connecting_flights

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Application to find shortest distance or duration or (fake price) of connecting flights through Floyd-Warshall algorithm.

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# Connecting Flights

Application to find lowest price, shortest distance, or duration of connecting flights through [Floyd-Warshall algorithm](http://www-math.mit.edu/~rothvoss/18.304.1PM/Presentations/1-Chandler-18.304lecture1.pdf). 
Presentation slides of the project can be found [here](https://docs.google.com/presentation/d/1rhBlG6i2Wh3xkYLhf-2lLqaB5DSqNwVw8vrsuk5ShGk/edit?usp=sharing).

![alt text](https://raw.githubusercontent.com/NuttySalmon/connecting_flights/master/screenshot.jpg "screenshot")

## Dependencies
Python version 3.7 is used.

Modules:

*  pymongo (3.8.0 or higher)
*  flask (0.14.2 or higher)
*  flask-wtf (0.14.2 or higher)
*  wtforms
*  pytest

__Install with pip:__ In project directory run `pip install -r requirements.txt`

__Install with pipenv:__ In project directory run `pipenv install`

## Running the program
Before running, make sure you have a __MongoDB v4 running__ on `localhost:27017` and all the dependencies installed.

__To run console interface:__
In project directory, run 
```
python start.py 
```
__To run web interface:__
In project directory, run 
```   
python run_webapp.py
```
and go to `localhost:5000` on your browser to access the web interface.

_Note:_ no data will be shown in query before data are added or imported using the console interface.

## Importing CSV
Sample data ***import_ready.csv*** can be found in the *resources* directory. It can be imported through the "Use CSV" option in the program's console interface by putting "./resources/import_ready.csv" as path to file when importing.

__About _import_ready.csv___: It is generated by scaling down the file *raw_data.csv*, which is the raw 2019 Jan data downloaded from [US Bureau of Transportation](https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236). The script `scale_down_csv.py` we created was used to generate the file. *raw_data.csv* is not recommended to be imported since the data size is too big and with no price information avaliable.

Sample quaries to try to get more than one flight in shortest-path:

*  SEA to ATL, price
*  SFO to MIA, price
*  SFO to ATL, distance, price

### More sample data
[US Bureau of Transportation Statistics's Reporting Carrier On-Time Performance data](https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236) can be downloaded as CSV to be used with the program. Check the fields `Reporting_Airline`, `Flight_Number_Reporting_Airline`, `Origin`, `Dest`, `CRSElapsedTime`, and `Distance` when downloading CSV. __The downloaded CSV is NOT ideally ready to be imported__ and manipulation to the data is required.

__To make the raw data ready for import__, run `python ./shortest/scale_down_csv.py` to scale down the raw data and to add random price information. You can also do it manually by deleteing rows of data and populating a new `price` column in the CSV.

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