Finance Manager

Built using Python, Flask, SQLLite, Pandas

Quick start

All dependencies can be installed using the following command

$ pip install -r requirements.txt

To run the Application please use the following command

$ python app.py

Input Data format

The raw_data that we used for this has been imported from Mint financial software

If you do not have an account with Mint, you can format all your expenses as a csv below and save it as transactions.csv under raw_data folder

Date	Description	Original Description	Amount	Transaction Type	Category	Account Name	Labels	Notes
2019-04-02	ABC	ABC*DEF	$12	Debit	Gym	Discover	Null	Null

API's Exposed

List all expenses

Definition

GET /expenses

Response

• 200 OK on success

[
    {
        "Description": "Abc Westca",
        "Original_Description": "ABC*WESTCA",
        "Amount": 49,
        "Category": "Gym",
        "Account_Name": "Cash rewards credit card ",
        "Date": "2019-01-24 00:00:00"
    },
    {
        "Description": "Uber.com",
        "Original_Description": "UBR* PENDING.UBER.COM",
        "Amount": 6.65,
        "Category": "Rental Car & Taxi",
        "Account_Name": "Cash rewards credit card ",
        "Date": "2019-01-24 00:00:00"
	}
]

List expenses grouped by category

Definition

GET /expenses/category

Response

• 200 OK on success

[
    {
        "Category": "XYZ",
        "Total_Amount": 2
    },
    {
        "Category": "ABC",
        "Total_Amount": 220
	}
]

List expenses grouped by category within last N days

Definition

GET /expenses/category/<int:num_days>

Response

• 200 OK on success

[
    {
        "Category": "XYZ",
        "Total_Amount": 2
    },
    {
        "Category": "ABC",
        "Total_Amount": 220
	}
]