@ -15,6 +15,7 @@ Returns calculation offloads bulk of the calculation to SQL since this removes t
The resulting array is then sliced in Numpy array to perform the final XIRR calculation. The XIRR function also utilizes numpy array to vectorize calculations and perform it at blazingly fast speeds. All this combined means that SIP returns calculation for 1-3-5-7-10 years takes an average of 50 milliseconds for any fund.
## Usage and deployment
### How to use
To get started, visit [@india_mf_bot](https://t.me/india_mf_bot) on Telegram. Type @india_mf_bot and start typing the fund name to search for a fund. It's an inline search, so do not send the message. Just select a fund from the list that shows up. The basic info for the selected fund will show up. It will also have two buttons for returns and SIP returns. These will be shown inside the original message itself.
@ -23,7 +24,7 @@ To get started, visit [@india_mf_bot](https://t.me/india_mf_bot) on Telegram. Ty
### How to deploy
The bot can either be deployed as it is, or can be containerized. To bot relies on a PostgreSQL Database which has a list of funds, their categories and sub-categories, their entire NAV history, etc.
To run the bot:
**To run the bot**:
1. Clone this repository
2. Rename .env.sample to .env
3. Get a token from the BotFather channel on Telegram. This will need to be copied to the env file.
@ -32,7 +33,7 @@ To run the bot:
6. Install all the dependencies from requirements.txt
7. Run the mf_bot.py script
To run the bot in a container
**To run the bot in a container**:
1. Carry out steps 1-4 in the previous list
2. run the build command `docker build -t word-bot .`
3. run the container using `docker run -d --env-file ./.env --add-host=host:<host-ip> --name mf-bot mf-bot`
