Botty Boy Bot

Inspiration

We were inspired by

What it does

Our project matches you with users of the same interests to talk to. Using sentiment analysis from Lexalytics we can match users together more accurately based on how much they like or dislike a specific topic.

How we built it

Using Python, the Python-Telegram-Bot Library and the Semantria API from Lexalytics.

Challenges we ran into

One of the challenges we ran into was that JSON parsing and adding data to an empty table was difficult without the key already existing.

Another challenge we had is that using the Semantic API, our first set of keys didn't work, and the API didn't send a response giving an error or why we weren't receiving data.

Accomplishments that we're proud of

We're proud of learning to use new APIs that we haven't touched before, and integrating them into our project.

What we learned

We learned to use new Libraries and API's

What's next for Botty Boy Bot

We would like if we can get it to a point where it is stable. Possibly adding a database backend instead of JSON, and overall just making the bot smarter.

Built With

• json
• python
• semantria
• telegram