Streamlit based web interface app to find and pay fintech talent.
Web-fin-finder is an application which allows the user to import Ethereum transaction functions, and sign, execute and inspect transactions.
See installation and usage below for specifics.
Web-fin-finder will use python, and highlight the Streamlit web interface library, web3.py library, and Ganache.
The main web functionality is implemented within Web-fin-finder and the crypto functionality is imported from crypto_wallet.
High-level steps:
- Import Ethereum Transaction functions from crypto_wallet into the application
- Sign and execute a Payment Transaction
- Inspect the transaction in Ganache
Submission:
- Importing, signing, executing transactions in fintech_finder.py
- Screenshots from Ganache showing address, balance history for both sender and receiver.
This challenge uses python 3.7 and the following modules:
It also uses Ganache to manage the local blockchain and accounts.
See installation and usage below for specifics.
You will need Python 3.7, that supports for this application to run. An easy way to install python 3.7 is to download and install Anaconda. After installing anaconda, open a terminal/command-prompt, and setup a python 3.7 environment, and then activate it like so:
# create an anaconda python 3.7 environment
# name can be any friendly name to refer to your environment, eg 'dev'
conda create --name dev python=3.7 anaconda
# activating the environment
conda activate dev
# use pip to install the above modules, eg:
pip install dateutil
...etc...
MNEMONIC ENV VAR
You must populate SAMPLE.env with your mnemonic words from Ganach application, and then rename the file to .env
in order for the application to connect to your running Ganache instance and generate an account.
Ganache
Docs and download Ganache from Ganache
To run the application, first launch Ganache, ensure your mnemonic words are in the .env
file, then, use the CLI and launch streamlit like:
# activating the environment
conda activate dev
# change to application directory
cd <repo_root>/app
# launch streamlit application
streamlit run fintech_finder.py
MIT