import zipfile
import os

# Unzipping the file
zip_path = "/mnt/data/pages.zip"
unzip_dir = "/mnt/data/pages"

with zipfile.ZipFile(zip_path, 'r') as zip_ref:
    zip_ref.extractall(unzip_dir)

# Checking the files in the unzipped directory
file_list = []
for dirpath, dirs, files in os.walk(unzip_dir):
    for filename in files:
        fname = os.path.join(dirpath, filename)
        file_list.append(fname)

file_list

import re

# Pattern to find a wallet address
pattern = re.compile(r"(useAccount)\((.*?)\)")

# Placeholder for matched lines
matches = []

# Iterate over all .mdx and .ts files
for file in file_list:
    if file.endswith('.mdx') or file.endswith('.ts'):
        with open(file, 'r') as f:
            try:
                # Read each line of the file
                for line in f.readlines():
                    # If pattern is found, append the line to matches
                    if pattern.findall(line):
                        matches.append(line.strip())
            except:
                pass

matches[:10]  # Display first 10 matches


['const { address, isConnected } = useAccount()',
 'const { address, isConnected } = useAccount()',
 'const { isConnected } = useAccount()',
 'const { address } = useAccount()',
 'const { isConnected } = useAccount()',
 'const { isConnected } = useAccount()',
 'const { isConnected } = useAccount()',
 'const { isConnected } = useAccount()',
 'const { address, connector, isConnected } = useAccount()',
 'const { address, isConnected } = useAccount()']

An experimental model that can solve tasks by generating Python code and executing it in a Jupyter notebook.
You can upload any kind of file, and ask model to analyse it, or produce a new file which you can download.

✅ wagmi OK