PDF to JSON Bank Statements

fetch('https://api.example.com/convert', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/pdf'
  },
  body: pdfFile
})
.then(res => res.json())
.then(data => console.log(data));

{
  "url": "https://api.example.com/convert",
  "callbackUrl": "https://yourapp.com/webhook",
  "pdfUrl": "https://yourapp.com/statement.pdf"
}

{
  "batch": [
    {"id": "1", "pdfUrl": "statement1.pdf"},
    {"id": "2", "pdfUrl": "statement2.pdf"}
  ],
  "callbackUrl": "https://yourapp.com/batch-complete"
}

const fs = require('fs');

// Load JSON bank statement
const statement = JSON.parse(fs.readFileSync('statement.json'));

// Calculate total income
const totalIncome = statement.transactions
  .filter(t => t.type === 'credit')
  .reduce((sum, t) => sum + t.amount, 0);

// Calculate total expenses
const totalExpenses = statement.transactions
  .filter(t => t.type === 'debit')
  .reduce((sum, t) => sum + Math.abs(t.amount), 0);

// Group by category
const byCategory = statement.transactions.reduce((acc, t) => {
  acc[t.category] = (acc[t.category] || 0) + Math.abs(t.amount);
  return acc;
}, {});

console.log('Income:', totalIncome);
console.log('Expenses:', totalExpenses);
console.log('By Category:', byCategory);

import json
import pandas as pd

# Load JSON statement
with open('statement.json') as f:
    statement = json.load(f)

# Convert transactions to DataFrame
df = pd.DataFrame(statement['transactions'])

# Convert date to datetime
df['date'] = pd.to_datetime(df['date'])

# Add month column
df['month'] = df['date'].dt.to_period('M')

# Monthly summary
monthly_summary = df.groupby('month')['amount'].agg([
    ('total', 'sum'),
    ('count', 'count'),
    ('avg', 'mean')
])

print(monthly_summary)

require 'json'

# Load JSON statement
statement = JSON.parse(File.read('statement.json'))

# Filter transactions by amount
large_transactions = statement['transactions'].select { |t|
  t['amount'].abs > 1000
}

# Group by type
by_type = statement['transactions'].group_by { |t| t['type'] }

# Calculate net change
net_change = statement['balances']['closingBalance'] -
             statement['balances']['openingBalance']

puts "Large transactions: #{large_transactions.count}"
puts "Net change: $#{net_change}"

-- Create table for transactions
CREATE TABLE transactions (
    id VARCHAR(50) PRIMARY KEY,
    date DATE,
    description TEXT,
    amount DECIMAL(10,2),
    type VARCHAR(10),
    balance DECIMAL(10,2),
    category VARCHAR(50)
);

-- Import from JSON (using jsonb column)
INSERT INTO transactions
SELECT
    t->>'id',
    (t->>'date')::DATE,
    t->>'description',
    (t->>'amount')::DECIMAL,
    t->>'type',
    (t->>'balance')::DECIMAL,
    t->>'category'
FROM jsonb_array_elements(
    (SELECT jsonb_build_object('transactions', content)
     FROM statement_json)
    -> 'transactions'
) t;