Importing CSV & Excel Files in Soli

Soli makes working with spreadsheet data straightforward. Whether you're importing user data from a CSV export, processing Excel reports, or building a data pipeline, the built-in spreadsheet functions have you covered.

Parsing CSV Data

CSV (Comma-Separated Values) is the most common format for data exchange. Soli provides two functions: one for parsing CSV strings and another for reading files directly.

Parsing a CSV String

When your CSV data comes from an API response or a text field:

csv_data = "name,email,role\nAlice,[email protected],admin\nBob,[email protected],user"
users = csv_parse(csv_data)

print(users[0]["name"])  # "Alice"
print(users[1]["role"])  # "user"

The csv_parse() function returns an array of hashes, using the first row as keys.

Reading CSV Files

When your data is in a file, use csv_parse_file():

# Import users from a CSV export
users = csv_parse_file("exports/users.csv")

for user in users
  u = User.create({
    "name": user["name"],
    "email": user["email"],
    "role": user["role"]
  })
  print("Created: " + u.email)
end

Processing Excel Files

The excel_parse() function reads .xlsx files directly, making it easy to process Excel reports:

# Read a sales report
sales = excel_parse("reports/monthly_sales.xlsx")

for row in sales
  print(row["Product"] + ": $" + str(row["Revenue"]))
end

Real-World Example: User Import with Validation

Here's a complete example that imports users from a CSV file, validates the data, and creates user records:

def import_users_from_csv(filepath)
  users = csv_parse_file(filepath)
  imported = 0
  errors = []

  for row in users
    # Validate required fields
    if !row["email"] || !row["name"]
      errors.push("Row missing required field: " + str(row))
      next
    end

    # Check for existing user
    if User.find_by("email", row["email"])
      print("Skipping existing user: " + row["email"])
      next
    end

    # Create the user
    user = User.create({
      "name": row["name"],
      "email": row["email"],
      "role": row["role"] || "user"
    })

    imported = imported + 1
  end

  return {
    "imported": imported,
    "errors": errors
  }
end

# Usage
result = import_users_from_csv("data/new_users.csv")
print("Imported " + str(result["imported"]) + " users")

Real-World Example: Sales Report Processing

Process monthly Excel reports to generate summaries:

def process_sales_report(filepath)
  data = excel_parse(filepath)
  total_revenue = 0
  by_category = {}

  for row in data
    revenue = float(row["Revenue"])
    category = row["Category"]

    total_revenue = total_revenue + revenue

    if !by_category.has_key(category)
      by_category[category] = 0
    end
    by_category[category] = by_category[category] + revenue
  end

  print("Total Revenue: $" + str(total_revenue))
  print("\nBy Category:")
  for category, total in by_category
    print("  " + category + ": $" + str(total))
  end
end

process_sales_report("reports/q4_sales.xlsx")

Real-World Example: Data Migration

Migrate data from a legacy system exported as CSV to your Soli app:

def migrate_products_from_legacy(csv_path)
  products = csv_parse_file(csv_path)
  migrated = 0

  for row in products
    # Skip if product already exists by SKU
    if Product.find_by("sku", row["sku"])
      next
    end

    product = Product.create({
      "sku": row["sku"],
      "name": row["product_name"],
      "price": float(row["price"]),
      "stock": int(row["quantity"]),
      "category": row["category"]
    })

    migrated = migrated + 1
  end

  print("Migrated " + str(migrated) + " products")
end

Summary

These functions make it trivial to integrate spreadsheet data into your Soli applications. Whether you're building import tools, processing reports, or migrating data, the syntax stays simple and the code stays readable.