Update Multiple Column Values

Update several column values at once for better performance and efficiency.

Finding Column IDs

Column IDs are Board-Specific

Before updating column values, you must find your board's actual column IDs. See the Items Create guide for how to query column IDs.

Basic Multiple Update

Update several columns in a single API call:

ruby

require "monday_ruby"
require "json"

Monday.configure do |config|
  config.token = ENV["MONDAY_TOKEN"]
end

client = Monday::Client.new

# ⚠️ Replace all column IDs with your board's actual column IDs
column_values = {
  status: { label: "Working on it" },  # Your status column ID
  text: "High priority task",  # Your text column ID
  numbers: 85  # Your numbers column ID
}

response = client.column.change_multiple_values(
  args: {
    board_id: 1234567890,
    item_id: 987654321,
    column_values: JSON.generate(column_values)
  }
)

if response.success?
  item = response.body.dig("data", "change_multiple_column_values")
  puts "✓ Updated multiple columns for: #{item['name']}"
else
  puts "✗ Failed to update columns"
end

Output:

✓ Updated multiple columns for: Marketing Campaign

Performance Benefit

Updating multiple columns at once is more efficient than making separate API calls for each column. It also ensures atomicity - all updates succeed or fail together.

Update Mixed Column Types

Combine simple and complex column types:

ruby

# ⚠️ Replace all column IDs with your board's actual column IDs
column_values = {
  status: {  # Status column
    label: "Done"
  },
  text: "Completed successfully",  # Text column
  date4: {  # Date column
    date: "2024-12-31",
    time: "17:00:00"
  },
  people: {  # People column
    personsAndTeams: [
      { id: 12345678, kind: "person" }  # Replace with actual user ID
    ]
  },
  numbers: 100,  # Numbers column
  checkbox: {  # Checkbox column
    checked: "true"
  }
}

response = client.column.change_multiple_values(
  args: {
    board_id: 1234567890,
    item_id: 987654321,
    column_values: JSON.generate(column_values)
  }
)

Update Item with Full Details

Set all relevant columns when creating or updating an item:

ruby

def update_task_complete(client, board_id, item_id)
  # ⚠️ Replace all column IDs with your board's actual column IDs
  column_values = {
    status: {
      label: "Done"
    },
    date4: {
      date: Date.today.to_s
    },
    text: "Task completed on time",
    numbers: 100  # 100% complete
  }

  response = client.column.change_multiple_values(
    args: {
      board_id: board_id,
      item_id: item_id,
      column_values: JSON.generate(column_values)
    }
  )

  if response.success?
    item = response.body.dig("data", "change_multiple_column_values")
    puts "✓ Task marked complete: #{item['name']}"
    true
  else
    puts "✗ Failed to update task"
    false
  end
end

# Usage
update_task_complete(client, 1234567890, 987654321)

Bulk Update Multiple Items

Update the same columns for multiple items:

ruby

def bulk_update_items(client, board_id, item_ids, column_values)
  updated_count = 0

  item_ids.each do |item_id|
    response = client.column.change_multiple_values(
      args: {
        board_id: board_id,
        item_id: item_id,
        column_values: JSON.generate(column_values)
      }
    )

    if response.success?
      item = response.body.dig("data", "change_multiple_column_values")
      updated_count += 1
      puts "✓ Updated: #{item['name']}"
    else
      puts "✗ Failed to update item #{item_id}"
    end

    sleep(0.3)  # Rate limiting
  end

  updated_count
end

# Usage: Mark multiple tasks as complete
# ⚠️ Replace column IDs with your actual column IDs
item_ids = [987654321, 987654322, 987654323]
values = {
  status: { label: "Done" },
  date4: { date: Date.today.to_s },
  text: "Batch completed"
}

count = bulk_update_items(client, 1234567890, item_ids, values)
puts "\n✓ Updated #{count} items"

Update with Conditional Logic

Update columns based on current values or conditions:

ruby

def update_if_in_progress(client, board_id, item_id)
  # First, get current item
  query_response = client.item.query(
    args: { ids: [item_id] },
    select: [
      "id",
      "name",
      {
        column_values: ["id", "text"]
      }
    ]
  )

  return false unless query_response.success?

  item = query_response.body.dig("data", "items", 0)
  status = item["column_values"].find { |cv| cv["id"] == "status" }

  # Only update if status is "In Progress"
  return false unless status&.dig("text") == "Working on it"

  # Update to next stage
  # ⚠️ Replace column IDs with your actual column IDs
  column_values = {
    status: { label: "Review" },
    text: "Ready for review",
    date4: { date: Date.today.to_s }
  }

  update_response = client.column.change_multiple_values(
    args: {
      board_id: board_id,
      item_id: item_id,
      column_values: JSON.generate(column_values)
    }
  )

  update_response.success?
end

# Usage
if update_if_in_progress(client, 1234567890, 987654321)
  puts "✓ Task moved to review"
else
  puts "Task not in progress or update failed"
end

Get Updated Column Values

Retrieve updated values after the change:

ruby

response = client.column.change_multiple_values(
  args: {
    board_id: 1234567890,
    item_id: 987654321,
    column_values: JSON.generate({
      status: { label: "Done" },  # ⚠️ Your column IDs
      text: "Completed",
      numbers: 100
    })
  },
  select: [
    "id",
    "name",
    "state",
    {
      column_values: ["id", "text", "type", "value"]
    }
  ]
)

if response.success?
  item = response.body.dig("data", "change_multiple_column_values")

  puts "Updated: #{item['name']}"
  puts "\nColumn Values:"

  item["column_values"].each do |col_val|
    next if col_val["text"].nil? || col_val["text"].empty?
    puts "  • #{col_val['id']}: #{col_val['text']} (#{col_val['type']})"
  end
end

Error Handling

Handle update errors gracefully:

ruby

def update_columns_safe(client, board_id, item_id, column_values)
  response = client.column.change_multiple_values(
    args: {
      board_id: board_id,
      item_id: item_id,
      column_values: JSON.generate(column_values)
    }
  )

  if response.success?
    item = response.body.dig("data", "change_multiple_column_values")
    puts "✓ Updated: #{item['name']}"
    true
  else
    puts "✗ Failed to update columns"
    puts "  Status: #{response.status}"

    if response.body["errors"]
      response.body["errors"].each do |error|
        puts "  Error: #{error['message']}"
      end
    end

    false
  end
rescue Monday::AuthorizationError
  puts "✗ Invalid API token"
  false
rescue Monday::InvalidRequestError => e
  puts "✗ Invalid request: #{e.message}"
  false
rescue Monday::Error => e
  puts "✗ API error: #{e.message}"
  false
end

# Usage
values = {
  status: { label: "Done" },
  text: "Task complete"
}

success = update_columns_safe(client, 1234567890, 987654321, values)

Clear Multiple Columns

Remove values from several columns at once:

ruby

# ⚠️ Replace column IDs with your actual column IDs
column_values = {
  status: {},  # Empty object clears the value
  text: "",  # Empty string for text columns
  date4: {},
  people: {}
}

response = client.column.change_multiple_values(
  args: {
    board_id: 1234567890,
    item_id: 987654321,
    column_values: JSON.generate(column_values)
  }
)

if response.success?
  puts "✓ Multiple columns cleared"
end

Complete Example

Update item with full workflow transition:

ruby

require "monday_ruby"
require "dotenv/load"
require "json"
require "date"

Monday.configure do |config|
  config.token = ENV["MONDAY_TOKEN"]
end

client = Monday::Client.new

def transition_to_qa(client, board_id, item_id, assignee_id)
  # IMPORTANT: Replace all column IDs with your board's actual column IDs

  column_values = {
    status: {  # ⚠️ Your status column ID
      label: "QA Testing"
    },
    people: {  # ⚠️ Your people column ID
      personsAndTeams: [
        { id: assignee_id, kind: "person" }
      ]
    },
    date4: {  # ⚠️ Your date column ID
      date: (Date.today + 3).to_s  # Due in 3 days
    },
    text: "Moved to QA for testing",  # ⚠️ Your text column ID
    numbers: 80  # ⚠️ Your numbers column ID (80% complete)
  }

  response = client.column.change_multiple_values(
    args: {
      board_id: board_id,
      item_id: item_id,
      column_values: JSON.generate(column_values)
    },
    select: [
      "id",
      "name",
      {
        column_values: ["id", "text"]
      }
    ]
  )

  if response.success?
    item = response.body.dig("data", "change_multiple_column_values")

    puts "\n✓ Item Transitioned to QA\n#{'=' * 50}"
    puts "Item: #{item['name']}"
    puts "Updated Values:"

    item["column_values"].each do |col|
      next if col["text"].nil? || col["text"].empty?
      puts "  • #{col['id']}: #{col['text']}"
    end

    puts "#{'=' * 50}"
    true
  else
    puts "✗ Failed to transition item"
    false
  end
end

# Usage
success = transition_to_qa(
  client,
  1234567890,  # board_id
  987654321,   # item_id
  12345678     # assignee_id - replace with actual user ID
)

Output:

✓ Item Transitioned to QA
==================================================
Item: Feature Development
Updated Values:
  • status: QA Testing
  • people: John Doe
  • date4: 2024-12-15
  • text: Moved to QA for testing
  • numbers: 80
==================================================

Best Practices

Do's

✅ Update multiple related columns together
✅ Use JSON.generate for all column values
✅ Include rate limiting delays in loops
✅ Verify column IDs before updating
✅ Handle errors appropriately

Don'ts

❌ Update columns one-by-one when you can batch them
❌ Hardcode column IDs without verification
❌ Skip error handling
❌ Update too many items without rate limiting
❌ Mix up column IDs between boards

Update Multiple Column Values ​

Finding Column IDs ​

Basic Multiple Update ​

Update Mixed Column Types ​

Update Item with Full Details ​

Bulk Update Multiple Items ​

Update with Conditional Logic ​

Get Updated Column Values ​

Error Handling ​

Clear Multiple Columns ​

Complete Example ​

Best Practices ​

Do's ​

Don'ts ​

Next Steps ​

Update Multiple Column Values

Finding Column IDs

Basic Multiple Update

Update Mixed Column Types

Update Item with Full Details

Bulk Update Multiple Items

Update with Conditional Logic

Get Updated Column Values

Error Handling

Clear Multiple Columns

Complete Example

Best Practices

Do's

Don'ts

Next Steps