Data Processors

Processors transform extracted values (strip whitespace, cast types, apply regex, etc.). They run sequentially in the order specified.

Available Processors

strip

Remove leading and trailing whitespace

replace

Replace substring in strings

regex

Extract substring using pattern

cast

Convert to specified type

join

Join list values to string

default

Return fallback value if empty

lowercase

Convert strings to lowercase

parse_datetime

Parse datetime to ISO format

Processor Reference

1. strip

Remove leading and trailing whitespace from strings. Parameters: None Example:

{
  "css": "h1::text",
  "processors": [{"type": "strip"}]
}

Transformation:

"  Hello World  " → "Hello World"

Works on: Strings and lists of strings

2. replace

Replace substring in strings. Parameters:

old (required): Substring to replace
new (required): Replacement string

Example:

{
  "css": "span.price::text",
  "processors": [
    {"type": "replace", "old": "$", "new": ""},
    {"type": "replace", "old": ",", "new": ""}
  ]
}

Transformation:

"$1,299.99" → "1299.99"

Works on: Strings and lists of strings

3. regex

Extract substring using regular expression pattern. Parameters:

pattern (required): Regex pattern to match
group (optional): Capture group to extract (default: 1)

Example:

{
  "css": "span::text",
  "processors": [
    {"type": "regex", "pattern": "Price: \\$([\\d.]+)"}
  ]
}

Transformation:

"Price: $99.99" → "99.99"

Multiple groups:

{"type": "regex", "pattern": "(\\d+) items", "group": 1}

Returns original value if no match. Works on: Strings only

4. cast

Convert value to specified type. Parameters:

to (required): Target type - "int", "float", "bool", or "str"

Example:

{
  "css": "span.rating::attr(data-rating)",
  "processors": [
    {"type": "cast", "to": "float"}
  ]
}

Transformations:

"4.5" → 4.5 (float)
"42" → 42 (int)
"true" → True (bool)

Boolean conversion:

true, 1, yes, on → True
Everything else → False

Returns None if conversion fails. Works on: Any type

5. join

Join list values into a single string. Parameters:

separator (optional): String to join with (default: " ")

Example:

{
  "css": "li.feature::text",
  "get_all": true,
  "processors": [
    {"type": "join", "separator": ", "}
  ]
}

Transformation:

["WiFi", "Bluetooth", "GPS"] → "WiFi, Bluetooth, GPS"

Filters out None values automatically. Works on: Lists only

6. default

Return default value if input is None, empty string, or empty list. Parameters:

default (required): Fallback value

Example:

{
  "css": "span.optional::text",
  "processors": [
    {"type": "default", "default": "N/A"}
  ]
}

Transformations:

None → "N/A"
"" → "N/A"
[] → "N/A"
"actual value" → "actual value"

Works on: Any type

7. lowercase

Convert strings to lowercase. Parameters: None Example:

{
  "css": "span.status::text",
  "processors": [
    {"type": "strip"},
    {"type": "lowercase"}
  ]
}

Transformation:

"IN STOCK" → "in stock"

Works on: Strings and lists of strings

8. parse_datetime

Parse datetime string into ISO format. Parameters:

format (optional): strptime format string (if None, uses dateutil parser for flexible parsing)

Example with format:

{
  "css": "time.date::attr(datetime)",
  "processors": [
    {"type": "parse_datetime", "format": "%Y-%m-%d"}
  ]
}

Example without format (auto-detect):

{
  "css": "span.date::text",
  "processors": [
    {"type": "parse_datetime"}
  ]
}

Transformations:

"2024-02-24" → "2024-02-24T00:00:00" (ISO format)
"February 24, 2024" → "2024-02-24T00:00:00"
"24/02/2024" → "2024-02-24T00:00:00" (auto-detected)

Stored as ISO string in database (automatically serialized). Returns None if parsing fails. Works on: Strings only

Processor Chaining

Processors run sequentially. Output of one becomes input to the next.

Example 1: Clean and Convert Price

{
  "css": "span.price::text",
  "processors": [
    {"type": "strip"},                           // "  $99.99  " → "$99.99"
    {"type": "replace", "old": "$", "new": ""},  // "$99.99" → "99.99"
    {"type": "cast", "to": "float"}              // "99.99" → 99.99
  ]
}

Example 2: Extract Rating Number

{
  "css": "div.rating::text",
  "processors": [
    {"type": "strip"},                           // "  Rating: 4.5 stars  " → "Rating: 4.5 stars"
    {"type": "regex", "pattern": "([\\d.]+)"},   // "Rating: 4.5 stars" → "4.5"
    {"type": "cast", "to": "float"}              // "4.5" → 4.5
  ]
}

Example 3: Normalize Text

{
  "css": "span.status::text",
  "processors": [
    {"type": "strip"},
    {"type": "lowercase"},
    {"type": "replace", "old": " ", "new": "_"}
  ]
}

Input: " In Stock "
Output: "in_stock"

Example 4: Handle Missing Values

{
  "css": "span.optional-field::text",
  "processors": [
    {"type": "strip"},
    {"type": "default", "default": "Not specified"}
  ]
}

Common Patterns

Extracting Currency Values

{
  "price": {
    "css": "span.price::text",
    "processors": [
      {"type": "strip"},
      {"type": "regex", "pattern": "\\$([\\d,.]+)"},
      {"type": "replace", "old": ",", "new": ""},
      {"type": "cast", "to": "float"}
    ]
  }
}

Handles: "$1,299.99", "Price: $99", " $42.50 "

Extracting Numbers from Text

{
  "quantity": {
    "css": "div.quantity::text",
    "processors": [
      {"type": "regex", "pattern": "(\\d+)"},
      {"type": "cast", "to": "int"}
    ]
  }
}

Handles: "23 items", "Quantity: 5", "42"

Boolean Fields

{
  "in_stock": {
    "css": "span.availability::text",
    "processors": [
      {"type": "lowercase"},
      {"type": "regex", "pattern": "(in stock|available)"},
      {"type": "cast", "to": "bool"}
    ]
  }
}

Returns: True if “in stock” or “available”, else False

Date Fields

{
  "published_date": {
    "css": "time::attr(datetime)",
    "processors": [
      {"type": "parse_datetime"}
    ]
  }
}

Auto-detects format, stores as ISO string.

Lists to Comma-Separated String

{
  "tags": {
    "css": "li.tag::text",
    "get_all": true,
    "processors": [
      {"type": "join", "separator": ", "}
    ]
  }
}

Input: ["Python", "Web Scraping", "Automation"]
Output: "Python, Web Scraping, Automation"

Complete Examples

E-commerce Product

{
  "callbacks": {
    "parse_product": {
      "extract": {
        "name": {
          "css": "h1.product-name::text",
          "processors": [{"type": "strip"}]
        },
        "price": {
          "css": "span.price::text",
          "processors": [
            {"type": "strip"},
            {"type": "regex", "pattern": "\\$([\\d,.]+)"},
            {"type": "replace", "old": ",", "new": ""},
            {"type": "cast", "to": "float"}
          ]
        },
        "rating": {
          "css": "div.rating::attr(data-rating)",
          "processors": [{"type": "cast", "to": "float"}]
        },
        "in_stock": {
          "css": "span.availability::text",
          "processors": [
            {"type": "lowercase"},
            {"type": "regex", "pattern": "(in stock|available)"},
            {"type": "cast", "to": "bool"}
          ]
        },
        "features": {
          "css": "li.feature::text",
          "get_all": true,
          "processors": [{"type": "join", "separator": ", "}]
        }
      }
    }
  }
}

Job Listing

{
  "callbacks": {
    "parse_job": {
      "extract": {
        "title": {
          "css": "h1.job-title::text",
          "processors": [{"type": "strip"}]
        },
        "salary_min": {
          "css": "span.salary-min::text",
          "processors": [
            {"type": "strip"},
            {"type": "replace", "old": "$", "new": ""},
            {"type": "replace", "old": ",", "new": ""},
            {"type": "cast", "to": "int"}
          ]
        },
        "salary_max": {
          "css": "span.salary-max::text",
          "processors": [
            {"type": "strip"},
            {"type": "replace", "old": "$", "new": ""},
            {"type": "replace", "old": ",", "new": ""},
            {"type": "cast", "to": "int"}
          ]
        },
        "posted_date": {
          "css": "time.posted-date::attr(datetime)",
          "processors": [{"type": "parse_datetime"}]
        },
        "remote": {
          "css": "span.job-type::text",
          "processors": [
            {"type": "lowercase"},
            {"type": "regex", "pattern": "(remote|work from home)"},
            {"type": "cast", "to": "bool"}
          ]
        },
        "skills": {
          "css": "span.skill::text",
          "get_all": true,
          "processors": [{"type": "join", "separator": ", "}]
        }
      }
    }
  }
}

Real Estate Listing

{
  "callbacks": {
    "parse_property": {
      "extract": {
        "address": {
          "css": "h1.property-address::text",
          "processors": [{"type": "strip"}]
        },
        "price": {
          "css": "span.property-price::text",
          "processors": [
            {"type": "strip"},
            {"type": "regex", "pattern": "\\$([\\d,.]+)"},
            {"type": "replace", "old": ",", "new": ""},
            {"type": "cast", "to": "float"}
          ]
        },
        "bedrooms": {
          "css": "span.bedrooms::text",
          "processors": [
            {"type": "regex", "pattern": "(\\d+)"},
            {"type": "cast", "to": "int"}
          ]
        },
        "bathrooms": {
          "css": "span.bathrooms::text",
          "processors": [
            {"type": "regex", "pattern": "([\\d.]+)"},
            {"type": "cast", "to": "float"}
          ]
        },
        "sqft": {
          "css": "span.square-feet::text",
          "processors": [
            {"type": "regex", "pattern": "([\\d,]+)"},
            {"type": "replace", "old": ",", "new": ""},
            {"type": "cast", "to": "int"}
          ]
        },
        "amenities": {
          "css": "li.amenity::text",
          "get_all": true,
          "processors": [{"type": "join", "separator": ", "}]
        }
      }
    }
  }
}

Error Handling

Processors handle errors gracefully:

Graceful Failures
Chain Behavior

strip, replace, lowercase, join: Return original value if not applicable type
regex: Returns original value if pattern doesn’t match
cast: Returns None if conversion fails
parse_datetime: Returns None if parsing fails
Unknown processor type: Skipped, logs warning

If a processor fails mid-chain, subsequent processors receive the last valid value or None.Example:

[
  {"type": "strip"},        // "  abc  " → "abc"
  {"type": "cast", "to": "int"},  // "abc" → None (conversion fails)
  {"type": "default", "default": 0}  // None → 0
]

Final output: 0

Best Practices

Always strip text fields

Prevents whitespace issues:

{"processors": [{"type": "strip"}]}

Use regex before cast

Extract numeric part first, then convert type:

[
  {"type": "regex", "pattern": "([\\d.]+)"},
  {"type": "cast", "to": "float"}
]

Chain replace for complex cleaning

Multiple replace processors handle different cases:

[
  {"type": "replace", "old": "$", "new": ""},
  {"type": "replace", "old": ",", "new": ""}
]

Default at the end

Apply fallback after all transformations:

[
  {"type": "strip"},
  {"type": "cast", "to": "float"},
  {"type": "default", "default": 0.0}
]

Test selectors first

Use analyze command before adding processors:

./scrapai analyze --test "selector"

Validate processor output

Run test crawl and check with show command:

./scrapai crawl spider --limit 5 --project proj
./scrapai show 1 --project proj

Troubleshooting

Processor Returns None

Check processor type

Verify processor name is correct (typo?)

Validate input type

Some processors only work on specific types:

regex: strings only
join: lists only
parse_datetime: strings only

Test without processors

Remove processors temporarily to see raw extracted value

Check logs

Look for processor warnings in crawl logs

Wrong Output Type

Add cast processor at the end:

{"processors": [{"type": "cast", "to": "float"}]}

Regex Not Matching

Test pattern separately

Use online regex tester (regex101.com)

Check escaping

Double backslashes in JSON:

{"pattern": "\\$([\\d.]+)"}

Add default fallback

[
  {"type": "regex", "pattern": "([\\d.]+)"},
  {"type": "default", "default": null}
]

Date Parsing Fails

Try without format

Let dateutil auto-detect:

{"type": "parse_datetime"}

Specify exact format

If auto-detect fails:

{"type": "parse_datetime", "format": "%Y-%m-%d"}

Check date format

View raw extracted value to understand format

Custom Callbacks

Extract structured data with callbacks

Extractors

Content extraction strategies

Get Started

Core Concepts

Guides

AI Agents

Configuration

Advanced

​Available Processors

strip

replace

regex

cast

join

default

lowercase

parse_datetime

​Processor Reference

​1. strip

​2. replace

​3. regex

​4. cast

​5. join

​6. default

​7. lowercase

​8. parse_datetime

​Processor Chaining

​Example 1: Clean and Convert Price

​Example 2: Extract Rating Number

​Example 3: Normalize Text

​Example 4: Handle Missing Values

​Common Patterns

​Extracting Currency Values

​Extracting Numbers from Text

​Boolean Fields

​Date Fields

​Lists to Comma-Separated String

​Complete Examples

​E-commerce Product

​Job Listing

​Real Estate Listing

​Error Handling

​Best Practices

​Troubleshooting

​Processor Returns None

​Wrong Output Type

​Regex Not Matching

​Date Parsing Fails

​Related Guides

Custom Callbacks

Extractors

Available Processors

Processor Reference

1. strip

2. replace

3. regex

4. cast

5. join

6. default

7. lowercase

8. parse_datetime

Processor Chaining

Example 1: Clean and Convert Price

Example 2: Extract Rating Number

Example 3: Normalize Text

Example 4: Handle Missing Values

Common Patterns

Extracting Currency Values

Extracting Numbers from Text

Boolean Fields

Date Fields

Lists to Comma-Separated String

Complete Examples

E-commerce Product

Job Listing

Real Estate Listing

Error Handling

Best Practices

Troubleshooting

Processor Returns None

Wrong Output Type

Regex Not Matching

Date Parsing Fails

Related Guides