Implementation:Datajuicer Data juicer CleanEmailMapper

Knowledge Sources	Datajuicer_Data_juicer
Domains	Data_Processing, Mapping
Last Updated	2026-02-14 16:00 GMT

Overview

Concrete tool for removing or replacing email addresses from text samples provided by Data-Juicer.

Description

CleanEmailMapper is a mapper operator that cleans email addresses from text samples using regular expression matching. It applies a regex pattern (default matches standard email formats like user@domain.tld) to each text in a batch, replacing matches with a configurable replacement string (empty by default, effectively removing emails). A custom regex pattern can be provided for specialized matching needs. It operates in batched mode for efficiency. It extends the Mapper base class.

Usage

Import when you need to strip personally identifiable email addresses from training data for privacy compliance.

Code Reference

Source Location

• Repository: Datajuicer_Data_juicer
• File: data_juicer/ops/mapper/clean_email_mapper.py

Signature

@OPERATORS.register_module("clean_email_mapper")
class CleanEmailMapper(Mapper):
    def __init__(self,
                 pattern: Optional[str] = None,
                 repl: str = "",
                 *args, **kwargs):

Import

from data_juicer.ops.mapper.clean_email_mapper import CleanEmailMapper

I/O Contract

Inputs

Name	Type	Required	Description
pattern	Optional[str]	No	Regular expression pattern to search for within text. Default: standard email pattern
repl	str	No	Replacement string for matched patterns. Default: "" (removes emails)

Outputs

Name	Type	Description
samples	Dict	Transformed samples with email addresses removed or replaced in text

Usage Examples

YAML Configuration

process:
  - clean_email_mapper:
      repl: "<EMAIL>"

Related Pages

• Environment:Datajuicer_Data_juicer_Python_Runtime_Environment