HL7 v2 in Python

Zato supports HL7 v2.9, which is backward compatible with earlier versions including v2.3, v2.5, and v2.7. All standard segments and their datatypes are available as typed Python classes.

Configure an MLLP channel in Zato to listen for incoming HL7v2 messages. Your Python service receives parsed message objects automatically:

from zato.hl7v2 import HL7Message

msg = HL7Message.parse(raw_data)
patient = msg.pid.patient_name

Use HL7Message.parse() with the raw ER7 string:

from zato.hl7v2 import HL7Message

msg = HL7Message.parse(raw_data)
name = msg.pid.patient_name.family_name
mrn = msg.pid.patient_identifier_list

Yes, use semantic Python names instead of positional notation:

# Instead of PID.5, use:
msg.pid.patient_name

# Instead of PID.3, use:
msg.pid.patient_identifier_list

# Subcomponents work too:
msg.pid.patient_name.family_name

Yes, Zato has built-in MLLP support for sending and receiving HL7v2 messages. MLLP channels handle the framing protocol automatically, so you only work with parsed message objects in your Python code.

Yes, validate field lengths, cardinality, required fields, and datatype conformance:

from zato.hl7v2 import validate_message

result = validate_message(raw_data)
for error in result.errors:
    print(error.message)

Use parse_batch and parse_file to process multiple messages wrapped in BHS/BTS and FHS/FTS segments. Each message in the batch is parsed individually.

Yes, Zato supports transforming HL7v2 messages and segments to FHIR resources. You can map fields between standards and build FHIR bundles from HL7v2 messages.