TEXTPROTO Text protocol buffer
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File Information
Text protocol buffer
Data
.textproto
text/plain
Text Protocol Buffer (textproto)
Overview
Text Protocol Buffer (textproto) is a human-readable text format for representing Protocol Buffer messages. It provides a way to serialize and deserialize protobuf data in a format that's easy to read, edit, and debug, making it ideal for configuration files and testing.
File Details
- Extension:
.textproto
,.txtpb
,.pbtxt
- MIME Type:
text/plain
- Category: Data
- Binary/Text: Text
Technical Specifications
Format Structure
Text protobuf uses a simple key-value syntax:
field_name: value
repeated_field: value1
repeated_field: value2
message_field {
nested_field: value
}
Data Types Support
- Scalar types: int32, int64, float, double, bool, string
- Repeated fields: Lists of values
- Nested messages: Hierarchical structures
- Enums: Named constants
- Maps: Key-value pairs
History
- 2008: Protocol Buffers open-sourced by Google
- 2010: Text format specification formalized
- 2016: Proto3 introduces simplified syntax
- 2019: JSON mapping standardized
- 2020+: Continued evolution with new features
Structure Details
Basic Syntax
# Comments start with #
string_field: "Hello, World!"
int_field: 42
float_field: 3.14159
bool_field: true
bytes_field: "SGVsbG8=" # Base64 encoded
Repeated Fields
# Multiple values for repeated fields
tags: "important"
tags: "urgent"
tags: "work"
# Or array-like syntax
numbers: [1, 2, 3, 4, 5]
Nested Messages
person {
name: "John Doe"
age: 30
address {
street: "123 Main St"
city: "Anytown"
state: "CA"
zip_code: "12345"
}
}
Code Examples
Protocol Definition (.proto)
syntax = "proto3";
package example;
message Person {
string name = 1;
int32 age = 2;
repeated string email = 3;
message Address {
string street = 1;
string city = 2;
string state = 3;
string zip_code = 4;
}
Address address = 4;
enum PhoneType {
MOBILE = 0;
HOME = 1;
WORK = 2;
}
message PhoneNumber {
string number = 1;
PhoneType type = 2;
}
repeated PhoneNumber phone = 5;
}
message AddressBook {
repeated Person person = 1;
}
Text Protobuf Example
# example.textproto
person {
name: "Alice Smith"
age: 28
email: "[email protected]"
email: "[email protected]"
address {
street: "456 Oak Avenue"
city: "Springfield"
state: "IL"
zip_code: "62701"
}
phone {
number: "+1-555-123-4567"
type: MOBILE
}
phone {
number: "+1-555-987-6543"
type: WORK
}
}
person {
name: "Bob Johnson"
age: 35
email: "[email protected]"
address {
street: "789 Pine Street"
city: "Portland"
state: "OR"
zip_code: "97201"
}
phone {
number: "+1-555-555-5555"
type: HOME
}
}
Python Processing
import google.protobuf.text_format as text_format
from your_proto_pb2 import AddressBook
def read_textproto(filename):
"""Read text protobuf from file"""
address_book = AddressBook()
with open(filename, 'r') as f:
text_format.Merge(f.read(), address_book)
return address_book
def write_textproto(address_book, filename):
"""Write protobuf to text format"""
with open(filename, 'w') as f:
f.write(text_format.MessageToString(address_book))
def convert_binary_to_text(binary_file, text_file):
"""Convert binary protobuf to text format"""
address_book = AddressBook()
with open(binary_file, 'rb') as f:
address_book.ParseFromString(f.read())
with open(text_file, 'w') as f:
f.write(text_format.MessageToString(address_book))
# Usage
address_book = read_textproto('data.textproto')
for person in address_book.person:
print(f"Name: {person.name}, Age: {person.age}")
C++ Processing
#include <google/protobuf/text_format.h>
#include <google/protobuf/io/zero_copy_stream_impl.h>
#include <fstream>
#include "example.pb.h"
bool ReadTextProto(const std::string& filename, AddressBook* address_book) {
std::ifstream file(filename);
if (!file.is_open()) {
return false;
}
google::protobuf::io::IstreamInputStream input(&file);
return google::protobuf::TextFormat::Parse(&input, address_book);
}
bool WriteTextProto(const AddressBook& address_book, const std::string& filename) {
std::ofstream file(filename);
if (!file.is_open()) {
return false;
}
google::protobuf::io::OstreamOutputStream output(&file);
return google::protobuf::TextFormat::Print(address_book, &output);
}
Tools and Applications
Protocol Buffer Tools
- protoc: Official compiler with text format support
- buf: Modern protobuf tooling
- prototool: Protobuf development toolkit
- grpcurl: Testing gRPC services with textproto
IDEs and Editors
- VS Code: Protocol Buffer extensions
- IntelliJ IDEA: Protobuf plugin
- Vim: Protobuf syntax highlighting
- Emacs: Protobuf mode
Validation Tools
# Validate textproto file
protoc --encode=AddressBook example.proto < data.textproto > /dev/null
# Convert between formats
protoc --decode=AddressBook example.proto < data.bin > data.textproto
protoc --encode=AddressBook example.proto < data.textproto > data.bin
Best Practices
File Organization
- Use descriptive filenames
- Group related configurations
- Maintain consistent formatting
- Include documentation comments
Syntax Guidelines
- Use consistent indentation (2 spaces)
- Add comments for complex structures
- Validate against schema
- Use meaningful field names
Configuration Management
# config.textproto
server_config {
host: "localhost"
port: 8080
max_connections: 1000
# TLS configuration
tls_config {
cert_file: "/path/to/cert.pem"
key_file: "/path/to/key.pem"
ca_file: "/path/to/ca.pem"
}
# Feature flags
features {
enable_logging: true
enable_metrics: true
enable_tracing: false
}
}
Security Considerations
Input Validation
def safe_parse_textproto(content, message_type):
"""Safely parse textproto with validation"""
try:
message = message_type()
text_format.Merge(content, message)
# Validate required fields
if not message.IsInitialized():
raise ValueError("Required fields missing")
return message
except text_format.ParseError as e:
raise ValueError(f"Parse error: {e}")
Access Control
- Restrict file system access
- Validate field values
- Implement size limits
- Monitor parsing errors
Data Sanitization
- Escape special characters
- Validate string encodings
- Check numeric ranges
- Prevent injection attacks
Common Use Cases
Configuration Files
# Application configuration
app_config {
database {
host: "db.example.com"
port: 5432
name: "myapp"
ssl_mode: "require"
}
cache {
redis_url: "redis://cache.example.com:6379"
ttl_seconds: 3600
}
logging {
level: "INFO"
format: "json"
outputs: ["stdout", "file"]
}
}
Test Data
# test_data.textproto
test_cases {
name: "valid_user"
input {
user_id: "12345"
email: "[email protected]"
}
expected_output {
status: "success"
user_created: true
}
}
test_cases {
name: "invalid_email"
input {
user_id: "12346"
email: "invalid-email"
}
expected_output {
status: "error"
error_message: "Invalid email format"
}
}
Machine Learning Models
# model_config.textproto
model {
name: "image_classifier"
version: "v1.2.0"
layers {
type: "conv2d"
filters: 32
kernel_size: [3, 3]
activation: "relu"
}
layers {
type: "max_pooling2d"
pool_size: [2, 2]
}
training_config {
learning_rate: 0.001
batch_size: 32
epochs: 100
}
}
Text Protocol Buffers provide an excellent balance between human readability and structured data representation, making them ideal for configuration management, testing, and debugging in protobuf-based systems.
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