bittensor.core.synapse

bittensor.core.synapse#

Classes#

Synapse

Represents a Synapse in the Bittensor network, serving as a communication schema between neurons (nodes).

TerminalInfo

TerminalInfo encapsulates detailed information about a network synapse (node) involved in a communication process.

Functions#

cast_float(raw)

Converts a string to a float, if the string is not None.

cast_int(raw)

Converts a string to an integer, if the string is not None.

get_size(obj[, seen])

Recursively finds size of objects.

Module Contents#

class bittensor.core.synapse.Synapse(/, **data)#

Bases: pydantic.BaseModel

Represents a Synapse in the Bittensor network, serving as a communication schema between neurons (nodes).

Synapses ensure the format and correctness of transmission tensors according to the Bittensor protocol. Each Synapse type is tailored for a specific machine learning (ML) task, following unique compression and communication processes. This helps maintain sanitized, correct, and useful information flow across the network.

The Synapse class encompasses essential network properties such as HTTP route names, timeouts, request sizes, and terminal information. It also includes methods for serialization, deserialization, attribute setting, and hash computation, ensuring secure and efficient data exchange in the network.

The class includes Pydantic validators and root validators to enforce data integrity and format. Additionally, properties like is_success, is_failure, is_timeout, etc., provide convenient status checks based on dendrite responses.

Think of Bittensor Synapses as glorified pydantic wrappers that have been designed to be used in a distributed network. They provide a standardized way to communicate between neurons, and are the primary mechanism for communication between neurons in Bittensor.

Key Features:

  1. HTTP Route Name (name attribute):

    Enables the identification and proper routing of requests within the network. Essential for users defining custom routes for specific machine learning tasks.

  2. Query Timeout (timeout attribute):

    Determines the maximum duration allowed for a query, ensuring timely responses and network efficiency. Crucial for users to manage network latency and response times, particularly in time-sensitive applications.

  3. Request Sizes (total_size, header_size attributes):

    Keeps track of the size of request bodies and headers, ensuring efficient data transmission without overloading the network. Important for users to monitor and optimize the data payload, especially in bandwidth-constrained environments.

  4. Terminal Information (dendrite, axon attributes):

    Stores information about the dendrite (receiving end) and axon (sending end), facilitating communication between nodes. Users can access detailed information about the communication endpoints, aiding in debugging and network analysis.

  5. Body Hash Computation (computed_body_hash, required_hash_fields):

    Ensures data integrity and security by computing hashes of transmitted data. Provides users with a mechanism to verify data integrity and detect any tampering during transmission. It is recommended that names of fields in required_hash_fields are listed in the order they are defined in the class.

  6. Serialization and Deserialization Methods:

    Facilitates the conversion of Synapse objects to and from a format suitable for network transmission. Essential for users who need to customize data formats for specific machine learning models or tasks.

  7. Status Check Properties (is_success, is_failure, is_timeout, etc.):

    Provides quick and easy methods to check the status of a request, improving error handling and response management. Users can efficiently handle different outcomes of network requests, enhancing the robustness of their applications.

Example usage:

# Creating a Synapse instance with default values
from bittensor.core.synapse import Synapse

synapse = Synapse()

# Setting properties and input
synapse.timeout = 15.0
synapse.name = "MySynapse"

# Not setting fields that are not defined in your synapse class will result in an error, e.g.:
synapse.dummy_input = 1 # This will raise an error because dummy_input is not defined in the Synapse class

# Get a dictionary of headers and body from the synapse instance
synapse_dict = synapse.model_dump_json()

# Get a dictionary of headers from the synapse instance
headers = synapse.to_headers()

# Reconstruct the synapse from headers using the classmethod 'from_headers'
synapse = Synapse.from_headers(headers)

# Deserialize synapse after receiving it over the network, controlled by `deserialize` method
deserialized_synapse = synapse.deserialize()

# Checking the status of the request
if synapse.is_success:
    print("Request succeeded")

# Checking and setting the status of the request
print(synapse.axon.status_code)
synapse.axon.status_code = 408 # Timeout
Parameters:

  • name (str) – HTTP route name, set on axon.attach().

  • timeout (float) – Total query length, set by the dendrite terminal.

  • total_size (int) – Total size of request body in bytes.

  • header_size (int) – Size of request header in bytes.

  • dendrite (TerminalInfo()) – Information about the dendrite terminal.

  • axon (TerminalInfo()) – Information about the axon terminal.

  • computed_body_hash (str) – Computed hash of the request body.

  • required_hash_fields (list[str]) – Fields required to compute the body hash.

  • data (Any)

deserialize()#

Custom deserialization logic for subclasses.

Return type:

Synapse

__setattr__()#

Override method to make required_hash_fields read-only.

Parameters:

  • name (str)

  • value (Any)

get_total_size()#

Calculates and returns the total size of the object.

Return type:

int

to_headers()#

Constructs a dictionary of headers from instance properties.

Return type:

dict

body_hash()#

Computes a SHA3-256 hash of the serialized body.

Return type:

str

parse_headers_to_inputs()#

Parses headers to construct an inputs dictionary.

Parameters:

headers (dict)

Return type:

dict

from_headers()#

Creates an instance from a headers dictionary.

Parameters:

headers (dict)

Return type:

Synapse

This class is a cornerstone in the Bittensor framework, providing the necessary tools for secure, efficient, and standardized communication in a decentralized environment.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__setattr__(name, value)#

Override the __setattr__() method to make the required_hash_fields property read-only.

This is a security mechanism such that the required_hash_fields property cannot be overridden by the user or malicious code.

Parameters:

  • name (str)

  • value (Any)

_extract_header_size#
_extract_timeout#
_extract_total_size#
axon: TerminalInfo | None#
property body_hash: str#

Computes a SHA3-256 hash of the serialized body of the Synapse instance.

This hash is used to ensure the data integrity and security of the Synapse instance when it’s transmitted across the network. It is a crucial feature for verifying that the data received is the same as the data sent.

Process:

  1. Iterates over each required field as specified in required_hash_fields.

  2. Concatenates the string representation of these fields.

  3. Applies SHA3-256 hashing to the concatenated string to produce a unique fingerprint of the data.

Example:

synapse = Synapse(name="ExampleRoute", timeout=10)
hash_value = synapse.body_hash
# hash_value is the SHA3-256 hash of the serialized body of the Synapse instance
Returns:

The SHA3-256 hash as a hexadecimal string, providing a fingerprint of the Synapse instance’s data for integrity checks.

Return type:

str

computed_body_hash: str | None#
dendrite: TerminalInfo | None#
deserialize()#

Deserializes the Synapse object.

This method is intended to be overridden by subclasses for custom deserialization logic. In the context of the Synapse superclass, this method simply returns the instance itself. When inheriting from this class, subclasses should provide their own implementation for deserialization if specific deserialization behavior is desired.

By default, if a subclass does not provide its own implementation of this method, the Synapse’s deserialize method will be used, returning the object instance as-is.

In its default form, this method simply returns the instance of the Synapse itself without any modifications. Subclasses of Synapse can override this method to add specific deserialization behaviors, such as converting serialized data back into complex object types or performing additional data integrity checks.

Example:

class CustomSynapse(Synapse):
    additional_data: str

    def deserialize(self) -> "CustomSynapse":
        # Custom deserialization logic
        # For example, decoding a base64 encoded string in 'additional_data'
        if self.additional_data:
            self.additional_data = base64.b64decode(self.additional_data).decode('utf-8')
        return self

serialized_data = '{"additional_data": "SGVsbG8gV29ybGQ="}'  # Base64 for 'Hello World'
custom_synapse = CustomSynapse.model_validate_json(serialized_data)
deserialized_synapse = custom_synapse.deserialize()

# deserialized_synapse.additional_data would now be 'Hello World'
Returns:

The deserialized Synapse object. In this default implementation, it returns the object itself.

Return type:

Synapse

property failed_verification: bool#

Checks if the dendrite’s status code indicates failed verification.

This method returns True if the status code of the dendrite is 401, which is the HTTP status code for unauthorized access.

Returns:

True if dendrite’s status code is 401, False otherwise.

Return type:

bool

classmethod from_headers(headers)#

Constructs a new Synapse instance from a given headers dictionary, enabling the re-creation of the Synapse’s state as it was prior to network transmission.

This method is a key part of the deserialization process in the Bittensor network, allowing nodes to accurately reconstruct Synapse objects from received data.

Example:

received_headers = {
    'bt_header_axon_address': '127.0.0.1',
    'bt_header_dendrite_port': '8080',
    # Other headers...
}
synapse = Synapse.from_headers(received_headers)
# synapse is a new Synapse instance reconstructed from the received headers
Parameters:

headers (dict) – The dictionary of headers containing serialized Synapse information.

Returns:

A new instance of Synapse, reconstructed from the parsed header information, replicating the original instance’s state.

Return type:

bittensor.core.synapse.Synapse

get_required_fields()#

Get the required fields from the model’s JSON schema.

get_total_size()#

Get the total size of the current object.

This method first calculates the size of the current object, then assigns it to the instance variable self.total_size() and finally returns this value.

Returns:

The total size of the current object.

Return type:

int

header_size: int | None#
property is_blacklist: bool#

Checks if the dendrite’s status code indicates a blacklisted request.

This method returns True if the status code of the dendrite is 403, which is the HTTP status code for a forbidden request.

Returns:

True if dendrite’s status code is 403, False otherwise.

Return type:

bool

property is_failure: bool#

Checks if the dendrite’s status code indicates failure.

This method returns True if the status code of the dendrite is not 200, which would mean the HTTP request was not successful.

Returns:

True if dendrite’s status code is not 200, False otherwise.

Return type:

bool

property is_success: bool#

Checks if the dendrite’s status code indicates success.

This method returns True if the status code of the dendrite is 200, which typically represents a successful HTTP request.

Returns:

True if dendrite’s status code is 200, False otherwise.

Return type:

bool

property is_timeout: bool#

Checks if the dendrite’s status code indicates a timeout.

This method returns True if the status code of the dendrite is 408, which is the HTTP status code for a request timeout.

Returns:

True if dendrite’s status code is 408, False otherwise.

Return type:

bool

model_config#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str | None#
classmethod parse_headers_to_inputs(headers)#

Interprets and transforms a given dictionary of headers into a structured dictionary, facilitating the reconstruction of Synapse objects.

This method is essential for parsing network-transmitted data back into a Synapse instance, ensuring data consistency and integrity.

Process:

  1. Separates headers into categories based on prefixes (axon, dendrite, etc.).

  2. Decodes and deserializes input_obj headers into their original objects.

  3. Assigns simple fields directly from the headers to the input dictionary.

Example:

received_headers = {
    'bt_header_axon_address': '127.0.0.1',
    'bt_header_dendrite_port': '8080',
    # Other headers...
}
inputs = Synapse.parse_headers_to_inputs(received_headers)
# inputs now contains a structured representation of Synapse properties based on the headers

Note

This is handled automatically when calling Synapse.from_headers(headers)() and does not need to be called directly.

Parameters:

headers (dict) – The headers dictionary to parse.

Returns:

A structured dictionary representing the inputs for constructing a Synapse instance.

Return type:

dict

required_hash_fields: ClassVar[tuple[str, Ellipsis]] = ()#
set_name_type(values)#
Parameters:

values (dict)

Return type:

dict

timeout: float | None#
to_headers()#

Converts the state of a Synapse instance into a dictionary of HTTP headers.

This method is essential for packaging Synapse data for network transmission in the Bittensor framework, ensuring that each key aspect of the Synapse is represented in a format suitable for HTTP communication.

Process:

  1. Basic Information: It starts by including the name and timeout of the Synapse, which are fundamental for identifying the query and managing its lifespan on the network.

  2. Complex Objects: The method serializes the axon and dendrite objects, if present, into strings. This serialization is crucial for preserving the state and structure of these objects over the network.

  3. Encoding: Non-optional complex objects are serialized and encoded in base64, making them safe for HTTP transport.

  4. Size Metrics: The method calculates and adds the size of headers and the total object size, providing valuable information for network bandwidth management.

Example Usage:

synapse = Synapse(name="ExampleSynapse", timeout=30)
headers = synapse.to_headers()
# headers now contains a dictionary representing the Synapse instance
Returns:

A dictionary containing key-value pairs representing the Synapse’s properties, suitable for HTTP communication.

Return type:

dict

total_size: int | None#
class bittensor.core.synapse.TerminalInfo(/, **data)#

Bases: pydantic.BaseModel

TerminalInfo encapsulates detailed information about a network synapse (node) involved in a communication process.

This class serves as a metadata carrier, providing essential details about the state and configuration of a terminal during network interactions. This is a crucial class in the Bittensor framework.

The TerminalInfo class contains information such as HTTP status codes and messages, processing times, IP addresses, ports, Bittensor version numbers, and unique identifiers. These details are vital for maintaining network reliability, security, and efficient data flow within the Bittensor network.

This class includes Pydantic validators and root validators to enforce data integrity and format. It is designed to be used natively within Synapses, so that you will not need to call this directly, but rather is used as a helper class for Synapses.

Parameters:

  • status_code (int) – HTTP status code indicating the result of a network request. Essential for identifying the outcome of network interactions.

  • status_message (str) – Descriptive message associated with the status code, providing additional context about the request’s result.

  • process_time (float) – Time taken by the terminal to process the call, important for performance monitoring and optimization.

  • ip (str) – IP address of the terminal, crucial for network routing and data transmission.

  • port (int) – Network port used by the terminal, key for establishing network connections.

  • version (int) – Bittensor version running on the terminal, ensuring compatibility between different nodes in the network.

  • nonce (int) – Unique, monotonically increasing number for each terminal, aiding in identifying and ordering network interactions.

  • uuid (str) – Unique identifier for the terminal, fundamental for network security and identification.

  • hotkey (str) – Encoded hotkey string of the terminal wallet, important for transaction and identity verification in the network.

  • signature (str) – Digital signature verifying the tuple of nonce, axon_hotkey, dendrite_hotkey, and uuid, critical for ensuring data authenticity and security.

  • data (Any)

Usage:

# Creating a TerminalInfo instance
from bittensor.core.synapse import TerminalInfo

terminal_info = TerminalInfo(
    status_code=200,
    status_message="Success",
    process_time=0.1,
    ip="198.123.23.1",
    port=9282,
    version=111,
    nonce=111111,
    uuid="5ecbd69c-1cec-11ee-b0dc-e29ce36fec1a",
    hotkey="5EnjDGNqqWnuL2HCAdxeEtN2oqtXZw6BMBe936Kfy2PFz1J1",
    signature="0x0813029319030129u4120u10841824y0182u091u230912u"
)

# Accessing TerminalInfo attributes
ip_address = terminal_info.ip
processing_duration = terminal_info.process_time

# TerminalInfo can be used to monitor and verify network interactions, ensuring proper communication and security within the Bittensor network.

TerminalInfo plays a pivotal role in providing transparency and control over network operations, making it an indispensable tool for developers and users interacting with the Bittensor ecosystem.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

_extract_nonce#
_extract_port#
_extract_process_time#
_extract_status_code#
_extract_version#
hotkey: str | None#
ip: str | None#
model_config#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

nonce: int | None#
port: int | None#
process_time: float | None#
signature: str | None#
status_code: int | None#
status_message: str | None#
uuid: str | None#
version: int | None#
bittensor.core.synapse.cast_float(raw)#

Converts a string to a float, if the string is not None.

This function attempts to convert a string to a float. If the string is None, it simply returns None.

Parameters:

raw (str) – The string to convert.

Returns:

The converted float, or None if the input was None.

Return type:

float or None

bittensor.core.synapse.cast_int(raw)#

Converts a string to an integer, if the string is not None.

This function attempts to convert a string to an integer. If the string is None, it simply returns None.

Parameters:

raw (str) – The string to convert.

Returns:

The converted integer, or None if the input was None.

Return type:

int or None

bittensor.core.synapse.get_size(obj, seen=None)#

Recursively finds size of objects.

This function traverses every item of a given object and sums their sizes to compute the total size.

Parameters:

  • obj (Any) – The object to get the size of.

  • seen (Optional[set]) – Set of object ids that have been calculated.

Returns:

The total size of the object.

Return type:

int

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