graflag.models

Data models for GraFlag API responses.

class graflag.models.ClusterInfo(manager_ip: str, is_connected: bool, swarm_initialized: bool, worker_nodes: Dict[str, str]]=<factory>, shared_dir: str = '', shared_contents: List[str] = <factory>, services: List[Dict] = <factory>, error: str | None = None)

Bases: object

Cluster status information.

manager_ip: str

is_connected: bool

swarm_initialized: bool

worker_nodes: List[Dict[str, str]]

shared_dir: str = ''

shared_contents: List[str]

services: List[Dict]

error: str | None = None

to_dict() → dict

class graflag.models.MethodInfo(name: str, description: str = '', source_code: str = '', integration: str = '', image: str = '', supported_data: str = '', parameters: Dict[str, ~typing.Any]=<factory>, has_dockerfile: bool = False, has_env: bool = False)

Bases: object

Method metadata.

name: str

description: str = ''

source_code: str = ''

integration: str = ''

upstream (the image runs the authors’ implementation) or reimplementation (this repository’s code, written from the paper). Empty for a method whose .env predates the key – rendered as “unstated”, which is what it is, rather than assumed to be either.

image: str = ''

The shared image this method builds from, from IMAGE= in its .env. Empty when the method builds its own – which is the common case; the seventeen bond_* methods share bond_base.

supported_data: str = ''

parameters: Dict[str, Any]

has_dockerfile: bool = False

has_env: bool = False

to_dict() → dict

class graflag.models.DatasetInfo(name: str, path: str = '', size_mb: float = 0.0, file_count: int = 0)

Bases: object

Dataset metadata.

name: str

path: str = ''

size_mb: float = 0.0

file_count: int = 0

to_dict() → dict

class graflag.models.ExperimentInfo(name: str, method: str, dataset: str, timestamp: str, status: str, has_results: bool = False, has_evaluation: bool = False, results_path: str | None = None, evaluation_path: str | None = None, service_name: str | None = None)

Bases: object

Experiment metadata and status.

name: str

method: str

dataset: str

timestamp: str

status: str

has_results: bool = False

has_evaluation: bool = False

results_path: str | None = None

evaluation_path: str | None = None

service_name: str | None = None

to_dict() → dict

class graflag.models.ExperimentResults(experiment_name: str, method_name: str, dataset: str, metadata: Dict[str, ~typing.Any]=<factory>, execution_time_ms: float | None = None, peak_memory_mb: float | None = None, peak_gpu_memory_mb: float | None = None, result_type: str | None = None, scores_available: bool = False)

Bases: object

Parsed experiment results.

experiment_name: str

method_name: str

dataset: str

metadata: Dict[str, Any]

execution_time_ms: float | None = None

peak_memory_mb: float | None = None

peak_gpu_memory_mb: float | None = None

result_type: str | None = None

scores_available: bool = False

to_dict() → dict

class graflag.models.EvaluationResults(experiment_name: str, metrics: Dict[str, float]=<factory>, plots_available: List[str] = <factory>, evaluation_path: str | None = None)

Bases: object

Parsed evaluation results.

experiment_name: str

metrics: Dict[str, float]

plots_available: List[str]

evaluation_path: str | None = None

to_dict() → dict

class graflag.models.ServiceCleanupResult(experiment: str, removed: bool, reason: str)

Bases: object

Outcome of considering one finished service for removal.

experiment: str

removed: bool

reason: str

to_dict() → dict

class graflag.models.ClearItem(kind: str, name: str, reason: str, size_bytes: int = 0, removed: bool = False)

Bases: object

One thing graflag clear considered removing, and why.

Every candidate is reported whether or not it was removed, so a dry run and an applied run print the same rows – the difference is removed.

kind: str

experiment | dataset | image | registry | stray

name: str

reason: str

The evidence for the verdict, in the words the report prints.

size_bytes: int = 0

Bytes on disk, 0 when not measured (registry repos before a GC).

removed: bool = False

to_dict() → dict

class graflag.models.ClearReport(applied: bool, items: List[ClearItem] = <factory>, freed_bytes: int = 0, errors: List[str] = <factory>, registry_collected: bool = False)

Bases: object

What graflag clear found, and what it did about it.

applied: bool

False for a dry run – nothing was removed.

items: List[ClearItem]

freed_bytes: int = 0

Bytes actually reclaimed. 0 on a dry run; on an applied run this is the sum over removed items, which for the registry counts only what a garbage collection actually freed, not the manifests deleted before it.

errors: List[str]

a failure to remove one item must not abort the sweep or fail the caller.

Type:

Non-fatal problems. Clearing is housekeeping

registry_collected: bool = False

True when registry blobs were collected, which needs the registry stopped – see core.clear.

property removed: List[ClearItem]

to_dict() → dict

class graflag.models.RunProgress(experiment_name: str, status: str, message: str = '', log_lines: List[str] = <factory>)

Bases: object

Progress information for run execution.

experiment_name: str

status: str

message: str = ''

log_lines: List[str]

to_dict() → dict

class graflag.models.VerificationReport(experiment_name: str, findings: Dict[str, str]]=<factory>, failed: int = 0, warned: int = 0, passed: int = 0, probe: Dict[str, ~typing.Any]=<factory>)

Bases: object

What graflag verify found in one experiment (see graflag.verify).

experiment_name: str

findings: List[Dict[str, str]]

…} per check, in the order they ran.

Type:

One {“level”

Type:

“ERROR” | “WARN” | “OK”, “message”

failed: int = 0

warned: int = 0

passed: int = 0

probe: Dict[str, Any]

counts, the reported and evaluated AUCs, the declared split. Never the scores themselves.

Type:

The probe summary the findings were drawn from

property ok: bool

True when no check failed. Warnings do not fail an experiment.

to_dict() → dict