ORES package

Subpackages

• ores.scoring_systems package
• ores.wsgi package

Submodules

ores.api module

This module provides a ores.api.Session class that can maintain a client connection to an instance of ORES and efficiently generate scores.

Batching and parallelism are set by constructor arguments.

class ores.api.Session(host, user_agent=None, session=None, retries=5, batch_size=50, parallel_requests=4)

Constructs a session with an ORES API and provides facilities for scoring revisions in batch and parallel.

Parameters

hoststr

The host of ORES to connect to (preceed with “http” or “https”)

user_agentstr

A User-Agent header to send with every request

batch_sizeint

The number of scores to batch per request.

parallel_requestint

The maximum number of requests to make in parallel

retriesint

The maximum number of retries for basic HTTP errors before giving up

score(context, models, revids)

Genetate scores for model applied to a sequence of revisions.

Parameters

contextstr

The name of the context – usually the database name of a wiki

modelsiterable

The names of a models to apply

revidsiterable

A sequence of revision IDs to score.

class ores.api.Session(host, user_agent=None, session=None, retries=5, batch_size=50, parallel_requests=4)

Bases: object

Constructs a session with an ORES API and provides facilities for scoring revisions in batch and parallel.

Parameters

hoststr

The host of ORES to connect to (preceed with “http” or “https”)

user_agentstr

A User-Agent header to send with every request

batch_sizeint

The number of scores to batch per request.

parallel_requestint

The maximum number of requests to make in parallel

retriesint

The maximum number of retries for basic HTTP errors before giving up

DEFAULT_USERAGENT = 'ores.api default user-agent'

score(context, models, revids)

Genetate scores for model applied to a sequence of revisions.

Parameters

contextstr

The name of the context – usually the database name of a wiki

modelsiterable

The names of a models to apply

revidsiterable

A sequence of revision IDs to score.

ores.errors module

exception ores.errors.MissingContext

Bases: RuntimeError

exception ores.errors.MissingModels

Bases: RuntimeError

exception ores.errors.ScoreProcessorOverloaded

Bases: RuntimeError

exception ores.errors.TimeoutError

Bases: RuntimeError

exception ores.errors.TooManyRequestsError

Bases: RuntimeError

ores.score_request module

class ores.score_request.ScoreRequest(context_name, rev_ids, model_names, precache=False, include_features=False, injection_caches=None, model_info=None, ip=None)

Bases: object

format(rev_id=None, model_name=None)

Fomat a request or a sub-part of a request based on a rev_id and/or model_name. This is useful for logging.

classmethod from_json(data)

to_json()

ores.score_response module

class ores.score_response.ScoreResponse(context, request, model_info=None, scores=None, errors=None, features=None)

Bases: object

add_error(rev_id, model_name, error)

add_features(rev_id, model_name, features)

add_model_info(model_name, info_doc)

add_score(rev_id, model_name, score)

ores.scoring_context module

class ores.scoring_context.ClientScoringContext(name, model_map, *args, **kwargs)

Bases: ores.scoring_context.ScoringContext

A simplistic scoring context that is not capable of performing the scoring itself. This ScoringContext is intended to be used in clients where an external service actually implements the scoring pattern (e.g. ores.scoring_systems.CeleryQueue). This ScoringContext saves on unnecessary memory usage, but still provides access to basic informational functionality.

class ModelLoader

Bases: object

load(config, key)

load_model_and_queue(q, config, key)

model_features(model_name)

model_version(model_name)

process_score(*args, **kwargs)

class ores.scoring_context.ScoringContext(name, model_map, extractor)

Bases: dict

Represents a context in which scoring can take place. Usually, a wiki is 1:1 with a “ScoringContext”.

Parameters

namestr

The name of the context in which scoring will happen. This is usually a wiki’s database name.

model_mapdict

A mapping between names and revscoring.Model instances

extractorrevscoring.Extractor

An extractor to use for gathering feature values

class ModelLoader

Bases: object

load(config, key)

extract_root_dependency_caches(model_names, rev_ids, injection_caches=None)

Extracts a mapping of root revscoring.Datasource capable of generating the features needed for a particular set of models without additional IO. This method implements all of the IO heavy operations. The roots dependency caches produced by calling this method can then be passed to process_model_scores() for scoring.

Parameters

model_nameslist ( str )

The names of a revscoring.Model to extract the roots dependencies for

format_id_string(model_name, rev_id, request, injection_cache=None)

format_model_info(model_name, paths=None)

classmethod from_config(config, name, section_key='scoring_contexts')

Expects:

scoring_contexts:

enwiki:

scorer_models:

damaging: enwiki_damaging_2014 good-faith: enwiki_good-faith_2014

extractor: enwiki

ptwiki:

scorer_models:

damaging: ptwiki_damaging_2014 good-faith: ptwiki_good-faith_2014

extractor: ptwiki

extractors:

enwiki_api: … ptwiki_api: …

scorer_models:

enwiki_damaging_2014: … enwiki_good-faith_2014: …

classmethod map_from_config(config, context_names, section_key='scoring_contexts')

Loads a whole set of ScoringContext’s from a configuration file while maintaining a cache of model names. This aids in better memory management and allows model aliases to be implemented at the configuration level.

Returns

A map of context_names and ScoringContext’s where models are loaded once and reused cross contexts.

model_features(model_name)

model_version(model_name)

process_model_scores(model_names, root_cache, include_features=False)

Generates a score map for a set of models based on a root_cache. This method performs no substantial IO, but may incur substantial CPU usage.

Parameters

model_namesset ( str )

A set of models to score

root_cachedict ( str –> mixed )

A cache of pre-computed root_dependencies for a specific revision. See extract_root_dependency_caches()

include_featuresbool

If True, include a map of basic features used in scoring along with the model score. If False, just generate the scores.

class ores.scoring_context.ServerScoringContext(name, *args, **kwargs)

Bases: ores.scoring_context.ScoringContext

A scoring context that is only capable of scoring. This ScoringContext is intended to be used in clients where a web service (client) implements all of the model_info actions (e.g. ores.scoring_systems.CeleryQueue).

This ScoringContext saves on unnecessary memory usage, but still provides access to basic scoring functionality.

class ModelLoader

Bases: object

load(config, key)

load_model_and_queue(q, config, key)

ores.util module

ores.util.jsonify_error(error)

ores.util.timeout(func, *args, seconds=None, **kwargs)