asreview.Project#

class asreview.Project(project_path, project_id=None)[source]#

Bases: object

Project class for ASReview project files.

Methods

__init__(project_path[, project_id])

add_dataset(fp[, dataset_id, file_writer])

Add a dataset to the project file.

add_feature_matrix(feature_matrix, name)

Add feature matrix to project file.

add_review([review_id, cycle, reviewer, status])

Add new review metadata.

create(project_path[, project_id, ...])

Initialize the necessary files specific to the web app.

delete_review([remove_folders])

export(export_fp)

get_feature_matrix(name)

Get the feature matrix from the project file.

get_review_error([review_id])

load(asreview_file, project_path[, ...])

mark_review_finished([review_id])

Mark a review in the project as finished.

read_input_data([reader])

remove_dataset()

Remove dataset from project.

remove_review_error([review_id])

set_review_error(err[, review_id])

update_config(**kwargs)

Update project info

update_review([review_id, cycle, state])

Update review metadata.

Attributes

config

data_dir

data_store

feature_matrices

reviews

add_dataset(fp, dataset_id=None, file_writer=None)[source]#

Add a dataset to the project file.

Parameters:

fp (str, Path) – Filepath to the dataset. It will be copied to the correct location in the project file.

add_feature_matrix(feature_matrix, name)[source]#

Add feature matrix to project file.

Parameters:

  • feature_matrix (numpy.ndarray, scipy.sparse.csr.csr_matrix) – The feature matrix to add to the project file.

  • name (str) – Name of the feature extractor.

add_review(review_id=None, cycle=None, reviewer=None, status='setup')[source]#

Add new review metadata.

Parameters:

  • review_id (str) – The review_id uuid4.

  • cycle – An active learning cycle object to add to the review. This object is used to store the configuration of the active learning cycle to file.

  • reviewer (object) – A reviewer object with to_sql() method.

  • status (str) – The status of the review. One of ‘setup’, ‘running’, ‘finished’.

property config#
classmethod create(project_path, project_id=None, project_mode='oracle', project_name=None, project_tags=None)[source]#

Initialize the necessary files specific to the web app.

property data_dir#
property data_store#
delete_review(remove_folders=False)[source]#
export(export_fp)[source]#
property feature_matrices#
get_feature_matrix(name)[source]#

Get the feature matrix from the project file.

Parameters:

name (str) – Name of the feature extractor for which to get the cached matrix.

Returns:

numpy.ndarray, scipy.sparse – (Sparse) feature matrix.

get_review_error(review_id=None)[source]#
classmethod load(asreview_file, project_path, safe_import=False, reset_model_if_not_found=False)[source]#
mark_review_finished(review_id=None)[source]#

Mark a review in the project as finished.

If no review_id is given, mark the first review as finished.

Parameters:

review_id (str) – Identifier of the review to mark as finished.

read_input_data(reader=None, *args, **kwargs)[source]#
remove_dataset()[source]#

Remove dataset from project.

remove_review_error(review_id=None)[source]#
property reviews#
set_review_error(err, review_id=None)[source]#
update_config(**kwargs)[source]#

Update project info

update_review(review_id=None, cycle=None, state=None, **kwargs)[source]#

Update review metadata.

Parameters:

  • review_id (str) – The review_id uuid4. Default None, which is the first added review.

  • status (str) – The status of the review. One of ‘setup’, ‘running’, ‘finished’.