Source code for kedro.contrib.io.matplotlib.matplotlib_s3_writer

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"""``MatplotlibS3Writer`` saves matplotlib objects as image files to S3."""

import copy
import io
from pathlib import Path
from typing import Any, Dict, List, Union

from matplotlib.pyplot import figure
from s3fs import S3FileSystem

from kedro.io import AbstractDataSet, DataSetError
from kedro.io.core import deprecation_warning


[docs]class MatplotlibS3Writer(AbstractDataSet): """``MatplotlibS3Writer`` saves matplotlib objects to an image file in S3. Example: :: >>> import matplotlib.pyplot as plt >>> from kedro.contrib.io.matplotlib import MatplotlibS3Writer >>> >>> # Saving single plot >>> plt.plot([1, 2, 3], [4, 5, 6]) >>> single_plot_writer = MatplotlibS3Writer( >>> bucket="my-super-great-bucket", filepath="matplot_lib_single_plot.png" >>> ) >>> single_plot_writer.save(plt) >>> plt.close() >>> >>> # Saving dictionary of plots >>> plots_dict = dict() >>> for colour in ["blue", "green", "red"]: >>> plots_dict[colour] = plt.figure() >>> plt.plot([1, 2, 3], [4, 5, 6], color=colour) >>> plt.close() >>> dict_plot_writer = MatplotlibS3Writer( >>> bucket="my-super-great-bucket", filepath="matplotlib_dict", >>> ) >>> dict_plot_writer.save(plots_dict) >>> >>> # Saving list of plots >>> plots_list = [] >>> for index in range(5): >>> plots_list.append(plt.figure()) >>> plt.plot([1,2,3],[4,5,6], color=colour) >>> list_plot_writer = MatplotlibS3Writer( >>> bucket="my-super-great-bucket", filepath="matplotlib_list" >>> ) >>> list_plot_writer.save(plots_list) """ # pylint: disable=too-many-arguments
[docs] def __init__( self, filepath: str, bucket_name: str, s3fs_args: Dict[str, Any] = None, credentials: Dict[str, Any] = None, save_args: Dict[str, Any] = None, ) -> None: """Creates a new instance of ``MatplotlibS3Writer``. Args: bucket_name: Name of the bucket without "s3://" prefix. filepath: Key path to matplot object file(s). s3fs_args: Arguments for ``S3FileSystem``. See https://s3fs.readthedocs.io/en/latest/api.html#s3fs.core.S3FileSystem credentials: Arguments for ``client_kwargs``. If needed ``aws_access_key_id`` and ``aws_secret_access_key`` are provided here. save_args: Save args passed to `plt.savefig`. See https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html """ deprecation_warning(self.__class__.__name__) _credentials = copy.deepcopy(credentials) or {} self._s3fs_args = copy.deepcopy(s3fs_args) or {} self._filepath = Path(filepath) self._save_args = save_args if save_args else dict() self._bucket_name = Path(bucket_name) self._s3 = S3FileSystem(client_kwargs=_credentials, **self._s3fs_args)
def _describe(self) -> Dict[str, Any]: return dict( bucket_name=self._bucket_name, filepath=self._filepath, s3fs_args=self._s3fs_args, save_args=self._save_args, ) def _load(self) -> None: raise DataSetError( "Loading not supported for `{}`".format(self.__class__.__name__) ) def _save(self, data: Union[figure, List[figure], Dict[str, figure]]) -> None: if isinstance(data, list): for index, plot in enumerate(data): full_key_path = ( self._bucket_name / self._filepath / (str(index) + ".png") ) self._save_to_s3(full_key_path=str(full_key_path), plot=plot) elif isinstance(data, dict): for plot_name, plot in data.items(): full_key_path = self._bucket_name / self._filepath / plot_name self._save_to_s3(full_key_path=str(full_key_path), plot=plot) else: full_key_path = self._bucket_name / self._filepath self._save_to_s3(full_key_path=str(full_key_path), plot=data) def _save_to_s3(self, full_key_path: str, plot: figure): bytes_buffer = io.BytesIO() plot.savefig(bytes_buffer, **self._save_args) with self._s3.open(full_key_path, mode="wb") as s3_file: s3_file.write(bytes_buffer.getvalue()) def _exists(self) -> bool: load_path = str(self._bucket_name / self._filepath) return self._s3.isfile(load_path) or ( self._s3.isdir(load_path) and bool(list(self._s3.walk(load_path))) )