add isort support with black profile

.circleci/config.yml

@@ -1009,7 +1009,7 @@ workflows:
       - tox-base:
           name: "code-check"
           python_version_minor: 8
-          toxenv: "protocheck,generatecheck,codecovcheck,mypy,mypy-report,pyupgrade,black,flake8,docstrings"
+          toxenv: "protocheck,generatecheck,codecovcheck,mypy,mypy-report,pyupgrade,black,isort-check,flake8,docstrings"
       #
       # Unit tests with pytest on Linux, using real wandb server
       #

pyproject.toml

@@ -2,20 +2,24 @@
 line-length = 88
 include = '\.pyi?$'
 exclude = '''
-  wandb/vendor/
-| wandb/old/
+wandb/vendor/
 | wandb/bin/
 | wandb/proto/
 | wandb/proto_check/
 | wandb/sdk/launch/deploys/
 | wandb/run*
 | wandb/offline-run*
-| tests/fixtures/
-| tests/logs/
-| tests/notebooks/
 | __pycache__
 | .pyc
 '''
 
 [tool.isort]
 profile = "black"
+skip = ["wandb/__init__.py"]
+extend_skip_glob = [
+    "wandb/vendor/**",
+    "wandb/proto/*.py",
+    "wandb/proto_check/*.py",
+    "tests/**",
+    "tools/**",
+]

tests/.isort.cfg

@@ -0,0 +1,3 @@
+[settings]
+profile=black
+known_third_party=wandb

tests/functional_tests/t0_main/catboost/t1_regression.py

@@ -1,9 +1,9 @@
 #!/usr/bin/env python
 """Test CatBoost integration."""
 
-from catboost import CatBoostClassifier, datasets, Pool
 import wandb
-from wandb.catboost import log_summary, WandbCallback
+from catboost import CatBoostClassifier, Pool, datasets
+from wandb.catboost import WandbCallback, log_summary
 
 train_df, _ = datasets.msrank_10k()
 X, Y = train_df[train_df.columns[1:]], train_df[train_df.columns[0]]

tests/functional_tests/t0_main/console/test_tqdm_nested.py

@@ -4,7 +4,6 @@
 import tqdm
 import wandb
 
-
 run = wandb.init()
 wandb.log(dict(this=2))
 print("before progress")

tests/functional_tests/t0_main/debug/t3_sentry_userproc.py

@@ -3,7 +3,6 @@
 
 import wandb
 
-
 with mock.patch(
     "wandb.sdk.wandb_init._WandbInit.init", mock.Mock(side_effect=Exception("injected"))
 ):

tests/functional_tests/t0_main/fastai/t1_v1.py

@@ -1,8 +1,7 @@
-from fastai.vision import *  # noqa: F403
 import wandb
+from fastai.vision import *  # noqa: F403
 from wandb.fastai import WandbCallback
 
-
 wandb.init()
 
 path = untar_data(URLs.MNIST_SAMPLE)  # noqa: F405

tests/functional_tests/t0_main/imports/10-batch10.py

@@ -53,7 +53,6 @@
 import wandb
 import zenml  # noqa: F401
 
-
 run = wandb.init()
 wandb.log(dict(loss=1))
 run.finish()

tests/functional_tests/t0_main/jax/01-log-bfloat16.py

@@ -4,7 +4,6 @@
 import jax.numpy as jnp
 import wandb
 
-
 if __name__ == "__main__":
     run = wandb.init()
     m1 = jnp.array(1.0, dtype=jnp.float32)

tests/functional_tests/t0_main/keras/test_keras_flops_functional.py

@@ -3,7 +3,6 @@
 import wandb
 from wandb.keras import WandbCallback
 
-
 np.random.seed(42)
 x = np.random.randint(255, size=(100, 28, 28, 1))
 y = np.random.randint(10, size=(100,))

tests/functional_tests/t0_main/keras/test_keras_nonnumeric.py

@@ -2,7 +2,6 @@
 import tensorflow as tf
 import wandb
 
-
 dftrain = pd.read_csv("https://storage.googleapis.com/tf-datasets/titanic/train.csv")
 y_train = dftrain.pop("survived")
 dftrain = dftrain[["sex", "class", "age", "fare", "n_siblings_spouses", "parch"]]

tests/functional_tests/t0_main/keras/test_keras_tensorboard.py

@@ -1,7 +1,7 @@
 import numpy as np
 import tensorflow as tf
-from tensorflow.keras.callbacks import TensorBoard
 import wandb
+from tensorflow.keras.callbacks import TensorBoard
 from wandb.keras import WandbCallback
 
 wandb.tensorboard.patch(root_logdir="logs")

tests/functional_tests/t0_main/kfp/kfp-pipeline-helper.py

@@ -3,8 +3,8 @@
 from typing import NamedTuple
 
 import kfp
-from kfp import components
 import kfp.dsl as dsl
+from kfp import components
 from kubernetes.client.models import V1EnvVar
 from wandb_probe import wandb_probe_package
 
@@ -30,11 +30,12 @@ def preprocess_data(
     mlpipeline_ui_metadata_path: components.OutputPath(),
     seed: int = 1337,
 ):
+    import json
+
     import numpy as np
+    import wandb
     from sklearn import datasets
     from sklearn.model_selection import train_test_split
-    import wandb
-    import json
 
     def add_wandb_visualization(run, mlpipeline_ui_metadata_path):
         """NOTE: To use this, you must modify your component to have an output called `mlpipeline_ui_metadata_path` AND call `wandb.init` yourself inside that component.
@@ -91,11 +92,12 @@ def train_model(
     model_path: components.OutputPath("sklearn_model"),  # noqa: F821
     mlpipeline_ui_metadata_path: components.OutputPath(),
 ):
+    import json
+
     import joblib
     import numpy as np
-    from sklearn.ensemble import RandomForestClassifier
     import wandb
-    import json
+    from sklearn.ensemble import RandomForestClassifier
 
     def add_wandb_visualization(run, mlpipeline_ui_metadata_path):
         """NOTE: To use this, you must modify your component to have an output called `mlpipeline_ui_metadata_path` AND call `wandb.init` yourself inside that component.
@@ -148,14 +150,14 @@ def test_model(
 ) -> NamedTuple(
     "Output", [("accuracy", float), ("precision", float), ("recall", float)]
 ):
+    import json
     from collections import namedtuple
 
     import joblib
     import numpy as np
+    import wandb
     from sklearn.ensemble import RandomForestClassifier  # noqa: F401
     from sklearn.metrics import accuracy_score, precision_score, recall_score
-    import wandb
-    import json
 
     def add_wandb_visualization(run, mlpipeline_ui_metadata_path):
         """NOTE: To use this, you must modify your component to have an output called `mlpipeline_ui_metadata_path` AND call `wandb.init` yourself inside that component.

tests/functional_tests/t0_main/kfp/kfp-pipeline-pytorch.py

@@ -2,10 +2,10 @@
 import random
 
 import kfp
-from kfp import components
 import kfp.dsl as dsl
-from kubernetes.client.models import V1EnvVar
 import wandb
+from kfp import components
+from kubernetes.client.models import V1EnvVar
 from wandb.integration.kfp import wandb_log
 from wandb_probe import wandb_probe_package
 

tests/functional_tests/t0_main/kfp/kfp-pipeline-simple.py

@@ -2,8 +2,8 @@
 import random
 
 import kfp
-from kfp import components
 import kfp.dsl as dsl
+from kfp import components
 from kubernetes.client.models import V1EnvVar
 from wandb.integration.kfp import wandb_log
 from wandb_probe import wandb_probe_package

tests/functional_tests/t0_main/kfp/kfp-pipeline-sklearn.py

@@ -3,8 +3,8 @@
 from typing import NamedTuple
 
 import kfp
-from kfp import components
 import kfp.dsl as dsl
+from kfp import components
 from kubernetes.client.models import V1EnvVar
 from wandb.integration.kfp import wandb_log
 from wandb_probe import wandb_probe_package

tests/functional_tests/t0_main/lightning/pl_base.py

@@ -1,5 +1,5 @@
-from pytorch_lightning import LightningModule
 import torch
+from pytorch_lightning import LightningModule
 from torch.utils.data import Dataset
 
 

tests/functional_tests/t0_main/lightning/t0_strategy_ddp.py

@@ -1,8 +1,8 @@
 #!/usr/bin/env python
 import os
 
-from pl_base import BoringModel, RandomDataset
 import pytorch_lightning as pl
+from pl_base import BoringModel, RandomDataset
 from pytorch_lightning.loggers import WandbLogger
 from torch.utils.data import DataLoader
 

tests/functional_tests/t0_main/lightning/train_gpu_ddp.py

@@ -3,11 +3,11 @@
 import os
 import pathlib
 
+import wandb
 from pl_base import BoringModel, RandomDataset
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import WandbLogger
 from torch.utils.data import DataLoader
-import wandb
 
 
 def main():

tests/functional_tests/t0_main/lightning/train_tpu_ddp.py

@@ -2,11 +2,11 @@
 
 import os
 
+import wandb
 from pl_base import BoringModel, RandomDataset
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import WandbLogger
 from torch.utils.data import DataLoader
-import wandb
 
 
 def main():

tests/functional_tests/t0_main/login/t1_timeout.py

@@ -5,7 +5,6 @@
 
 import wandb
 
-
 timeout = 4
 slop = 0.50
 tm_start = time.time()

tests/functional_tests/t0_main/login/t3_login_cloud_local_key.py

@@ -5,7 +5,6 @@
 import wandb
 import wandb.errors
 
-
 if __name__ == "__main__":
     # api_key starts with "local", but base_url points to cloud
     with pytest.raises(wandb.errors.UsageError) as e:

tests/functional_tests/t0_main/magic/t1_mnist_convnet.py

@@ -23,7 +23,6 @@
 import numpy as np
 from tensorflow import keras
 from tensorflow.keras import layers
-
 from wandb import magic  # noqa: F401
 
 # Make sure this is reproducible

tests/functional_tests/t0_main/metaflow/wandb-example-flow-decoboth.py

@@ -5,13 +5,12 @@
 import os
 
 import pandas as pd
+from metaflow import FlowSpec, Parameter, step
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score
 from sklearn.model_selection import train_test_split
 from wandb.integration.metaflow import wandb_log
 
-from metaflow import FlowSpec, Parameter, step
-
 os.environ["WANDB_SILENT"] = "true"
 os.environ["METAFLOW_USER"] = "test_user"
 

tests/functional_tests/t0_main/metaflow/wandb-example-flow-decoclass.py

@@ -5,13 +5,12 @@
 import os
 
 import pandas as pd
+from metaflow import FlowSpec, Parameter, step
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score
 from sklearn.model_selection import train_test_split
 from wandb.integration.metaflow import wandb_log
 
-from metaflow import FlowSpec, Parameter, step
-
 os.environ["WANDB_SILENT"] = "true"
 os.environ["METAFLOW_USER"] = "test_user"
 

tests/functional_tests/t0_main/metaflow/wandb-example-flow-decostep.py

@@ -5,13 +5,12 @@
 import os
 
 import pandas as pd
+from metaflow import FlowSpec, Parameter, step
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score
 from sklearn.model_selection import train_test_split
 from wandb.integration.metaflow import wandb_log
 
-from metaflow import FlowSpec, Parameter, step
-
 os.environ["WANDB_SILENT"] = "true"
 os.environ["METAFLOW_USER"] = "test_user"
 

tests/functional_tests/t0_main/metaflow/wandb-foreach-flow.py

@@ -5,16 +5,15 @@
 import os
 
 import pandas as pd
+from metaflow import FlowSpec, Parameter, step
 from sklearn.ensemble import (  # noqa: F401
-    RandomForestClassifier,
     GradientBoostingClassifier,
+    RandomForestClassifier,
 )
 from sklearn.metrics import accuracy_score
 from sklearn.model_selection import train_test_split
 from wandb.integration.metaflow import wandb_log
 
-from metaflow import FlowSpec, Parameter, step
-
 os.environ["WANDB_SILENT"] = "true"
 os.environ["METAFLOW_USER"] = "test_user"
 

tests/functional_tests/t0_main/metaflow/wandb-pytorch-flow.py

@@ -9,13 +9,12 @@
 import torch.nn as nn
 import torch.nn.functional as F
 import torch.optim as optim
+import wandb
+from metaflow import FlowSpec, Parameter, step
 from torch.optim.lr_scheduler import StepLR
 from torchvision import datasets, transforms
 from wandb.integration.metaflow import wandb_log
 
-import wandb
-from metaflow import FlowSpec, Parameter, step
-
 os.environ["WANDB_SILENT"] = "true"
 os.environ["METAFLOW_USER"] = "test_user"
 

tests/functional_tests/t0_main/mp/06-2-share-child-gt-step.py

@@ -3,9 +3,9 @@
 example usage of `run.log` with user provide step greater than the internal step"""
 
 
-from contextlib import redirect_stderr
 import io
 import multiprocessing as mp
+from contextlib import redirect_stderr
 
 import wandb
 import yea

tests/functional_tests/t0_main/mp/06-3-share-child-lt-step.py

@@ -2,9 +2,9 @@
 """Test parent and child processes sharing a run. Compare to a run in a single process.
 example usage of `run.log` with user provide step less than the internal step"""
 
-from contextlib import redirect_stderr
 import io
 import multiprocessing as mp
+from contextlib import redirect_stderr
 
 import wandb
 import yea

tests/functional_tests/t0_main/mp/13-synctb-gradienttape.py

@@ -10,7 +10,6 @@
 import tensorflow as tf
 import wandb
 
-
 parser = argparse.ArgumentParser()
 parser.add_argument("--log_dir", type=str, help="Where to store tensorboard files")
 args = parser.parse_args()

tests/functional_tests/t0_main/mp/20-2-thread-pool-executor.py

@@ -2,8 +2,8 @@
 """Simple example of using ThreadPoolExecutor with service.
     This example is base on issue https://wandb.atlassian.net/browse/WB-8733
 """
-from concurrent.futures import ThreadPoolExecutor
 import multiprocessing as mp
+from concurrent.futures import ThreadPoolExecutor
 
 import wandb
 import yea