Fix mutable default arguments

roboflow/adapters/rfapi.py

@@ -1,7 +1,7 @@
 import json
 import os
 import urllib
-from typing import Optional
+from typing import List, Optional
 
 import requests
 from requests.exceptions import RequestException
@@ -56,7 +56,7 @@ def upload_image(
     hosted_image: bool = False,
     split: str = "train",
     batch_name: str = DEFAULT_BATCH_NAME,
-    tag_names: list = [],
+    tag_names: Optional[List[str]] = None,
     sequence_number: Optional[int] = None,
     sequence_size: Optional[int] = None,
     **kwargs,
@@ -71,6 +71,8 @@ def upload_image(
     """
 
     coalesced_batch_name = batch_name or DEFAULT_BATCH_NAME
+    if tag_names is None:
+        tag_names = []
 
     # If image is not a hosted image
     if not hosted_image:

roboflow/core/project.py

@@ -256,13 +256,7 @@ def generate_version(self, settings):
 
     def train(
         self,
-        new_version_settings={
-            "preprocessing": {
-                "auto-orient": True,
-                "resize": {"width": 640, "height": 640, "format": "Stretch to"},
-            },
-            "augmentation": {},
-        },
+        new_version_settings: Optional[Dict] = None,
         speed=None,
         checkpoint=None,
         plot_in_notebook=False,
@@ -294,6 +288,15 @@ def train(
             >>> version.train()
         """  # noqa: E501 // docs
 
+        if new_version_settings is None:
+            new_version_settings = {
+                "preprocessing": {
+                    "auto-orient": True,
+                    "resize": {"width": 640, "height": 640, "format": "Stretch to"},
+                },
+                "augmentation": {},
+            }
+
         new_version = self.generate_version(settings=new_version_settings)
         new_version = self.version(new_version)
         new_model = new_version.train(speed=speed, checkpoint=checkpoint, plot_in_notebook=plot_in_notebook)
@@ -384,7 +387,7 @@ def upload(
         split: str = "train",
         num_retry_uploads: int = 0,
         batch_name: Optional[str] = None,
-        tag_names: list = [],
+        tag_names: Optional[List[str]] = None,
         is_prediction: bool = False,
         **kwargs,
     ):
@@ -413,6 +416,9 @@ def upload(
             >>> project.upload(image_path="YOUR_IMAGE.jpg")
         """  # noqa: E501 // docs
 
+        if tag_names is None:
+            tag_names = []
+
         is_hosted = image_path.startswith("http://") or image_path.startswith("https://")
 
         is_file = os.path.isfile(image_path) or is_hosted
@@ -476,13 +482,16 @@ def upload_image(
         split="train",
         num_retry_uploads=0,
         batch_name=None,
-        tag_names=[],
+        tag_names: Optional[List[str]] = None,
         sequence_number=None,
         sequence_size=None,
         **kwargs,
     ):
         project_url = self.id.rsplit("/")[1]
 
+        if tag_names is None:
+            tag_names = []
+
         t0 = time.time()
         upload_retry_attempts = 0
         retry = Retry(num_retry_uploads, ImageUploadError)
@@ -557,13 +566,15 @@ def single_upload(
         split="train",
         num_retry_uploads=0,
         batch_name=None,
-        tag_names=[],
+        tag_names: Optional[List[str]] = None,
         is_prediction: bool = False,
         annotation_overwrite=False,
         sequence_number=None,
         sequence_size=None,
         **kwargs,
     ):
+        if tag_names is None:
+            tag_names = []
         if image_path and image_id:
             raise Exception("You can't pass both image_id and image_path")
         if not (image_path or image_id):
@@ -641,7 +652,7 @@ def search(
         in_dataset: Optional[str] = None,
         batch: bool = False,
         batch_id: Optional[str] = None,
-        fields: list = ["id", "created", "name", "labels"],
+        fields: Optional[List[str]] = None,
     ):
         """
         Search for images in a project.
@@ -670,6 +681,9 @@ def search(
 
             >>> results = project.search(query="cat", limit=10)
         """  # noqa: E501 // docs
+        if fields is None:
+            fields = ["id", "created", "name", "labels"]
+
         payload: Dict[str, Union[str, int, List[str]]] = {}
 
         if like_image is not None:
@@ -719,7 +733,7 @@ def search_all(
         in_dataset: Optional[str] = None,
         batch: bool = False,
         batch_id: Optional[str] = None,
-        fields: list = ["id", "created"],
+        fields: Optional[List[str]] = None,
     ):
         """
         Create a paginated list of search results for use in searching the images in a project.
@@ -752,6 +766,9 @@ def search_all(
 
             >>>     print(result)
         """  # noqa: E501 // docs
+        if fields is None:
+            fields = ["id", "created"]
+
         while True:
             data = self.search(
                 like_image=like_image,

roboflow/core/workspace.py

@@ -5,7 +5,7 @@
 import json
 import os
 import sys
-from typing import Any, List
+from typing import Any, Dict, List, Optional
 
 import requests
 from PIL import Image
@@ -433,9 +433,9 @@ def active_learning(
         self,
         raw_data_location: str = "",
         raw_data_extension: str = "",
-        inference_endpoint: list = [],
+        inference_endpoint: Optional[List[str]] = None,
         upload_destination: str = "",
-        conditionals: dict = {},
+        conditionals: Optional[Dict] = None,
         use_localhost: bool = False,
         local_server="http://localhost:9001/",
     ) -> Any:
@@ -449,6 +449,11 @@ def active_learning(
             use_localhost: (bool) = determines if local http format used or remote endpoint
             local_server: (str) = local http address for inference server, use_localhost must be True for this to be used
         """  # noqa: E501 // docs
+        if inference_endpoint is None:
+            inference_endpoint = []
+        if conditionals is None:
+            conditionals = {}
+
         import numpy as np
 
         prediction_results = []

roboflow/models/inference.py

@@ -3,7 +3,7 @@
 import os
 import time
 import urllib
-from typing import Optional, Tuple
+from typing import List, Optional, Tuple
 from urllib.parse import urljoin
 
 import requests
@@ -137,7 +137,7 @@ def predict_video(
         self,
         video_path: str,
         fps: int = 5,
-        additional_models: list = [],
+        additional_models: Optional[List[str]] = None,
         prediction_type: str = "batch-video",
     ) -> Tuple[str, str, Optional[str]]:
         """
@@ -170,6 +170,9 @@ def predict_video(
         if fps > 120:
             raise Exception("FPS must be less than or equal to 120.")
 
+        if additional_models is None:
+            additional_models = []
+
         for model in additional_models:
             if model not in SUPPORTED_ADDITIONAL_MODELS:
                 raise Exception(f"Model {model} is not supported for video inference.")