Remove Async examples

api-reference/datasets/accessing-collection.mdx

@@ -11,16 +11,10 @@ information for it.
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 collections = dataset.collection("My-collection")
 ```
 
-```python Python (Async)
-collections = dataset.collection("My-collection")
-# just creates a collection object, no network calls are made
-# so no await required
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/datasets/accessing-dataset.mdx

@@ -8,12 +8,7 @@ Once you have listed all available datasets, you can access a specific dataset b
 
 <RequestExample>
 
-```python Python (Sync)
-dataset = datasets.open_data.copernicus.sentinel1_sar
-# or any other dataset available to you
-```
-
-```python Python (Async)
+```python Python
 dataset = datasets.open_data.copernicus.sentinel1_sar
 # or any other dataset available to you
 ```

api-reference/datasets/collection-info.mdx

@@ -8,14 +8,10 @@ You can access information such as availability and number of available datapoin
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 info = collection.info()
 ```
 
-```python Python (Async)
-info = await collection.info()
-```
-
 </RequestExample>
 
 ## Errors

api-reference/datasets/listing-collection.mdx

@@ -8,20 +8,13 @@ You can list all the collections available for a dataset using the `collections`
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 collections = dataset.collections(
     availability = True,
     count = False,
 )
 ```
 
-```python Python (Async)
-collections = await dataset.collections(
-    availability = True,
-    count = False,
-)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/datasets/listing-datasets.mdx

@@ -8,18 +8,11 @@ All available datasets can be listed using the datasets method on your Tilebox d
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 from tilebox.datasets import Client
 
 client = Client()
 datasets = client.datasets()
 ```
 
-```python Python (Async)
-from tilebox.datasets.aio import Client
-
-client = Client()
-datasets = await client.datasets()
-```
-
 </RequestExample>

api-reference/datasets/loading-data.mdx

@@ -14,7 +14,7 @@ Tilebox as time. Currently this includes either strings in ISO 8601 format or py
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 from datetime import datetime
 from tilebox.clients.core.data import TimeInterval
 
@@ -40,32 +40,6 @@ meta_data = collection.load(..., skip_data=True)
 first_50 = collection.load(meta_data.time[:50], skip_data=False)
 ```
 
-```python Python (Async)
-from datetime import datetime
-from tilebox.clients.core.data import TimeInterval
-
-# loading a specific time
-time = "2023-05-01 12:45:33.423"
-data = await collection.load(time)
-
-# loading a time interval
-interval = ("2023-05-01", "2023-08-01")
-data = await collection.load(interval, show_progress=True)
-
-# loading a time interval alternative equivalent to the above example
-interval = TimeInterval(
-    start = datetime(2023, 5, 1),
-    end = datetime(2023, 8, 1),
-    start_exclusive = False,
-    end_inclusive = False,
-)
-data = await collection.load(interval, show_progress=True)
-
-# loading with an iterable
-meta_data = await collection.load(..., skip_data=True)
-first_50 = await collection.load(meta_data.time[:50], skip_data=False)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/datasets/loading-datapoint.mdx

@@ -8,22 +8,14 @@ To load a single data point from a collection using its id, use the find method
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 datapoint_id = "0186d6b6-66cc-fcfd-91df-bbbff72499c3"
 data = collection.find(
     datapoint_id,
     skip_data = False,
 )
 ```
 
-```python Python (Async)
-datapoint_id = "0186d6b6-66cc-fcfd-91df-bbbff72499c3"
-data = await collection.find(
-    datapoint_id,
-    skip_data = False,
-)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/storage-providers/creating-storage-client.mdx

@@ -10,7 +10,7 @@ For a complete example look at the [Accessing Open Data](/datasets/open-data#sam
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 from pathlib import Path
 from tilebox.storage import ASFStorageClient
 # or UmbraStorageClient
@@ -22,18 +22,6 @@ storage_client = ASFStorageClient(
 )
 ```
 
-```python Python (Async)
-from pathlib import Path
-from tilebox.storage.aio import ASFStorageClient
-# or UmbraStorageClient
-# or CopernicusStorageClient
-
-storage_client = ASFStorageClient(
-    "ASF_USERNAME", "ASF_PASSWORD",
-    cache_directory=Path("./data")
-)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/storage-providers/deleting-cache.mdx

@@ -8,14 +8,9 @@ To delete the entire download cache you can use the `destroy_cache` method.
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 # careful, this will delete the entire cache directory
 storage_client.destroy_cache()
 ```
 
-```python Python (Async)
-# careful, this will delete the entire cache directory
-await storage_client.destroy_cache()
-```
-
 </RequestExample>

api-reference/storage-providers/deleting-products.mdx

@@ -8,16 +8,11 @@ To delete downloaded products or images again you can use the `delete` method.
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 storage_client.delete(path_to_data)
 storage_client.delete(path_to_image)
 ```
 
-```python Python (Async)
-await storage_client.delete(path_to_data)
-await storage_client.delete(path_to_image)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/storage-providers/direct-storage-access.mdx

@@ -9,7 +9,7 @@ It does not cache any files and expects an `output_dir` parameter for all downlo
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 from pathlib import Path
 from tilebox.storage import ASFStorageClient
 # or UmbraStorageClient
@@ -28,23 +28,4 @@ path_to_data = direct_storage_client.download(
 )
 ```
 
-```python Python (Async)
-from pathlib import Path
-from tilebox.storage.aio import ASFStorageClient
-# or UmbraStorageClient
-# or CopernicusStorageClient
-
-direct_storage_client = ASFStorageClient(
-    "ASF_USERNAME", "ASF_PASSWORD",
-    cache_directory=None
-)
-path_to_data = await direct_storage_client.download(
-    datapoint,
-    output_dir=Path("./data"),
-    verify=True,
-    extract=True,
-    show_progress=True,
-)
-```
-
 </RequestExample>

api-reference/storage-providers/downloading-products.mdx

@@ -8,7 +8,7 @@ You can download the product file for a given data point using the download meth
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 path_to_data = storage_client.download(
     datapoint,
     verify=True,
@@ -17,15 +17,6 @@ path_to_data = storage_client.download(
 )
 ```
 
-```python Python (Async)
-path_to_data = await storage_client.download(
-    datapoint,
-    verify=True,
-    extract=True,
-    show_progress=True,
-)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/storage-providers/downloading-quicklook-images.mdx

@@ -8,18 +8,12 @@ In case a storage provider offers quicklook images for products you can download
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 path_to_image = storage_client.download_quicklook(
     datapoint
 )
 ```
 
-```python Python (Async)
-path_to_image = await storage_client.download_quicklook(
-    datapoint
-)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/storage-providers/previewing-quicklook-images.mdx

@@ -8,20 +8,13 @@ In interactive environments you can also display quicklook images directly in th
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 image = storage_client.quicklook(
     datapoint
 )
 image  # display the image as the cell output
 ```
 
-```python Python (Async)
-image = await storage_client.quicklook(
-    datapoint
-)
-image  # display the image as the cell output
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/workflows/cache-access.mdx

@@ -10,8 +10,7 @@ Make sure to specify dependencies between tasks to ensure that certain cache key
 been written to.
 
 <RequestExample>
-
-```python Python (Sync)
+```python Python
 class WriterTask(Task):
     def execute(self, context: ExecutionContext):
         context.job_cache["some-key"] = b"my-value"
@@ -20,15 +19,4 @@ class ReaderTask(Task):
     def execute(self, context: ExecutionContext):
         data = context.job_cache["some-key"]
 ```
-
-```python Python (Async)
-class WriterTask(Task):
-    def execute(self, context: ExecutionContext):
-        context.job_cache["some-key"] = b"my-value"
-
-class ReaderTask(Task):
-    def execute(self, context: ExecutionContext):
-        data = context.job_cache["some-key"]
-```
-
 </RequestExample>

api-reference/workflows/cancelling-job.mdx

@@ -10,14 +10,10 @@ If after cancelling a job you want to resume it, you can [retry](/api-reference/
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 job_client.cancel(job)
 ```
 
-```python Python (Async)
-await job_client.cancel(job)
-```
-
 </RequestExample>
 
 ## Parameters

api-reference/workflows/cluster-management.mdx

@@ -8,11 +8,11 @@ You can use an instance of the `ClusterClient` to find, list, create, and delete
 
 <RequestExample>
 
-```python Python (Sync)
+```python Python
 from tilebox.workflows import Client
 
 client = Client()
-cluster_client = client.clusters()
+cluster_client = client.clusters()  
 
 # Find, List, Create and Delete clusters
 cluster = cluster_client.find("my-cluster-EdsdUozYprBJDL")  # cluster-slug
@@ -22,18 +22,4 @@ cluster = cluster_client.create("My Cluster")
 cluster_client.delete("my-cluster-EdsdUozYprBJDL")
 ```
 
-```python Python (Async)
-from tilebox.workflows import Client
-
-client = Client()
-cluster_client = await client.clusters()
-
-# Find, List, Create and Delete clusters
-cluster = await cluster_client.find("my-cluster-EdsdUozYprBJDL")  # cluster-slug
-all_clusters = await cluster_client.all()
-# will generate a new cluster slug from the provided name
-cluster = await cluster_client.create("My Cluster")
-await cluster_client.delete("my-cluster-EdsdUozYprBJDL")
-```
-
 </RequestExample>