feat: Update docs, examples, tests to use method-based API

docs/authentication.md

@@ -94,28 +94,26 @@ Refer to [`obstore.auth.google`](api/auth/google.md).
 You can use the [`AzureCredentialProvider`][obstore.auth.azure.AzureCredentialProvider] to use [`azure.identity`][] to handle credentials.
 
 ```py
-import obstore as obs
 from obstore.auth.azure import AzureCredentialProvider
 from obstore.store import AzureStore
 
 credential_provider = AzureAsyncCredentialProvider(credential=...)
 store = AzureStore("container", credential_provider=credential_provider)
-print(obs.list(store).collect())
+print(store.list().collect())
 ```
 
 Alternatively, you can use [`AzureAsyncCredentialProvider`][obstore.auth.azure.AzureAsyncCredentialProvider] with the async API:
 
 ```py
 import asyncio
-import obstore as obs
 from obstore.auth.azure import AzureCredentialProvider
 from obstore.store import AzureStore
 
 credential_provider = AzureAsyncCredentialProvider(credential=...)
 store = AzureStore("container", credential_provider=credential_provider)
 
 async def fetch_blobs():
-    blobs = await obs.list(store).collect_async()
+    blobs = await store.list().collect_async()
     print(blobs)
 
 asyncio.run(fetch_blobs())

docs/cookbook.md

@@ -5,8 +5,6 @@
 Use the [`obstore.list`][] method.
 
 ```py
-import obstore as obs
-
 store = ... # store of your choice
 
 # Recursively list all files below the 'data' path.
@@ -15,7 +13,7 @@ store = ... # store of your choice
 prefix = "data"
 
 # Get a stream of metadata objects:
-list_stream = obs.list(store, prefix)
+list_stream = store.list(prefix)
 
 # Print info
 for batch in list_stream:
@@ -32,12 +30,10 @@ Instead, you may consider passing `return_arrow=True` to [`obstore.list`][] to r
 This Arrow integration requires the [`arro3-core` dependency](https://kylebarron.dev/arro3/latest/), a lightweight Arrow implementation. You can pass the emitted `RecordBatch` to [`pyarrow`](https://arrow.apache.org/docs/python/index.html) (zero-copy) by passing it to [`pyarrow.record_batch`][] or to [`polars`](https://pola.rs/) (also zero-copy) by passing it to `polars.DataFrame`.
 
 ```py
-import obstore as obs
-
 store = ... # store of your choice
 
 # Get a stream of Arrow RecordBatches of metadata
-list_stream = obs.list(store, prefix="data", return_arrow=True)
+list_stream = store.list(prefix="data", return_arrow=True)
 for record_batch in list_stream:
     # Perform zero-copy conversion to your arrow-backed library of choice
     #
@@ -58,13 +54,12 @@ for record_batch in list_stream:
 Here's a working example with the [`sentinel-cogs` bucket](https://registry.opendata.aws/sentinel-2-l2a-cogs/) in AWS Open Data:
 
 ```py
-import obstore as obs
 import pandas as pd
 import pyarrow as pa
 from obstore.store import S3Store
 
 store = S3Store("sentinel-cogs", region="us-west-2", skip_signature=True)
-stream = obs.list(store, chunk_size=20, return_arrow=True)
+stream = store.list(chunk_size=20, return_arrow=True)
 
 for record_batch in stream:
     # Convert to pyarrow (zero-copy), then to pandas for easy export to a
@@ -86,30 +81,28 @@ The Arrow record batch looks like the following:
 
 ## Fetch objects
 
-Use the [`obstore.get`][] function to fetch data bytes from remote storage or files in the local filesystem.
+Use the `get` method to fetch data bytes from remote storage or files in the local filesystem.
 
 ```py
-import obstore as obs
-
 store = ... # store of your choice
 
 # Retrieve a specific file
 path = "data/file01.parquet"
 
 # Fetch just the file metadata
-meta = obs.head(store, path)
+meta = store.head(path)
 print(meta)
 
 # Fetch the object including metadata
-result = obs.get(store, path)
+result = store.get(path)
 assert result.meta == meta
 
 # Buffer the entire object in memory
 buffer = result.bytes()
 assert len(buffer) == meta.size
 
 # Alternatively stream the bytes from object storage
-stream = obs.get(store, path).stream()
+stream = store.get(path).stream()
 
 # We can now iterate over the stream
 total_buffer_len = 0
@@ -125,9 +118,7 @@ Using the response as an iterator ensures that we don't buffer the entire file
 into memory.
 
 ```py
-import obstore as obs
-
-resp = obs.get(store, path)
+resp = store.get(path)
 
 with open("output/file", "wb") as f:
     for chunk in resp:
@@ -139,65 +130,56 @@ with open("output/file", "wb") as f:
 Use the [`obstore.put`][] function to atomically write data. `obstore.put` will automatically use [multipart uploads](https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html) for large input data.
 
 ```py
-import obstore as obs
-
 store = ... # store of your choice
 path = "data/file1"
 content = b"hello"
-obs.put(store, path, content)
+store.put(path, content)
 ```
 
 You can also upload local files:
 
 ```py
 from pathlib import Path
-import obstore as obs
 
 store = ... # store of your choice
 path = "data/file1"
 content = Path("path/to/local/file")
-obs.put(store, path, content)
+store.put(path, content)
 ```
 
 Or file-like objects:
 
 ```py
-import obstore as obs
-
 store = ... # store of your choice
 path = "data/file1"
 with open("path/to/local/file", "rb") as content:
-    obs.put(store, path, content)
+    store.put(path, content)
 ```
 
 Or iterables:
 
 ```py
-import obstore as obs
-
 def bytes_iter():
     for i in range(5):
         yield b"foo"
 
 store = ... # store of your choice
 path = "data/file1"
 content = bytes_iter()
-obs.put(store, path, content)
+store.put(path, content)
 ```
 
 Or async iterables:
 
 ```py
-import obstore as obs
-
 async def bytes_stream():
     for i in range(5):
         yield b"foo"
 
 store = ... # store of your choice
 path = "data/file1"
 content = bytes_stream()
-obs.put(store, path, content)
+store.put(path, content)
 ```
 
 ## Copy objects from one store to another
@@ -209,16 +191,14 @@ Perhaps you have data in one store, say AWS S3, that you need to copy to another
 Download the file, collect its bytes in memory, then upload it. Note that this will materialize the entire file in memory.
 
 ```py
-import obstore as obs
-
 store1 = ... # store of your choice
 store2 = ... # store of your choice
 
 path1 = "data/file1"
 path2 = "data/file2"
 
-buffer = obs.get(store1, path1).bytes()
-obs.put(store2, path2, buffer)
+buffer = store1.get(path1).bytes()
+store2.put(path2, buffer)
 ```
 
 ### Local file
@@ -227,22 +207,21 @@ First download the file to disk, then upload it.
 
 ```py
 from pathlib import Path
-import obstore as obs
 
 store1 = ... # store of your choice
 store2 = ... # store of your choice
 
 path1 = "data/file1"
 path2 = "data/file2"
 
-resp = obs.get(store1, path1)
+resp = store1.get(path1)
 
 with open("temporary_file", "wb") as f:
     for chunk in resp:
         f.write(chunk)
 
 # Upload the path
-obs.put(store2, path2, Path("temporary_file"))
+store2.put(path2, Path("temporary_file"))
 ```
 
 ### Streaming
@@ -254,30 +233,27 @@ It's easy to **stream** a download from one store directly as the upload to anot
     Using the async API is currently required to use streaming copies.
 
 ```py
-import obstore as obs
-
 store1 = ... # store of your choice
 store2 = ... # store of your choice
 
 path1 = "data/file1"
 path2 = "data/file2"
 
 # This only constructs the stream, it doesn't materialize the data in memory
-resp = await obs.get_async(store1, path1)
+resp = await store1.get_async(path1)
 # A streaming upload is created to copy the file to path2
-await obs.put_async(store2, path2, resp)
+await store2.put_async(path2, resp)
 ```
 
 Or, by customizing the chunk size and the upload concurrency you can control memory overhead.
 
 ```py
-resp = await obs.get_async(store1, path1)
+resp = await store1.get_async(path1)
 chunk_size = 5 * 1024 * 1024 # 5MB
 stream = resp.stream(min_chunk_size=chunk_size)
 
 # A streaming upload is created to copy the file to path2
-await obs.put_async(
-    store2,
+await store2.put_async(
     path2,
     stream,
     chunk_size=chunk_size,

docs/examples/fastapi.md

@@ -18,7 +18,6 @@ First, import `fastapi` and `obstore` and create the FastAPI application.
 from fastapi import FastAPI
 from fastapi.responses import StreamingResponse
 
-import obstore as obs
 from obstore.store import HTTPStore, S3Store
 
 app = FastAPI()
@@ -39,7 +38,7 @@ async def download_example() -> StreamingResponse:
 
     # Make the request. This only begins the download; it does not wait for the
     # download to finish.
-    resp = await obs.get_async(store, path)
+    resp = await store.get_async(path)
     return StreamingResponse(resp)
 ```
 
@@ -56,7 +55,7 @@ async def large_example() -> StreamingResponse:
 
     # Note: for large file downloads you may need to increase the timeout in
     # the client configuration
-    resp = await obs.get_async(store, path)
+    resp = await store.get_async(path)
 
     # Example: Ensure the stream returns at least 5MB of data in each chunk.
     return StreamingResponse(resp.stream(min_chunk_size=5 * 1024 * 1024))

docs/examples/minio.md

@@ -20,7 +20,6 @@ docker run -p 9000:9000 -p 9001:9001 \
 Now we can create an `S3Store` to interact with minio:
 
 ```py
-import obstore as obs
 from obstore.store import S3Store
 
 store = S3Store(
@@ -33,20 +32,20 @@ store = S3Store(
 )
 
 # Add files
-obs.put(store, "a.txt", b"foo")
-obs.put(store, "b.txt", b"bar")
-obs.put(store, "c/d.txt", b"baz")
+store.put("a.txt", b"foo")
+store.put("b.txt", b"bar")
+store.put("c/d.txt", b"baz")
 
 # List files
-files = obs.list(store).collect()
+files = store.list().collect()
 print(files)
 
 # Download a file
-resp = obs.get(store, "a.txt")
+resp = store.get("a.txt")
 print(resp.bytes())
 
 # Delete a file
-obs.delete(store, "a.txt")
+store.delete("a.txt")
 ```
 
 There's a [full example](https://github.com/developmentseed/obstore/tree/main/examples/minio) in the obstore repository.

docs/getting-started.md

@@ -76,12 +76,12 @@ File-like object support is also provided:
 ### Example
 
 ```py
-import obstore as obs
+from obstore.store import MemoryStore
 
-store = obs.store.MemoryStore()
+store = MemoryStore()
 
-obs.put(store, "file.txt", b"hello world!")
-response = obs.get(store, "file.txt")
+store.put("file.txt", b"hello world!")
+response = store.get("file.txt")
 response.meta
 # {'path': 'file.txt',
 #  'last_modified': datetime.datetime(2024, 10, 21, 16, 19, 45, 102620, tzinfo=datetime.timezone.utc),
@@ -90,22 +90,22 @@ response.meta
 #  'version': None}
 assert response.bytes() == b"hello world!"
 
-byte_range = obs.get_range(store, "file.txt", start=0, end=5)
+byte_range = store.get_range("file.txt", start=0, end=5)
 assert byte_range == b"hello"
 
-obs.copy(store, "file.txt", "other.txt")
-assert obs.get(store, "other.txt").bytes() == b"hello world!"
+store.copy("file.txt", "other.txt")
+assert store.get("other.txt").bytes() == b"hello world!"
 ```
 
 All of these methods also have `async` counterparts, suffixed with `_async`.
 
 ```py
-import obstore as obs
+from obstore.store import MemoryStore
 
-store = obs.store.MemoryStore()
+store = MemoryStore()
 
-await obs.put_async(store, "file.txt", b"hello world!")
-response = await obs.get_async(store, "file.txt")
+await store.put_async("file.txt", b"hello world!")
+response = await store.get_async("file.txt")
 response.meta
 # {'path': 'file.txt',
 #  'last_modified': datetime.datetime(2024, 10, 21, 16, 20, 36, 477418, tzinfo=datetime.timezone.utc),
@@ -114,10 +114,10 @@ response.meta
 #  'version': None}
 assert await response.bytes_async() == b"hello world!"
 
-byte_range = await obs.get_range_async(store, "file.txt", start=0, end=5)
+byte_range = await store.get_range_async("file.txt", start=0, end=5)
 assert byte_range == b"hello"
 
-await obs.copy_async(store, "file.txt", "other.txt")
-resp = await obs.get_async(store, "other.txt")
+await store.copy_async("file.txt", "other.txt")
+resp = await store.get_async("other.txt")
 assert await resp.bytes_async() == b"hello world!"
 ```