From ee7d4a1dcf1c53247cbb95e9ef74b55aca71c83d Mon Sep 17 00:00:00 2001
From: Avril Aysha <68642378+avriiil@users.noreply.github.com>
Date: Wed, 12 Jun 2024 15:45:26 +0100
Subject: [PATCH] add aws/config note to load-table docs

---
 docs/usage/loading-table.md | 26 ++++++++++++++------------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/docs/usage/loading-table.md b/docs/usage/loading-table.md
index e8d817c6e5..5c5b8b49c3 100644
--- a/docs/usage/loading-table.md
+++ b/docs/usage/loading-table.md
@@ -16,7 +16,7 @@ options](https://docs.rs/object_store/latest/object_store/azure/enum.AzureConfig
 [gcs
 options](https://docs.rs/object_store/latest/object_store/gcp/enum.GoogleConfigKey.html#variants).
 
-``` python
+```python
 >>> storage_options = {"AWS_ACCESS_KEY_ID": "THE_AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY":"THE_AWS_SECRET_ACCESS_KEY"}
 >>> dt = DeltaTable("../rust/tests/data/delta-0.2.0", storage_options=storage_options)
 ```
@@ -28,25 +28,27 @@ properties.
 
 **S3**:
 
-> -   s3://\<bucket\>/\<path\>
-> -   s3a://\<bucket\>/\<path\>
+> - s3://\<bucket\>/\<path\>
+> - s3a://\<bucket\>/\<path\>
+
+Note that `delta-rs` does not read credentials from a local `.aws/config` or `.aws/creds` file. Credentials can be accessed from environment variables, ec2 metadata, profiles or web identity. You can also pass credentials to `storage_options` using `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
 
 **Azure**:
 
-> -   az://\<container\>/\<path\>
-> -   adl://\<container\>/\<path\>
-> -   abfs://\<container\>/\<path\>
+> - az://\<container\>/\<path\>
+> - adl://\<container\>/\<path\>
+> - abfs://\<container\>/\<path\>
 
 **GCS**:
 
-> -   gs://\<bucket\>/\<path\>
+> - gs://\<bucket\>/\<path\>
 
 Alternatively, if you have a data catalog you can load it by reference
 to a database and table name. Currently only AWS Glue is supported.
 
 For AWS Glue catalog, use AWS environment variables to authenticate.
 
-``` python
+```python
 >>> from deltalake import DeltaTable
 >>> from deltalake import DataCatalog
 >>> database_name = "simple_database"
@@ -66,7 +68,7 @@ customize the storage interface used for reading the bulk data.
 
 `deltalake` will work with any storage compliant with `pyarrow.fs.FileSystem`, however the root of the filesystem has to be adjusted to point at the root of the Delta table. We can achieve this by wrapping the custom filesystem into a `pyarrow.fs.SubTreeFileSystem`.
 
-``` python
+```python
 import pyarrow.fs as fs
 from deltalake import DeltaTable
 
@@ -81,7 +83,7 @@ When using the pyarrow factory method for file systems, the normalized
 path is provided on creation. In case of S3 this would look something
 like:
 
-``` python
+```python
 import pyarrow.fs as fs
 from deltalake import DeltaTable
 
@@ -98,14 +100,14 @@ ds = dt.to_pyarrow_dataset(filesystem=filesystem)
 To load previous table states, you can provide the version number you
 wish to load:
 
-``` python
+```python
 >>> dt = DeltaTable("../rust/tests/data/simple_table", version=2)
 ```
 
 Once you\'ve loaded a table, you can also change versions using either a
 version number or datetime string:
 
-``` python
+```python
 >>> dt.load_version(1)
 >>> dt.load_with_datetime("2021-11-04 00:05:23.283+00:00")
 ```