From 1dd221103b426b6eda753dfc8b903576d11acf1a Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 9 Mar 2026 22:45:46 +0000
Subject: [PATCH 1/2] Initial plan


From 70c2f2393889b10e7ad7497bd828f85b6ab7fabe Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 9 Mar 2026 22:51:53 +0000
Subject: [PATCH 2/2] Improve documentation: clarify document vs payload
 structure in insert.py and README.md

Co-authored-by: sgbaird <45469701+sgbaird@users.noreply.github.com>
---
 README.md | 34 ++++++++++++++++++++++++----------
 insert.py | 34 ++++++++++++++++++++++++----------
 2 files changed, 48 insertions(+), 20 deletions(-)

diff --git a/README.md b/README.md
index 381a909..0d06a06 100644
--- a/README.md
+++ b/README.md
@@ -108,20 +108,34 @@ https://github.com/ACC-HelloWorld/5-data-logging-sgbaird/settings/secrets/codesp
 
 ## Insert
 
-Update [`insert.py`](./insert.py) to iteratively run color experiments and insert the data into your MongoDB database. You will need to:
+Update [`insert.py`](./insert.py) to iteratively run color experiments and upload the data to your MongoDB database via the AWS Lambda function. You will need to:
 
-1. Connect to MongoDB using the provided URI
-2. Run each experiment in `payload_dicts` using the `run_color_experiment()` function
-3. Insert the results into the database
+1. Import `urequests` and `json` (MicroPython equivalents of `requests` and `json`)
+2. Loop through each entry in the `documents` list
+3. Run each experiment using the `run_color_experiment()` function with the R, G, B values from the entry's `"command"` dictionary
+4. Build a **document** dictionary containing the command, sensor data, experiment ID, and your course ID
+5. Wrap the document in a **payload** dictionary that tells the Lambda function which database and collection to use (see the `test_lambda_function_url` function in [`mongodb_credentials_test.py`](./mongodb_credentials_test.py) for reference)
+6. POST the payload to the Lambda function URL
 
-The document structure should be of the form:
+> **Important: document vs. payload**
+> The *document* is the data you want to store in MongoDB (command, sensor data, experiment ID, course ID). The *payload* wraps the document with metadata (database name, collection name) so the Lambda function knows where to insert it.
+
+The **document** (what gets stored in MongoDB) should be of the form:
+```python
+{
+    "command": {"R": ..., "G": ..., "B": ...},
+    "sensor_data": {"ch410": ..., "ch440": ..., ..., "ch670": ...},
+    "experiment_id": "...",
+    "course_id": "...",
+}
+```
+
+The **payload** (what gets sent to the Lambda function) should be of the form:
 ```python
 {
-"command": {"R": ..., "G": ..., "B": ...},
-"sensor_data": {"ch410": ..., "ch440": ..., ..., "ch670": ...},
-"experiment_id": "...",
-"course_id": "...",
-"timestamp": "..."
+    "database": DATABASE_NAME,
+    "collection": COLLECTION_NAME,
+    "document": <your document from above>,
 }
 ```
 
diff --git a/insert.py b/insert.py
index 835b52c..83adb0d 100644
--- a/insert.py
+++ b/insert.py
@@ -10,7 +10,7 @@
     LAMBDA_FUNCTION_URL,
 )
 
-# TODO: other imports here
+# TODO: import urequests and json here
 ...
 
 # Connect to WiFi
@@ -55,13 +55,27 @@ def run_color_experiment(R, G, B):
 ]
 # fmt: on
 
-# TODO: for each of the commands above, run the corresponding dummy color
-# experiment and upload a document containing your course ID (use `course_id` as
-# the key), the original command, the experiment ID, and the sensor data to your
-# MongoDB collection. The dictionary should be of the form:
-# {
-#     "command": {"R": ..., "G": ..., "B": ...},
-#     "sensor_data": {"ch410": ..., "ch440": ..., ..., "ch670": ...},
-#     "experiment_id": "...",
-# }
+# TODO: for each document, do the following steps:
+# 1. Run the color experiment using `run_color_experiment()` with the R, G, B
+#    values from the document's "command" dictionary.
+# 2. Build a document dictionary containing the following keys:
+#    - "command": the original command (e.g., {"R": ..., "G": ..., "B": ...})
+#    - "sensor_data": the result from `run_color_experiment()`
+#    - "experiment_id": the experiment ID from the original document
+#    - "course_id": use the `COURSE_ID` variable from `my_secrets`
+# 3. Wrap the document in a payload dictionary for the Lambda function. The
+#    payload is NOT the same as the document—it includes metadata about where
+#    to store the document. See `test_lambda_function_url` in
+#    `mongodb_credentials_test.py` for reference. The payload should be:
+#    {
+#        "database": DATABASE_NAME,
+#        "collection": COLLECTION_NAME,
+#        "document": <your document from step 2>,
+#    }
+# 4. POST the payload to the Lambda function URL using `urequests.post()`:
+#    response = urequests.post(
+#        LAMBDA_FUNCTION_URL,
+#        headers={"Content-Type": "application/json"},
+#        data=json.dumps(payload),
+#    )
 ...