MongoDB VS Code Bug Bash

For the purposes of this bug bash, we will focus on testing the following key features of the VS Code Extension:

Query Editor
CRUD Documents
View documents table/treeview/json
Download data from query
Upload query

Please report any bugs found during testing here.

Prerequisite

To begin, if you do not already have a sample Cosmos DB for MongoDB (vCore) account, create one using the Azure portal

How to install the extension

To manually install the Visual Studio Code (VS Code) extension from a VSIX file, you can do the following: Download the latest VS Code Extension Release: vscode-cosmosdb-0.23.1-alpha-PrPr-25.10.2024

Click the Extensions icon at the bottom of the Activity Bar
Click the More button in the top right corner of the Extensions view
Select Install from VSIX
Select the VSIX file in the file browser or in your downloads folder.
Click Install
Click Reload to activate the extension

Setup Instructions

1. Install the Azure Cosmos DB for MongoDB vCore Extension

Ensure you have the Azure Cosmos DB for MongoDB vCore extension installed in your Visual Studio Code environment. This extension is crucial for managing and interacting with your MongoDB vCore clusters seamlessly.

2. Sign In and Select Your Azure Subscription

After signing in to Azure, choose the subscription associated with your MongoDB vCore cluster. This step links your VS Code environment with your Azure resources.

3. Explore Your Resources in the Azure Tree View

Navigate to the Azure Resources section in VS Code. Locate the item labeled Azure Cosmos DB for MongoDB (vCore) and expand it to reveal your available clusters and databases.

4. Select and Access Your MongoDB vCore Cluster

Identify your cluster in the expanded tree view and select it. This will open the details and management options for your cluster.

5. Authenticate with Your Admin Password

When prompted, enter the admin password for your MongoDB vCore cluster. This step is necessary to authenticate your session and securely manage your database.

Testing Scenarios

1. Create a New Database and Collection Using the Extension

Scenario: Use the MongoDB extension in Azure to create a new database named RestaurantDB and a collection named Restaurants.
Action:
1. Open the MongoDB extension.
2. Create RestaurantDB.
3. Add a collection named Restaurants.
4. Insert sample data into the Restaurants collection. Data can be found in this repo.

2. Find All Restaurants That Have `is_open = 1`

Scenario: Query to fetch all open restaurants.
Action: Enter the following command in the Filter textbox:
```
{ "is_open": 1 }
```
Expected Result: A list of open restaurants.

3. Using the Table View, Give Monday's Working Hours for Open Restaurants

Scenario: Display the names of open restaurants and their Monday working hours in a table view.
Action: You can filter open restaurants with the following command:
```
{ "is_open": 1 }
```
Task: Capture a screenshot of the table view showing the names and Monday hours. You can view the hours by double-clicking on the hours of operation field. To return to the root level, click the Root level button at the bottom left of the screen.

4. Edit the Time for a Specific Entry and Share the Screenshot

Scenario: Modify the Monday working hours for one of the open restaurants.

Action: Update the entry using this filter:

{ "name": "Shalhoob's Funk Zone Patio" }

Task: Capture and share a screenshot of the updated entry in the table view, with the new name "Cosmic Restaurant."

5. Delete One Entry That Has `is_open = 0`

Scenario: Remove a closed restaurant named "Minnow Cafe."
Action: Use the following command to find the entry:
```
{ "is_open": 0 }
```
Expected Result: Confirmation of deletion.

6. Add a New Entry

Scenario: Insert a new restaurant entry into the collection.

Action:

{
  "business_id": "abc123def456ghi789jkl",
  "name": "Golden Gate Catering Services",
  "address": "123 Culinary Ave",
  "city": "San Francisco",
  "state": "CA",
  "stars": 4.5,
  "review_count": 15,
  "is_open": 1,
  "categories": "Caterers, Event Planning & Services, Food, Professional Services",
  "hours": {
    "Monday": "8:0-20:0",
    "Tuesday": "8:0-20:0",
    "Wednesday": "8:0-20:0",
    "Thursday": "8:0-20:0",
    "Friday": "8:0-20:0",
    "Saturday": "10:0-18:0",
    "Sunday": "Closed"
  },
  "location": {
    "type": "Point",
    "coordinates": [ -122.419416, 37.774929 ]
  },
  "description": "### Business Summary\n\nGolden Gate Catering Services, based in San Francisco, CA, is renowned for delivering exquisite culinary experiences for a variety of events. ..."
}

Expected Result: The new entry should appear in the collection.

7. Export Query Results with `is_open = 0`

Scenario: Export all documents where is_open = 0.
Action: Use the following command to filter the results:
```
{ "is_open": 0 }
```
Task: Export the results to a JSON file and count the number of documents in the file.
Expected Result: A new file containing all documents with is_open = 0, along with a document count summary.

SandraAhlgrimm/mongo-vs-code-bug-bash