In this section, we’ll learn how to run two versions of an autocorrect app called Letter Inventory: a console-based version and a web-based version. We won’t be writing any code for this demo!
First, download the nifty-web-apps-python repository. Unzip the contents.
Run the console app with python3 inventory.py. When prompted for a query, try entering any word such as “occurence”. If everything goes well, you should see the following output appear.
Query: occurence
occurrence
concrete
concert
concern
concerned
conference
cancer
soccer
ec
once
Query:
Run the web app with python3 server.py. In a web browser, navigate the following address: localhost:8000.
Try entering some text in the input text field and see how the app responds. Then, try clicking on the ⚡ (lightning bolt) icon and see what happens.
When you’re done demoing the web app, stop the Python terminal process with Ctrl+C.
inventory.py with server.pyWhen we ran the console app, Python executed the __main__ code at the bottom of inventory.py. When we ran the web app, Python executed the __main__ code in server.py.
Later, we’ll adapt this server.py file to run a different app called Random Sentence Generator. To help make the connections between the console app and the web app, notice how we’ve marked up matching code snippets: both server.py and inventory.py contain a comment for Step 1 and a comment for Step 2. These matching code snippets represent the logic that we’ll need to change for each assignment.
Step 1: Return the top 10 most similar optionsWhile the server.py file adds each option to a running result list, the inventory.py console app just prints out the result to the screen. This difference is important. server.py needs to self.send the result back to the web browser as a JSON string:
{"items": ["occurrence", "concrete", "concert", "concern", ...]}
Step 2: Return a random string from the datasetIn addition to entering text directly into the input box, the user can also touch the ⚡ (lightning bolt) icon to randomly fill the input box with a word from the dataset. This is feature is only present in the web app server.py. Like step 1, step 2 also needs to self.send the result back to the web browser as a JSON string:
{"s": "tripadvisor"}