Over the last few days, I've been working on serializing and deserializing our wiki pages in terms of JSON data. In other words, how a page stored in a server directory is decoded by a wiki client and re-encoded (serialized) as JSON after changes. commit
How could we summarize our conversation here?
During our conversation on "Decode JSON in Elm," we discussed various aspects of decoding JSON data in the Elm programming language. Here's a summary of the key points we covered: (ChatGPT May 24 Version)
1. JSON Decoding Basics:
* We explored the Json.Decode module in Elm, which provides functions for decoding JSON data. * The Json.Decode.decodeValue function is used to decode a JSON string into an Elm value. * Elm provides various decoding functions such as string, int, float, bool, null, list, array, object, and more.
2. Decoding Custom Types:
* We discussed how to decode custom types by defining decoders for each field in the JSON object. * Decoding custom types involves using functions like field, at, andThen, and combining them with other decoders.
3. Handling Optional Fields:
* We explored techniques for handling optional fields in JSON data. * Elm's Maybe type allows us to represent optional values, and we can use nullable or andThen with Maybe to handle optional fields.
4. Error Handling:
* We talked about error handling during JSON decoding. * Elm's Result type is often used to handle decoding errors, where Ok represents successful decoding and Err represents decoding errors.
5. Encoding to JSON:
* We briefly touched on encoding Elm values to JSON using the Json.Encode module. * Functions like Encode.object, Encode.list, and Encode.string can be used to encode Elm values as JSON.
Throughout the conversation, we worked on specific examples and discussed different approaches to achieve the desired JSON encoding and decoding behavior.
Please note that this is just a summary, and there might be additional details that we discussed in our conversation. If you have any further questions or need more specific information, feel free to ask!
The challenges associated with making automation a 'team player' in a joint human-agent activity are discussed. Joint activity is defined as an extended set of actions that are carried out by an ensemble of people coordinating with each other. To carry out joint activity, each party effectively enters into a Basic Compact, an agreement to facilitate coordination, work toward shared goals, and prevent breakdowns in team coordination. Effective coordination requires establishing and maintaining common ground and an intelligent agent must fulfil the require