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Week_02.md

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Guidance

Answer the following questions considering the learning outcomes for

Make sure to record evidence of your processes. You can use code snippets, screenshots or any other material to support your answers.

Do not fill in the feedback section. The Founders and Coders team will update this with feedback on your progress.

Assessment

1. Show evidence of some of the learning outcomes you have achieved this week.

Using npm to Manage Dependencies

  • I initialised a Node.js project using npm init -y and installed the figlet module to generate ASCII art. Below is the code snippet from my script, asciiArtGenerator.js, which successfully generated ASCII art and stored it in asciiArt.txt:

    const figlet = require('figlet');
const fs = require('fs');

figlet('Hello World', (err, data) => {
  if (err) {
    console.log('Something went wrong...');
    return;
  }
  fs.writeFileSync('asciiArt.txt', data);
});

Setting up an Express Server

  • I created a basic Express HTTP server that handles GET requests and responds with HTML. Here’s the relevant code snippet:

    const express = require('express');
const server = express();

server.get('/', (req, res) => {
  res.send('<h1>Hello from Express</h1>');
});

server.listen(3000, () => {
  console.log('Server running on http://localhost:3000');
});

Understanding Asynchronous JavaScript

  • I implemented asynchronous functions using async/await, particularly for handling API calls in my Discord bot project. Here’s a simplified example of handling OpenAI responses:

    async function handleOpenAIResponse(message) {
  try {
    const reply = await getOpenAIResponse(message.content);
    await message.channel.send(reply);
  } catch (error) {
    console.error("Error with OpenAI:", error);
    await message.channel.send("There was an error processing your request.");
  }
}

OpenAI Chat Integration

  • I integrated OpenAI's API into my Discord bot to generate dynamic responses based on user inputs. Here’s a concise version of the code demonstrating this integration:

    const completion = await openai.createChatCompletion({
  model: "gpt-3.5-turbo",
  messages: [{ role: "user", content: userInput }],
});

return completion.choices[0].message.content;

Error Handling and Secure Environment Configuration

  • I ensured secure handling of sensitive data using environment variables and implemented error handling across the bot's functions. Here's a snippet showing secure configuration and error handling:

    import dotenv from 'dotenv';
dotenv.config();

async function getOpenAIResponse(messageToAI) {
  try {
    const completion = await openai.createChatCompletion({...});
    return completion.choices[0].message.content;
  } catch (error) {
    console.error("Error with OpenAI API:", error);
    return "Error processing your request.";
  }
}

  • Project Work Code Example: Below is an example from the project code I worked on, which implements Discord’s message components like buttons and handles interactions:

    import { Events, ActionRowBuilder, ButtonBuilder, ButtonStyle } from "discord.js";

export default {
  name: Events.InteractionCreate,

  async execute(interaction) {
    if (interaction.isButton()) {
      try {
        if (interaction.customId === "confirm") {
          await interaction.update({ content: "Action confirmed!", components: [] });
        } else if (interaction.customId === "cancel") {
          await interaction.update({ content: "Action cancelled.", components: [] });
        }
      } catch (error) {
        console.error("Interaction update failed:", error);
      }
    }
  },
};

Project Management

  • To manage the project efficiently, my team and I used a task board and timeline to break down tasks, prioritise them, and track progress(divided into "To Do," "In Progress," and "Done" columns). This structured approach ensured steady progress and timely completion of the project tasks. Additionally, the timeline helped in coordinating tasks with deadlines, ensuring that everything was completed within the set timeframe.

2. Show an example of some of the learning outcomes you have struggled with and/or would like to revisit.

Understanding HTTP and Middleware in Express

  • I struggled with setting up middleware and handling HTTP POST requests during the Work09_NodeAndExpress_YourName workshop. Below is the key part of the code where I faced issues:

    server.use(express.json());

server.post('/data', (req, res) => {
  res.send(`Received: ${req.body}`);
});

ChatBot Project

  • At the start of the project, I had trouble following the documentation guidelines. Even after reading the documentation, I found it hard to change the template to meet our project’s specific needs. However, I got better at this as the project went on.

  • Another challenge was integrating my code into the main project. My functions worked well on their own, but sometimes didn’t work correctly when added to the larger codebase. This led to a lot of troubleshooting and debugging to fix problems with dependencies, variable scope, and event handling. I also faced issues where the API didn’t always communicate properly with the bot, which made the integration even more challenging.

Additional Notes

  • Initially, I felt intimidated by the Execute Program concurrency course, so I decided to first complete the related Codecademy courses on Promises and Async-Await. This approach helped me feel more prepared and confident to tackle the Execute Program course.

  • Pair programming was highly beneficial; my teammate and I collaborated on debugging, refactoring, and modularizing the code files, leading to cleaner and more efficient project outcomes. This experience significantly contributed to my learning progress.

Feedback (For CF's)

[Course Facilitator name]

Alexander

[What went well]

Very good example of short code snippets and commands. I won't say that it is my favorite Progress log in the cohort, but it is!

[Even better if]

I won't change anything. I would just say to your future self to check this log before looking for help somewhere else