Stock Analysis CLI Application

Overview

This CLI application is built to analyze stocks using the OPG (Open Price Gap) strategy.

The project can be broken down into the following phases:

• Load Stocks from a CSV File
• Filter out unworthy Stocks
• Process Stocks (position: quantity and price)
• Fetch News for each Stock
• Produce Output in JSON Format

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Day-Wise Progress

Day 1

CSV File Format

The CSV file is structured as follows:

• Row 1: Ticker
• Row 2: Gap
• Row 3: Opening Price

Reading the CSV File

• Before reading the CSV file, the program needs to open the file. This is done using the os.Open("/path") method.
• We use csv.NewReader to read the contents of the CSV file.

Stock Struct

• To store the stock data, we create a Stock struct with the following fields:
  • Ticker
  • Gap
  • Opening Price
• We then use a slice to hold multiple Stock struct objects.

Data Type Conversion

• CSV file values are read as strings, but the Stock struct fields (Gap and OpeningPrice) are of type float64.
• To handle this, we use strconv.ParseFloat() to convert the string values to float64.

Closing the File

• We use defer f.Close() to ensure the file is closed properly after the operation is complete.

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Day 2

Filtering Unworthy Stocks

• Used DeleteFunc() of slices to delete the unworthy stocks.

---

Day 3

Calculating positions for the shares

• Postion is : Entry price, number of shares, target profit, stop less price
• For calculation we have coded some hard coded values and some formulas
• To store the result, a struct Position is created

Position struct {
EntryPrice float64 // the price at which to buy or sell
Shares int // amount of shares to buy / sell
TakeProfitPrice float64 // the price at which to take exit and make profit
StopLossPrice float64 // the price at which to stop my loss if stock doesn't go our way
Profit float64 // expected final profit
}

• then calculate() function
• Now we have instance of Stock struct and Position Struct for each stocks we have. We need to combine both under Selection Struct having Ticker and Postion : this will help user to determine if to buy the stock or not

type Selection struct {
Ticker string
Position
}

---

Day 4

Fetching news

• We will fetch news on each stock from seekingalpha.com
• first we created a http client http.NewRequest(http.MethodGet, url + ticker, nil), this takes 3 argument : method, url, req-body if any
• We added a header, and then created http Client to make request using Do() function.
• Do() fnc return a pointer to http response object

Mapping response data and creating structs to read data from response

Demo response

{
    "data": [
        {
            "id": "4395525",
            "type": "news",
            "attributes": {
                "publishOn": "2025-01-16T05:56:23-05:00",
                "isLockedPro": false,
                "commentCount": 10,
                "gettyImageUrl": "https://static.seekingalpha.com/cdn/s3/uploads/getty_images/2193527787/image_2193527787.jpg",
                "videoPreviewUrl": null,
                "videoDuration": null,
                "themes": {},
                "title": "Biden warns of ultrarich oligarchy, tech-industrial complex in farewell speech",
                "isPaywalled": false

• So here we will focus on PublishOn and Title attributes from the res.Body.data, So we have created a struct

  type attributes struct {
  PublishOn time.Time `json:publishOn`
  Title     string    `json:title`
  }

  the `` helps to clearify the mapping process that PublishOn will be mapped to json - publishOn attribute, it is a good practise

• Now as attributes is inside data, we need to have data types that can contain the required format.

  type attributes struct {
  PublishOn time.Time `json:publishOn`
  Title     string    `json:title`
  }
  
  type seekingAlphaNews struct {
    Attributes attributes `json:attributes`
  }
  type SeekingAlphaResponse struct {
    Data []seekingAlphaNews `json:data`      // response can be mapped to SeekinAlphaNews
  }

• Now we map all the req data in our struct

  res := &SeekingAlphaResponse{}
  json.NewDecoder(response.Body).Decode(res)

• Now finally we have articles slice of Article Strcut objects, which are returned along with the error.

Day 5

• Now we will update Selection struct to have slice of articles for each stock

  type Selection struct {
  Ticker string
  Position
  Articles []Article
  }

• We will call FetchNews() func in the for_range loop when creating selection stock and set the articles as well

Day 6

• Now we will write the output into the file as JSON using Deliver() fnc.
  • First using os package file is created
  • then using encoder for JSON, the values from selections slice is written in file !!

Happy Stocking with Go !!