THE FOLDER NAME SHOULD BE mgconky NOT mgconky-master.txt

@@ -4,4 +4,4 @@ This should be the folder:
 
 ~/.conky/mgconky/
 
-Thank you!
+Thank you.

conf

@@ -15,11 +15,10 @@
 -- !!!IMPORTANT!!! THE FOLLOWING ARE REQUIREMENTS FOR THIS SCRIPT TO WORK PROPERLY:
 --     (1) DEPENDENCIES.
 --         Install the following software, if not already installed:
---         "Conky"                 sudo apt-get install conky-all
---         "Jq"                    sudo apt-get install jq
---         "Curl"                  sudo apt-get install curl
---         "Wget"                  sudo apt-get install wget
---         "python3"               sudo apt-get install python3
+--         "Conky"                 sudo apt-get install conky-all          (or use software manager)
+--         "Jq"                    sudo apt-get install jq                 (or use software manager)
+--         "Curl"                  sudo apt-get install curl               (or use software manager)
+--         "Wget"                  sudo apt-get install wget               (or use software manager)
 --     (2) FONTS.
 --         Install the following custom fonts:
 --         "Neuropolitical"        Place .ttf file in ~/.fonts/            https://www.dafont.com/font-comment.php?file=neuropolitical
@@ -29,9 +28,8 @@
 --         chmod +x ~/.conky/mgconky/weather/get_weather.sh
 --         chmod +x ~/.conky/mgconky/weather/parse_weather.sh
 --         chmod +x ~/.conky/mgconky/weather/parse_forecast.sh
---         chmod +x ~/.conky/mgconky/stocks/get_stocks_alphavantage.py
---         chmod +x ~/.conky/mgconky/stocks/process_stocks_alphavantage.py
---         chmod +x ~/.conky/mgconky/stocks/get_stocks_finnhub.py
+--         chmod +x ~/.conky/mgconky/weather/parse_forecast.sh
+--         chmod +x ~/.conky/mgconky/stocks/get_stocks.py                  (Requires python3, which is usually pre-installed on your OS)
 --     (4) WEATHER.
 --         Make a free account at https://openweathermap.org/
 --         Write down your API key, which is found on the "API keys" tab after you log in.  (https://home.openweathermap.org/api_key
@@ -93,16 +91,16 @@ conky.config = {
     color7 = "#FF0000", -- Bad values (red)
 
     -- Weather variables
-    template0 = "<ENTER YOUR OPEANWEATHERMAP API KEY HERE>", -- OpenWeatherMap API key (https://home.openweathermap.org/api_keys)
-    template1 = "4467657", -- OpenWeatherMap City ID (the number in the URL of your city, for example:  https://openweathermap.org/city/5128581)
+    template0 = "YOUR_OPENWEATHERMAP_API_KEY_HERE", -- OpenWeatherMap API key (https://home.openweathermap.org/api_keys)
+    template1 = "YOUR_OPENWEATHERMAP_CITY_ID_HERE", -- OpenWeatherMap City ID (the number in the URL of your city, for example:  https://openweathermap.org/city/5128581)
     template2 = "imperial", -- Temp unit ("default" for Kelvin, "metric" for Celsius, "imperial" for Fahrenheit)
     template3 = "", -- Locale (e.g., "es_ES.UTF-8") # Leave empty for default
 
     -- Stock variables
-    template4 = "<ENTER YOUR FINNHUB API KEY HERE>", -- FinnHub API key (https://finnhub.io/)
-    template5 = "<ENTER YOUR ALPHAVANTAGE API KEY HERE", -- Alpha Vantage API key (https://www.alphavantage.co/)
-    template6 = "spy,dia,nvda,tsla,amzn,aapl,msft,meta,pg,ibit", -- Stock symbols for FinnHub (comma separated, no spaces, i.e. goog,amzn,aapl)
-    template7 = "tsla,spy,dia", -- Stock symbols for Alpha Vantage (keep to a minimum unless you have a paid API key)
+    template4 = "YOUR_FINNHUB_API_KEY_HERE", -- FinnHub API key (https://finnhub.io/)
+    template5 = "YOUR_ALPHAVANTAGE_API_KEY_HERE", -- Alpha Vantage API key (https://www.alphavantage.co/)
+    template6 = "goog,amzn,aapl,msft,meta,tsla,avgo,tsm,brk.a,pg,nvda", -- Stock symbols for FinnHub (comma separated, no spaces, i.e. goog,amzn,aapl)
+    template7 = "nvda", -- Stock symbols for Alpha Vantage (keep to a minimum unless you have a paid API key)
 
     -- Load Lua script(s) -- If multiple files, separate each path with a space. They should all be loaded on a single lua_load command.
     -- lua_load = "~/.conky/mgconky/script1.lua ~/.conky/mgconky/script2.lua",
@@ -179,8 +177,7 @@ ${voffset -6}${execpi 60 $HOME/.conky/mgconky/stocks/get_stocks_finnhub.py --api
 ${endif}
 # ***** Alpha Vantage API *****
 ${if_match "${template5}" != "YOUR_ALPHAVANTAGE_API_KEY_HERE"}
-${execpi 43200 $HOME/.conky/mgconky/stocks/get_stocks_alphavantage.py --api_key ${template5} --symbols ${template7} --range_in_days 30}
-${voffset -12}${execpi 60 $HOME/.conky/mgconky/stocks/process_stocks_alphavantage.py --symbols ${template7} --range_in_days 30 --price_dec_places 0 --percent_dec_places 1 --stale_seconds 43200}
+${voffset -12}${execpi 7200 $HOME/.conky/mgconky/stocks/get_stocks_alphavantage.py --api_key ${template5} --symbols ${template7} --range_in_days 30 --price_dec_places 0 --percent_dec_places 1}
 ${endif}
 #
 #--------------------------
@@ -237,7 +234,7 @@ ${voffset -6}Total: ${color3}${totaldown ${gw_iface}}${color}${goto 140}Total: $
 # Connections - netstat shows number of connections from your computer and application/PID making it. Kill spyware!
 #--------------------
 ${voffset 6}${color0}${font Neuropolitical:size=8:bold}CONNECTIONS ${color1}${hr 2}${color}${font Courier:size=9}
-#${voffset 2}${color3}${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr}${color}
-${voffset 2}${lua_parse conky_get_connections}
+${voffset 6}Num. connections / PID / Process
+${voffset 2}${color3}${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr}${color}
 ]]
 

devices/get_device_info.lua

@@ -13,7 +13,6 @@ function conky_shorten_cpu_name(cpu_name)
         :gsub("CPU", "")          -- Remove "CPU"
         :gsub("Processor", "")    -- Remove "Processor"
         :gsub("@[%s%w%.]+", "")   -- Remove "@ XGHz"
-        :gsub("with.*", "")       -- Remove "with" and anything after the word "with"
         :gsub("%s%s+", " ")       -- Remove extra spaces
         :gsub("^%s+", "")         -- Trim leading spaces
         :gsub("%s+$", "")         -- Trim trailing spaces
@@ -52,7 +51,7 @@ function conky_get_cpu_info()
     end
 end
 
--- ########################################################## GET GPU MAKE AND MODEL ##########################################################
+-- ########################################################## GET GU MAKE AND MODEL ###########################################################
 
 function conky_shorten_gpu_name(gpu_name)
     return (gpu_name
@@ -74,15 +73,11 @@ function conky_shorten_gpu_name(gpu_name)
         :gsub("Raspberry Pi Foundation", "Raspberry Pi")
         :gsub("Broadcom Inc%.", "Broadcom")
         :gsub("Lite Hash Rate", "LHR")
-        :gsub("Renoir", "")                      -- Remove "Renoir"
-        :gsub("Ryzen %d+/%d+ Mobile Series", "") -- Remove Ryzen details (for APUs)
-        :gsub("%(Ryzen.-%)", "")                 -- Remove Ryzen-related info in parentheses
-        :gsub("GA%d+%s%[", "")                   -- Remove chip identifier like "GA106 ["
-        :gsub("%[.*%]%s*", "")                   -- Remove chip code in brackets like "[1002:1636]"
-        :gsub("%((rev .-)%)", "")                -- Remove revision info like "(rev a1)"
-        :gsub("%s+", " ")                        -- Normalize spaces
-        :gsub("%]%s*$", "")                      -- Remove trailing square bracket "]" if it exists
-        :match("^%s*(.-)%s*$")                   -- Trim leading/trailing spaces
+        :gsub("GA%d+%s%[", "")                  -- Remove chip identifier like "GA106 ["
+        :gsub("%].*", "")                       -- Remove everything after "]"
+        :gsub("%(.*%)", "")                     -- Remove revision info like "(rev a1)"
+        :gsub("%s+", " ")                       -- Normalize spaces
+        :match("^%s*(.-)%s*$")                  -- Trim leading/trailing spaces
     )
 end
 
@@ -171,23 +166,6 @@ function conky_get_drives_and_volumes()
         if #data.mountpoints > 0 then
             output = output .. '${voffset 0}${color0}${font Neuropolitical:size=8:bold}DRIVE${font Courier:size=9} /dev/' .. drive .. '${color} ${color1}${hr 2}${color}\n'
             for _, mount in ipairs(data.mountpoints) do
-
-                -- Skip entries that are not real mountpoints like [SWAP]
-                if mount:sub(1, 1) ~= "/" then
-                    goto continue
-                end
-
-                -- Skip common temporary mounts
-                if mount:match("^/sys/") then goto continue end
-                if mount:match("^/proc/") then goto continue end
-                if mount:match("^/dev/") then goto continue end
-
-                -- Skip mounts under /var/, but allow a mount at /var itself
-                if mount ~= "/var" and mount:match("^/var/") then goto continue end
-
-                -- Skip runtime mounts except removable media
-                if mount:match("^/run/") and not mount:match("^/run/media/") then goto continue end
-
                 -- Use df to get the size and used space for the mount
                 local handle = io.popen("df -h --output=target,size,used " .. mount .. " | tail -n 1")
                 local df_result = handle:read("*a")
@@ -195,19 +173,10 @@ function conky_get_drives_and_volumes()
 
                 -- Parse df output
                 local target, size, used = df_result:match("(%S+)%s+(%S+)%s+(%S+)")
-
-                -- Ensure mount still exists before emitting fs_bar
-                local test = io.open(target, "r")
-                if not test then goto continue end
-                test:close()
-
-                -- Create output lines for this mountpoint.
                 if target and size and used then
                     output = output .. '${voffset 2}' .. target .. ': ${alignr}${color3}' .. used .. 'B${color} of ${color3}' .. size .. 'B${color}\n'
                     output = output .. '${voffset -2}${color5}${fs_bar ' .. target .. '}${color}\n'
                 end
-
-                ::continue::
             end
             output = output .. '\n' -- Add a blank line after the last mount point of the current drive
         end
@@ -387,64 +356,3 @@ print("    CHECK SWAP STATUS = " .. conky_check_swap_status())
 print("    GET MEMORY USAGE = " .. conky_get_memory_usage("mem"))
 print("    GET SWAP USAGE = " .. conky_get_memory_usage("swap"))
 
-
--- ####################################################### GET ACTIVE CONNECTIONS ##############################################################
-
-function conky_get_key_with_highest_value(t)
-    local max_key = nil
-    local max_value = -math.huge  -- Initialize with the smallest possible number
-
-    for key, value in pairs(t) do
-        if type(value) == "number" and value > max_value then
-            max_value = value
-            max_key = key
-        end
-    end
-
-    return max_key
-end
-
-function conky_get_connections()
-    local handle = io.popen("ss -eptH | grep ESTAB 2>/dev/null")
-    if not handle then return "Error: Unable to execute ss command" end
-
-    local process_names = {}
-    local process_counts = {}
-
-    -- Read each line of output
-    for line in handle:lines() do
-        -- Extract process name and PID using pattern matching
-        local pname, pid = line:match('users:%(%("([^"]+)",pid=(%d+)')
-        pid = tonumber(pid)  -- Ensure pid is a number
-        if pname and pid then
-            -- Store process name by PID and count occurrences
-            process_names[pid] = pname
-            process_counts[pid] = (process_counts[pid] or 0) + 1
-        end
-    end
-    handle:close()
-
-    -- Header line
-    local tab1_offset = "${goto 145}"
-    local line_prefix = "${voffset 0}${color}${font StyleBats:size=10}h${font Courier:size=9}${voffset -1}${color3}"
-    local result = string.format("${color}Process%sPID${alignr}Num \n", tab1_offset)
-
-    -- Sort and format output
-    while true do
-        local max_key = conky_get_key_with_highest_value(process_counts)
-
-        if max_key == nil then
-            break  -- Stop when the table is empty
-        end
-
-        result = result .. string.format("%s %s%s%d${alignr}%d \n", line_prefix, string.sub(process_names[max_key], 1, 16), tab1_offset, max_key, process_counts[max_key])
-
-        -- Remove the highest key from both tables
-        process_counts[max_key] = nil
-        process_names[max_key] = nil
-    end
-
-    return result
-end
-
-

stocks/get_stocks_alphavantage.py

@@ -1,31 +1,11 @@
 #!/usr/bin/env python3
 
-import os
-import sys
-import time
-import json
-import argparse
 import requests
 from datetime import datetime, timedelta
-
-# Directory where per-symbol cache JSON files are stored
-CACHE_DIR = os.path.expanduser("~/.cache/mgconky/stocks_alphavantage/")
-
-# Delay between API calls to respect AlphaVantage rate limits
-API_DELAY_SECONDS = 1
-
-# Minimum age before re-querying a symbol to avoid API thrashing
-NO_THRASH_SECONDS = 60 * 60  # 1 hour
-
-
-def log_error(message):
-    """Print timestamped error message to stderr and flush immediately."""
-    ts = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    print(f"[{ts}] {message}", file=sys.stderr, flush=True)
-
+import argparse
 
 def fetch_intraday_data(api_key, symbol, interval="1min"):
-    # Query AlphaVantage intraday endpoint for the given symbol
+    """Fetch current and historical intraday price using TIME_SERIES_INTRADAY."""
     url = "https://www.alphavantage.co/query"
     params = {
         "function": "TIME_SERIES_INTRADAY",
@@ -39,31 +19,36 @@ def fetch_intraday_data(api_key, symbol, interval="1min"):
             data = response.json()
             time_series = data.get(f"Time Series ({interval})")
 
+            # Debug: Log the raw response
+            #print(f"DEBUG: Response data for {symbol}: {data}")
+
             if time_series:
-                # Use earliest bar as open price and latest bar as current price
+                # Sort the timestamps to get the first (open) and latest price
                 sorted_timestamps = sorted(time_series.keys())
-                open_time = sorted_timestamps[0]
-                latest_time = sorted_timestamps[-1]
+                open_time = sorted_timestamps[0]  # Earliest timestamp of the day
+                latest_time = sorted_timestamps[-1]  # Most recent timestamp
+
+                # Extract open price and latest price
+                open_price = float(time_series[open_time]["1. open"])
+                latest_price = float(time_series[latest_time]["4. close"])
 
                 return {
-                    "current_price": float(time_series[latest_time]["4. close"]),
-                    "compare_price": float(time_series[open_time]["1. open"]),
+                    "current_price": latest_price,
+                    "compare_price": open_price
                 }
             else:
-                # API responded but did not include expected time series data
-                log_error(f"No 'Time Series ({interval})' data found for {symbol}.")
+                print(f"Error: No 'Time Series ({interval})' data found for {symbol}.")
+                return None
         else:
-            # HTTP error from AlphaVantage
-            log_error(f"Failed to fetch intraday data for {symbol} (HTTP {response.status_code})")
+            print(f"Error: Failed to fetch intraday data for {symbol} (HTTP {response.status_code})")
+            return None
     except requests.RequestException as e:
-        # Network or request failure
-        log_error(f"Failed to fetch intraday data for {symbol} - {e}")
-
-    return None
+        print(f"Error: Failed to fetch intraday data for {symbol} - {e}")
+        return None
 
 
 def fetch_historical_data(api_key, symbol, range_in_days):
-    # Query AlphaVantage daily endpoint for historical comparison
+    """Fetch current and historical price using TIME_SERIES_DAILY, allowing fallback to nearby dates."""
     url = "https://www.alphavantage.co/query"
     params = {
         "function": "TIME_SERIES_DAILY",
@@ -76,109 +61,96 @@ def fetch_historical_data(api_key, symbol, range_in_days):
             data = response.json()
             time_series = data.get("Time Series (Daily)")
 
+            # Debug: Log the raw response
+            #print(f"DEBUG: Response data for {symbol}: {data}")
+
             if time_series:
-                # Most recent trading day's close is the current price
+                # Current price is the latest closing price
                 latest_date = max(time_series.keys())
-                current_price = float(time_series[latest_date]["4. close"])
+                latest_data = time_series[latest_date]
+                current_price = float(latest_data["4. close"])
 
-                # Target calendar date for comparison
-                target = datetime.now() - timedelta(days=range_in_days)
+                # Dates to check: exact, one day before, one day after
+                target_date = (datetime.now() - timedelta(days=range_in_days)).strftime("%Y-%m-%d")
+                fallback_dates = [
+                    target_date,
+                    (datetime.now() - timedelta(days=range_in_days + 1)).strftime("%Y-%m-%d"),
+                    (datetime.now() - timedelta(days=range_in_days - 1)).strftime("%Y-%m-%d")
+                ]
 
-                # Walk backward up to 10 days to find a valid trading day
+                # Find the first available date in the fallback list
                 historical_price = None
-                for offset in range(10):
-                    d = (target - timedelta(days=offset)).strftime("%Y-%m-%d")
-                    if d in time_series:
-                        historical_price = float(time_series[d]["4. close"])
+                for date in fallback_dates:
+                    if date in time_series:
+                        historical_price = float(time_series[date]["4. close"])
                         break
 
                 return {
                     "current_price": current_price,
-                    "compare_price": historical_price,
+                    "compare_price": historical_price
                 }
             else:
-                # API responded but did not include expected daily series data
-                log_error(f"No 'Time Series (Daily)' data found for {symbol}.")
+                print(f"Error: No 'Time Series (Daily)' data found for {symbol}.")
+                return None
         else:
-            # HTTP error from AlphaVantage
-            log_error(f"Failed to fetch historical data for {symbol} (HTTP {response.status_code})")
-
+            print(f"Error: Failed to fetch historical data for {symbol} (HTTP {response.status_code})")
+            return None
     except requests.RequestException as e:
-        # Network or request failure
-        log_error(f"Failed to fetch historical data for {symbol} - {e}")
-
-    return None
-
+        print(f"Error: Failed to fetch historical data for {symbol} - {e}")
+        return None
 
 def main():
     # Parse command-line arguments
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--api_key", required=True)
-    parser.add_argument("--symbols", required=True)
-    parser.add_argument("--range_in_days", type=int, default=0)
+    parser = argparse.ArgumentParser(description="Fetch stock data from Alpha Vantage.")
+    parser.add_argument("--api_key", required=True, help="Your Alpha Vantage API key")
+    parser.add_argument("--symbols", required=True, help="Comma-separated list of stock symbols")
+    parser.add_argument("--range_in_days", type=int, default=0, help="Number of days for historical comparison (0 for none)")
+    parser.add_argument("--price_dec_places", type=int, default=0, help="Decimal places for prices")
+    parser.add_argument("--percent_dec_places", type=int, default=1, help="Decimal places for percentages")
     args = parser.parse_args()
 
-    # Normalize and split ticker symbols
+    # Split symbols
     symbols = args.symbols.strip().upper().split(",")
 
-    # Ensure cache directory exists
-    os.makedirs(CACHE_DIR, exist_ok=True)
+    # Use a list to build the final output string
+    output = []
 
-    for i, symbol in enumerate(symbols):
-        cache_path = os.path.join(CACHE_DIR, f"{symbol}.json")
+    # Prepare for printing output
+    color_header = "${color}"
+    color_label = "${color3}"
+    color_value = "${color3}"
+    color_good = "${color6}"
+    color_bad = "${color7}"
+    line_tab1_offset = "${goto 25}"
+    line_tab2_offset = "${goto 90}"
+    line_tab3_offset = "${alignr}" # Could also replace this with goto 120 if you don't like the right alignment
 
-        # --- No-thrash protection: skip API call if cache is still fresh ---
-        if os.path.exists(cache_path):
-            try:
-                with open(cache_path, "r") as f:
-                    payload = json.load(f)
-
-                if (
-                    isinstance(payload, dict)
-                    and "timestamp" in payload
-                    and isinstance(payload["timestamp"], (int, float))
-                    and (time.time() - payload["timestamp"]) < NO_THRASH_SECONDS
-                ):
-                    # Cached data is recent enough -> skip querying AlphaVantage
-                    continue
-            except Exception:
-                # Any read/parse error -> ignore cache and refetch
-                pass
-
-        # Fetch either intraday or historical data depending on range
-        fetched_data = (
-            fetch_intraday_data(args.api_key, symbol)
-            if args.range_in_days < 1
-            else fetch_historical_data(args.api_key, symbol, args.range_in_days)
-        )
-
-        # Only write cache if fetched data is structurally valid
-        if (
-            isinstance(fetched_data, dict)
-            and "current_price" in fetched_data
-            and isinstance(fetched_data["current_price"], (int, float))
-        ):
-            tmp = os.path.join(CACHE_DIR, f"{symbol}.json.tmp")
-            final = os.path.join(CACHE_DIR, f"{symbol}.json")
-
-            # Payload includes metadata for staleness and debugging
-            payload = {
-                "symbol": symbol,
-                "range_in_days": args.range_in_days,
-                "timestamp": int(time.time()),
-                "data": fetched_data,
-            }
-
-            # Atomic write to avoid corrupting existing cache
-            with open(tmp, "w") as f:
-                json.dump(payload, f)
-            os.replace(tmp, final)
-
-        # Rate-limit delay between symbols
-        if i < len(symbols) - 1:
-            time.sleep(API_DELAY_SECONDS)
+    # Iterate symbols
+    for symbol in symbols:
+        fetched_data = fetch_intraday_data(args.api_key, symbol) if args.range_in_days < 1 else fetch_historical_data(args.api_key, symbol, args.range_in_days)
+        if fetched_data:
+            current_price = fetched_data["current_price"]
+            compare_price = fetched_data["compare_price"]
+            price_difference = current_price - compare_price
+            percent_change = (price_difference / current_price) * 100
+            color_dynamic = (
+                color_good if round(price_difference, args.price_dec_places) > 0 
+                else color_bad if round(price_difference, args.price_dec_places) < 0 
+                else color_value
+            )
+            output.append(
+                f"{line_tab1_offset}{color_label}{symbol}: {line_tab2_offset}{color_value}{round(current_price, args.price_dec_places):.{args.price_dec_places}f} "
+                f"{line_tab3_offset}{color_dynamic}{round(price_difference, args.price_dec_places):+.{args.price_dec_places}f} "
+                f"({round(percent_change, args.percent_dec_places):+.{args.percent_dec_places}f}%)"
+            )
+        else:
+            output.append(f"{symbol}: Error fetching data")
 
+    # Join all parts of the output and print it
+    header_label = f"Intraday" if args.range_in_days < 1 else f"{args.range_in_days} Day"
+    header_line = f"{line_tab1_offset}{color_header}Ticker{line_tab2_offset}Price ($$){line_tab3_offset}{header_label}{color_label}"
+    return header_line + "\n" + f"{line_tab1_offset}{color_header}${{voffset -5}}${{hr 1}}" + "\n" + "\n".join(output)
 
 if __name__ == "__main__":
-    main()
+    print(main())
 

stocks/process_stocks_alphavantage.py

@@ -1,146 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import sys
-import time
-import json
-import argparse
-from datetime import datetime, timedelta
-
-# Directory containing cached per-symbol JSON files
-CACHE_DIR = os.path.expanduser("~/.cache/mgconky/stocks_alphavantage/")
-
-def main():
-    # Parse command-line arguments (reader does not need api_key)
-    parser = argparse.ArgumentParser(description="Process cached Alpha Vantage stock data.")
-    parser.add_argument("--symbols", required=True, help="Comma-separated list of stock symbols")
-    parser.add_argument("--range_in_days", type=int, default=0, help="Number of days for historical comparison")
-    parser.add_argument("--price_dec_places", type=int, default=0, help="Decimal places for prices")
-    parser.add_argument("--percent_dec_places", type=int, default=1, help="Decimal places for percentages")
-    parser.add_argument("--stale_seconds", type=int, default=13 * 3600, help="Seconds before cached data is considered stale")
-    args = parser.parse_args()
-
-    # Split ticker symbols by comma
-    symbols = args.symbols.strip().upper().split(",")
-
-    # Collect formatted output lines for Conky
-    output = []
-
-    # Conky color and layout formatting
-    color_header = "${color}"
-    color_label = "${color3}"
-    color_value = "${color3}"
-    color_good = "${color6}"
-    color_bad = "${color7}"
-    line_tab1_offset = "${goto 25}"
-    line_tab2_offset = "${goto 90}"
-    line_tab3_offset = "${alignr}"
-
-    # Process each symbol
-    for symbol in symbols:
-        cache_path = os.path.join(CACHE_DIR, f"{symbol}.json")
-
-        # Missing cache file -- display formatted placeholder
-        if not os.path.exists(cache_path):
-            output.append(
-                f"{line_tab1_offset}{color_bad}{symbol}: "
-                f"{line_tab2_offset}{color_value}-- "
-                f"{line_tab3_offset}{color_value}-- (--%)"
-            )
-            continue
-
-        # Determine cache age using file modification time
-        age_seconds = time.time() - os.stat(cache_path).st_mtime
-
-        # Symbol turns red (color_bad) if cached data is stale
-        symbol_color = color_bad if age_seconds > args.stale_seconds else color_label
-
-        # Load cached JSON payload
-        try:
-            with open(cache_path, "r") as f:
-                payload = json.load(f)
-
-            # Validate payload structure before use
-            if not isinstance(payload, dict) or "data" not in payload:
-                raise ValueError("Invalid cache payload")
-
-            fetched_data = payload["data"]
-
-        except Exception:
-            # Corrupt or unreadable cache file -- display formatted placeholder
-            output.append(
-                f"{line_tab1_offset}{color_bad}{symbol}: "
-                f"{line_tab2_offset}{color_value}-- "
-                f"{line_tab3_offset}{color_value}-- (--%)"
-            )
-            continue
-
-        # ------------------------------
-        # VALIDATION
-        # ------------------------------
-        if (
-            isinstance(fetched_data, dict)
-            and "current_price" in fetched_data
-            and isinstance(fetched_data["current_price"], (int, float))
-        ):
-            current_price = fetched_data["current_price"]
-            compare_price = fetched_data["compare_price"]
-
-            # Comparison price may be missing if no trading day was found
-            if not isinstance(compare_price, (int, float)):
-                symbol_color = color_bad
-                output.append(
-                    f"{line_tab1_offset}{symbol_color}{symbol}: "
-                    f"{line_tab2_offset}{color_value}-- "
-                    f"{line_tab3_offset}{color_value}-- (--%)"
-                )
-                continue
-
-            # Compute absolute and percentage change
-            price_difference = current_price - compare_price
-            percent_change = (price_difference / current_price) * 100
-
-            # Color change based on price movement direction
-            color_dynamic = (
-                color_good if round(price_difference, args.price_dec_places) > 0
-                else color_bad if round(price_difference, args.price_dec_places) < 0
-                else color_value
-            )
-
-            # The actual formatted line with valid stock data
-            output.append(
-                f"{line_tab1_offset}{symbol_color}{symbol}: "
-                f"{line_tab2_offset}{color_value}{round(current_price, args.price_dec_places):.{args.price_dec_places}f} "
-                f"{line_tab3_offset}{color_dynamic}{round(price_difference, args.price_dec_places):+.{args.price_dec_places}f} "
-                f"({round(percent_change, args.percent_dec_places):+.{args.percent_dec_places}f}%)"
-            )
-        else:
-            # Cached data missing required fields -- display formatted placeholder
-            output.append(
-                f"{line_tab1_offset}{color_bad}{symbol}: "
-                f"{line_tab2_offset}{color_value}-- "
-                f"{line_tab3_offset}{color_value}-- (--%)"
-            )
-
-    # Header label depends on intraday vs historical mode
-    header_label = "Intraday" if args.range_in_days < 1 else f"{args.range_in_days} Day"
-
-    # Formatted header line
-    header_line = (
-        f"{line_tab1_offset}{color_header}Ticker"
-        f"{line_tab2_offset}Price ($$)"
-        f"{line_tab3_offset}{header_label}{color_label}"
-    )
-
-    # Print final output for Conky to render
-    print(
-        header_line
-        + "\n"
-        + f"{line_tab1_offset}{color_header}${{voffset -5}}${{hr 1}}"
-        + "\n"
-        + "\n".join(output)
-    )
-
-if __name__ == "__main__":
-    main()
-