initial commit

README.md

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+# rdb-to-sheets
+A very simple python script to convert the TXT output from RDB to an Excel Sheet
+
+## How to use
+1. On Meridian 1 do : LD 21; REQ PRT; TYPE RDB;
+1. Copy the output from the first DN up to the last DN listed (see example below)
+1. Save to somewhere as a raw txt
+1. Use Bash script to set up Python3 VENV, or install requirements.txt things with pip on your system however you please.
+1. Run : python3 ./rdb-to-sheets.py /your/rdb/file.txt 
+1. Enjoy your now converted rdb excel sheet (made in same directory as rdb-to-sheets.py by default, can also be anywhere you desire python3 like this ./rdb-to-sheets.py /your/rdb/file.txt /your/output/rdb/sheet.xslx)
+
+## Consideration
+1. I know little coding and even less python, I've tested it on my Meridian 1 Option 11e only as thats the only system I own.
+1. If you have suggestions on how to improve this feel free to submit those here.
+1. If I made something completely wrong in the script its not my responsibility.
+1. Have fun !

rdb-to-sheets.py

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+import sys
+import pandas as pd
+import re
+
+# Ensure its easier to use for normies
+if len(sys.argv) < 2:
+    print("Usage: python rdb-to-sheets.py <input_file> [output_file]")
+    print("Example: python rdb-to-sheets.py RDBv2.txt RDB.xlsx")
+    print("If no output file is defined RDB.xlsx will be used per default make sure such doesn't exist already")
+    sys.exit(1)  # Committ da sus side for script!
+
+# Set input and output file 
+input_file = sys.argv[1]
+output_path = sys.argv[2] if len(sys.argv) > 2 else "RDB.xlsx"  # Default to RDB.xlsx if user of script doesnt define it lmao
+
+
+with open(input_file, "r") as file:
+    lines = file.readlines()
+
+# Look at the data
+def parse_rdb_data(lines):
+    entries = []
+    current_entry = {}
+    current_tns = []
+
+    for line in lines:
+        line = line.strip()
+        if not line:
+            continue
+
+        # New DN entry starts
+        if line.startswith("DN"):
+            if current_entry:  # How about we save the previous entry before we look at a new one omg
+                if current_tns:
+                    current_entry["TNs"] = current_tns
+                entries.append(current_entry)
+                current_tns = []
+            current_entry = {"DN": line.split()[1]}
+
+        elif "CPND" in line:
+            current_entry["NAME"] = None
+
+        elif "NAME" in line and current_entry.get("NAME") is None:
+            current_entry["NAME"] = line.replace("NAME", "").strip()
+
+        elif line.startswith("TYPE"):
+            current_entry["TYPE"] = line.split()[1]
+
+        elif line.startswith("ROUT"):
+            current_entry["ROUT"] = line.split()[1]
+
+        elif line.startswith("STCD"):
+            current_entry["STCD"] = line.split()[1]
+
+        elif line.startswith("FEAT"):
+            current_entry["FEAT"] = " ".join(line.split()[1:])
+
+        elif line.startswith("TN"):
+            tn_match = re.search(r"(\d{3} \d \d{2} \d{2})", line)
+            if tn_match:
+                tn_value = tn_match.group(1)
+                tn_entry = {"TN_1_TN": tn_value}
+
+                key_match = re.search(r"KEY (\d{2})", line)
+                if key_match:
+                    tn_entry["KEY"] = key_match.group(1)
+
+                des_match = re.search(r"DES\s+(\S+)", line)
+                if des_match:
+                    tn_entry["DES"] = des_match.group(1)
+
+                date_match = re.search(r"(\d{1,2} \w{3} \d{4})", line)
+                if date_match:
+                    tn_entry["DATE"] = date_match.group(0)
+
+                tn_entry["MARP"] = "YES" if "MARP" in line else "NO"
+                current_tns.append(tn_entry)
+
+    if current_entry:
+        if current_tns:
+            current_entry["TNs"] = current_tns
+        entries.append(current_entry)
+
+    return entries
+
+parsed_entries = parse_rdb_data(lines)
+
+# Categorize them and shit
+def categorize_entries(entries):
+    main_entries = []
+    multiple_tns_entries = []
+    route_entries = []
+    cdp_entries = []
+    feature_code_entries = []
+    att_ldn_entries = []
+    other_entries = []
+    unexpected_data = []
+
+    for entry in entries:
+        entry_type = entry.get("TYPE")
+
+        if entry_type in ["SL1", "500"]:
+            if "TNs" in entry and len(entry["TNs"]) > 1:
+                for tn in entry["TNs"]:
+                    multi_entry = entry.copy()
+                    multi_entry.update(tn)
+                    multiple_tns_entries.append(multi_entry)
+            elif "TNs" in entry:
+                for tn in entry["TNs"]:
+                    main_entry = entry.copy()
+                    main_entry.update(tn)
+                    main_entries.append(main_entry)
+            else:
+                main_entries.append(entry)
+
+        elif entry_type in ["ATT", "LDN"]:
+            if "TNs" in entry:
+                for tn in entry["TNs"]:
+                    att_ldn_entry = entry.copy()
+                    att_ldn_entry.update(tn)
+                    att_ldn_entries.append(att_ldn_entry)
+            else:
+                att_ldn_entries.append(entry)
+
+        elif entry_type == "RDB":
+            route_entries.append(entry)
+
+        elif entry_type == "CDP":
+            cdp_entries.append({"DN": entry.get("DN", ""), "TYPE": entry.get("TYPE", ""), "STCD": entry.get("STCD", "DSC")})
+
+        elif entry_type == "FFC":
+            feature_code_entries.append(entry)
+
+        elif entry_type is None:
+            unexpected_data.append(entry)
+
+        else:
+            other_entries.append(entry)
+
+    unexpected_sheet_name = "No Unexpected Data" if not unexpected_data else "Unexpected Data"
+
+    return main_entries, multiple_tns_entries, route_entries, cdp_entries, feature_code_entries, att_ldn_entries, other_entries, unexpected_data, unexpected_sheet_name
+
+# Categorize entries further
+main_entries, multiple_tns_entries, route_entries, cdp_entries, feature_code_entries, att_ldn_entries, other_entries, unexpected_data, unexpected_sheet_name = categorize_entries(parsed_entries)
+
+
+# Save all the data to excel but dropping the raw unprocessed TNs tab that gets made for some reason I dont know why I hate coding and python
+with pd.ExcelWriter(output_path) as writer:
+    for sheet_name, data in {
+        "Main": main_entries,
+        "Multiple TNs": multiple_tns_entries,
+        "Routes": route_entries,
+        "CDP": cdp_entries,
+        "Feature Codes": feature_code_entries,
+        "ATT_LDN": att_ldn_entries,
+        "Other": other_entries,
+        unexpected_sheet_name: unexpected_data
+    }.items():
+        df = pd.DataFrame(data)
+        if "TNs" in df.columns:
+            df = df.drop(columns=["TNs"])  # Remove TNs column if present
+        df.to_excel(writer, sheet_name=sheet_name, index=False)
+
+print("Processing complete. Output saved to", output_path)

requirements.txt

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+et_xmlfile==2.0.0
+numpy==2.2.2
+openpyxl==3.1.5
+pandas==2.2.3
+python-dateutil==2.9.0.post0
+pytz==2025.1
+six==1.17.0
+tzdata==2025.1

setup.sh

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+#!/bin/bash
+python3 -m venv .venv
+source .venv/bin/activate
+pip3 install -r requirements.txt
+echo "venv made and activated. requirements should be installed too now"