Added translated JSON files

tools/ucsxls2json.py

@@ -0,0 +1,72 @@
+# ucsxls2json.py 
+# (c) 2024 Jamie Hardt
+#
+# This tool takes the "Full Translations" xlsx file and converts it into a
+# series of json files, one for each language in the table.
+#
+# This script is a part of the `ucs-community` project, a LICENSE file outling
+# your rights should be included in its distribution. For more information see 
+# the project website on github: https://github.com/iluvcapra/ucs-community
+
+import pandas as pd
+import json
+from typing import Dict
+import os
+
+# this key is added to ever category entry created in the output files
+UCS_VERSION = "8.2.1"
+
+# This is the file to pull descriptions from
+EXCEL_FILE = 'UCS v8.2.1 Full Translations.xlsx'
+
+data = pd.read_excel(EXCEL_FILE)
+
+# Create a table of all languages that maps language-column pairs to their
+# corresponding index in the xlsx
+
+# The English column headers aren't formatted like the other languages so we
+# just have to special-case them
+langs: Dict[str,Dict[int,str]] = {'en': {0: 'Category', 1: 'SubCategory', 2:
+                                         'CatID', 3:'CatShort',
+                                         4:'Explanations', 5: 'Synonyms'}}
+
+# step through each column
+for i, (col_index, col_data) in enumerate(data.T.iterrows()):
+
+    # the data is transposed, so indexing into col_data steps down in rows,
+    # row[1] is where all the headers are.
+    components = col_data[1].split("_")
+    
+    if len(components) == 2:
+        # If this is true, we are in a translation column
+        if components[0] == 'Category':
+            langs[components[1]] = dict()
+    
+        langs[components[1]][i] = components[0]
+
+os.makedirs("ucs_json", exist_ok=True)
+
+# Pull the rows into a list
+# skip the first three rows of the data, it's just header material
+rows = list(data.iterrows())[3:]
+
+# for each language
+
+for lang in langs:
+    # construct a schedule for the language
+    schedule = []
+
+    # for each row
+    for (_, row) in rows:
+
+        # create a dict for the category on this row
+        category = {'version':UCS_VERSION}
+        for col_index in langs[lang]:
+            key_name = langs[lang][col_index]
+            category[key_name] = row.iloc[col_index]
+        
+        schedule.append(category)
+
+    # and dump it to json
+    with open(f"ucs_json/{lang}.json", "w") as fp:
+        json.dump(schedule, indent=True, fp=fp)