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+## LIBRARIES
+# //////////////////////////////////////////////////////////////////////////////
+
+import pandas as pd     # pandas for excel reading
+import re       # regex
+import json     # json
+import os.path  # ...
+
+
+## LOCAL FUNCTIONS
+# //////////////////////////////////////////////////////////////////////////////
+
+# do-me-INTeger
+# ---
+def domeInt(x) :
+    if isinstance(x, str) :     # if string
+        return int(x.strip())
+    if isinstance(x, float) :   # if float
+        return round(x)
+    return x      # otherwise is int already
+
+# do-me-Float
+# ---
+def domeFloat(x) :
+    if isinstance(x, str) :
+        return float(x.strip())
+    else :
+        return x + 0.00     # make sure that result is float
+
+
+def cleanText(x) :
+    removeList = [ ' με ', ' σε ', ' για ', ' του ', ' της ', ' των ', ' από ', '&', '.', ',', '!', '(', ')', '[', ']', '\'', '\"' ]
+
+    for r in removeList :
+        x = x.replace(r, ' ')
+    
+    x.replace('    ', ' ')      # remove spare spaces
+    x.replace('   ', ' ')
+    x.replace('  ', ' ')
+
+    return x
+
+
+def isSignificant(x) :
+    # is significant if words has no digit-characters
+    return not bool(re.match("\S*\d+\S*", x))
+
+
+
+# set root-keyQ: w (if not exist)
+# update frequency: f
+# into list: l
+## ---
+def rootKey ( w, f, l ) :
+    keyExists = False
+    for it in l :
+        if it['w'] == w :
+            keyExists = True
+            it['f'] += f
+    
+    if keyExists == False :
+        l.append({
+            'w' : w,
+            'f' : f,
+            'c' : []
+        })
+
+
+
+# connect keys: a , b
+# of product with id: i
+# with frequency: f
+# into list: l
+## ---
+def connectKeys( a, b, i, f, l ) :
+    if a == b :
+        return False    ## exclude just-in-case
+
+    for it in l :
+        if it['w'] == a :
+            
+            # word a found;
+            # lets update the connection to: b
+            bExists = False
+
+            for jt in it['c'] :
+                if jt['w'] == b :
+                    bExists = True
+                    # update the connection's data
+                    jt['f'] += f
+                    jt['p'].append(i)
+            
+            if bExists == False :
+                # create connection with word: b
+                it['c'].append({
+                    'w': b,
+                    'f': f,
+                    'p': [ i ]
+                })
+
+
+
+
+
+## LOCAL CONSTANTS
+# //////////////////////////////////////////////////////////////////////////////
+
+_COL = {
+    # -- main info
+    'freq'  : 0,    # frequency (based on recent orders)
+    'pid'   : 1,    # product id
+    'brand' : 2,    # brand
+    'barcd' : 3,    # barcode
+    'sklcd' : 4,
+    'eyscd' : 5,
+    'descr' : 6,    # product description
+    'sap2'  : 7     # SAP category level-2 id
+}
+
+
+
+
+## SET SOURCE and EXPORT FileNames
+# ------------------------------------------------------------------------------
+# location of excel file
+loc = "./data/PRODucts2search-wBrands.xlsx"
+
+print("default filename:", loc)
+newXLfile = input("input other Excel filename [enter to keep default]: ")
+
+if newXLfile != "" and os.path.exists(newXLfile):
+    loc = newXLfile
+else :
+    print(newXLfile, "is not a file; default is kept;")
+
+## baseEXPORTname = input("Base export name: ")
+
+
+
+## Read data
+# //////////////////////////////////////////////////////////////////////////////
+
+df = pd.read_excel(loc)     # read data from excel file
+
+rows = df.iterrows()        # set rows list
+
+
+# --- Lists to fill
+keywords_ = []     # all data
+minilist_ = []
+
+## keywords format:
+##   [
+##     {
+##        w : 'fresh',
+##        f : 150,
+##        c : [
+##              {  w : 'milk',   f : 150 , p : [122, 254, 907] },
+##              {  w : 'juice',  f : 50  , p : [254, 351] }
+##        ]
+##     },
+##     {...},
+##     ...
+##   ]
+## --- index:
+## w : word
+## f : frequency
+## c : combos / connections
+## p : list of product-ids with this combo
+
+# --- temporary variables (initialize)
+
+
+## LOOP through the rows to pre-proccess all products
+## ---
+for idx, row in rows :
+
+    description = row[_COL['descr']].strip()       # product description
+    pid  = domeInt( row[_COL['pid']] )      # product-id
+    fq   = domeInt( row[_COL['freq']] )     # frequency
+
+    # TODO:
+    # identify brands
+    # then ...
+
+    description = cleanText(description)           # clean sescription string
+    words = description.strip().upper().split()           # split to words
+    ## words = [w.strip('.,!;()[]') for w in words]   # clean strings
+
+    # identify significant words
+    keys = []
+    for w in words :
+        if isSignificant(w) :
+            keys.append(w)
+    
+    print(pid, keys)
+    # append words (and their combos) to the list
+    for w in keys :
+        rootKey( w, fq, keywords_ )
+        for w2 in keys :
+            if w2 != w :
+                connectKeys( w, w2, pid, fq, keywords_ )
+
+
+## SORT keywords
+# //////////////////////////////////////////////////////////////////////////////
+
+# --- sort childs of each key (per frequency, desc)
+for it in keywords_ :
+    it['c'].sort(key=lambda x: x['f'], reverse=True)
+
+
+# --- sort root keys
+keywords_.sort(key=lambda x: x['f'], reverse=True)
+
+# --- create mini list based on the sorted keywords_
+for it in keywords_ :
+    minilist_.append( it['w'] )
+
+
+## OUTPUT final data to a json-format file
+# //////////////////////////////////////////////////////////////////////////////
+
+with open("results/keywords-v2.json", "w", encoding="utf-8") as outfile :
+    data = json.dump(keywords_, outfile, sort_keys=False, indent=3, ensure_ascii=False)
+
+with open("results/minilist.json", "w", encoding="utf-8") as outfile :
+    data = json.dump(minilist_, outfile, sort_keys=False, indent=3, ensure_ascii=False)