celaning

flask_be/engine/decoder/atab.csv

@@ -1,3329 +0,0 @@
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flask_be/engine/decoder/decoder.py

@@ -1,87 +0,0 @@
-# %%
-import csv
-# %%
-with open("vettSpec.csv", 'r') as file1:
-    reader = csv.DictReader(file1)
-    vettSpec = [row for row in reader]
-# %%
-testChar = 'Ҙ'
-print( testChar.encode("utf-32-le") )
-
-print( int.from_bytes(testChar.encode("utf-32-le"), 'little', signed=False) )
-
-pre = next((el['unicode'] for el in vettSpec if int(el['intcode']) == int.from_bytes(testChar.encode("utf-32-le"), 'little', signed=False)), None)
-
-res = bytes.fromhex(pre)
-while len(res)<4:
-    res=res+b'\x00'
-
-print('pre-Res:', pre)
-print('Res-bytes:', res)
-print('Res:', res.decode("utf-32-le") )
-# %%
-# mmm...
-print('n'.encode("utf-32-be").hex().lstrip('0').upper())
-
-post = next((el['intcode'] for el in vettSpec if el['unicode'] == 'n'.encode("utf-32-be").hex().lstrip('0').upper()), None)
-
-print(post)
-
-byteini = int.to_bytes(int(post), 4, byteorder='little')
-
-byteini.decode('utf-32-le')
-# %%
-testoProva = 'C:/Users/Kora/Desktop/ndg2.gat4/ndg2.gat4/itxt/10n'
-# %%
-with open(testoProva, 'rb') as fille:
-    azz = fille.read()
-# %%
-azz
-# %%
-def decode(char):
-    pre = next((el['unicode'] for el in vettSpec if int(el['intcode']) == int.from_bytes(char.encode("utf-32-le"), 'little', signed=False)), None)
-    resBytes = bytes.fromhex(pre)
-    while len(resBytes)<4:
-        resBytes=resBytes+b'\x00'
-    res = resBytes.decode("utf-32-le")
-    return res
-
-def decodeFromBytes(charBytes):
-    pre = next((el['unicode'] for el in vettSpec if int(el['intcode']) == int.from_bytes(charBytes, 'little', signed=False)), None)
-    resBytes = bytes.fromhex(pre)
-    while len(resBytes)<4:
-        resBytes=resBytes+b'\x00'
-    res = resBytes.decode("utf-32-le")
-    return res
-# %%
-str1 = ""
-for ind, char in enumerate(azz[:100]):
-    print(char)
-    str1 = str1+decode(char)
-print(str1)
-# %%
-print( azz[:4] )
-int.from_bytes(azz[:4], 'little', signed=False)
-# %%
-def decode(char):
-    pre = next((el['unicode'] for el in vettSpec if int(el['intcode']) == int.from_bytes(char.encode("utf-32-le"), 'little', signed=False)), None)
-    resBytes = bytes.fromhex(pre)
-    while len(resBytes)<4:
-        resBytes=resBytes+b'\x00'
-    res = resBytes.decode("utf-32-le")
-    return res
-
-testChar = 'Ҙ'
-print( testChar.encode("utf-32-le") )
-print( int.from_bytes(testChar.encode("utf-32-le"), 'little', signed=False) )
-pre = next((el['unicode'] for el in vettSpec if int(el['intcode']) == int.from_bytes(testChar.encode("utf-32-le"), 'little', signed=False)), None)
-print(pre)
-resBytes = bytes.fromhex(pre)
-print(resBytes)
-while len(resBytes)<4:
-        resBytes=resBytes+b'\x00'
-print(resBytes)
-res = resBytes.decode("utf-32-le")
-print(res)
-# %%
-

flask_be/engine/decoder/furioso.csv

@@ -1,332 +0,0 @@
-417
-865
-62
-783
-874
-280
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flask_be/engine/decoder/key_p07.csv

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flask_be/engine/decoder/keys/key_aa1.csv

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flask_be/engine/decoder/keys/key_cd.csv

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flask_be/engine/decoder/keys/key_ck.csv

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flask_be/engine/decoder/keys/key_d17.csv

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flask_be/engine/decoder/keys/key_fq.csv

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flask_be/engine/decoder/keys/key_g.csv

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flask_be/engine/decoder/keys/key_i51.csv

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flask_be/engine/decoder/keys/key_iya.csv

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flask_be/engine/decoder/keys/key_lb1.csv

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flask_be/engine/decoder/keys/key_od2.csv

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flask_be/engine/decoder/keys/key_p07.csv

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flask_be/engine/decoder/keys/key_rd.csv

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flask_be/engine/decoder/keys/vettSpec.csv

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flask_be/engine/decoder/test_decoder.py

@@ -1,498 +0,0 @@
-# %%
-import csv
-import sqlite3
-import pandas as pd
-import dtale
-import unicodedata
-import sys
-import random
-# %%
-
-# encoding/decoding functions for db
-# %% funzione decodifica
-def db_decode(string):
-    res = ""
-    with open("vettSpec.csv", 'r') as file1:
-        reader = csv.DictReader(file1)
-        vettSpec = [row for row in reader]
-    for c in string:
-        char_code = int.from_bytes(c.encode("utf-32-le"), 'little', signed=False)
-        found = next((el['unicode'] for el in vettSpec if int(el['intcode']) == char_code), "")
-
-        res += chr(int(found, 16))
-
-    return res
-
-#%% funzione codifica
-def db_encode(string):
-    encoded_string = ""
-    with open("vettSpec.csv", 'r') as file1:
-        reader = csv.DictReader(file1)
-        vettSpec = [row for row in reader]
-    for char in string:
-        post = next((el['intcode'] for el in vettSpec if el['unicode'] == char.encode("utf-32-be").hex().lstrip('0').upper()), None)
-        byteini = int.to_bytes(int(post), 4, byteorder='little')
-        encoded_string += byteini.decode('utf-32-le')
-    return encoded_string
-
-#%% funzione combinazioni (gestione <>)
-def combinations(s):
-  result = []
-  start = s.find("˴")
-  end = s.find("˶")
-  if start == -1 or end == -1:
-    return [s]
-  items = s[start + 1:end].split("Ñ")
-  for item in items:
-    result.extend([s[:start] + item + rest for rest in combinations(s[end + 1:])])
-  return result
-
-#%% funzione interprete (chiama le funzioni precedenti e sostituisce i caratteri jolly non standard)
-def interpreter (data):
-    encoded_data = db_encode(data)
-    clean_data= "'"+encoded_data.replace("˯", "%").replace("Ò", "_")+"'"
-    return combinations(clean_data)    
-
-#%% raddoppia l'iniziale della stringa in ingresso (se non è un carattere jolly)     
-def inizialeraddoppiata (data):
-    doubleddata=[]
-    for el in data:
-        if el[1] != "%" and "_":
-            doubleddata = doubleddata + ["'"+ el[1] + el[1:]]
-    return doubleddata
-
-#%% normalizza la stringa di testo togliendo i diacritici
-def str_normalize(string):
-    normalized_string = ""
-    with open("atab.csv", 'r') as file1:
-        reader = csv.DictReader(file1)
-        atab = [row for row in reader]
-    for c in string:
-        char_code = int.from_bytes(c.encode("utf-32-le"), 'little', signed=False)
-        found = next((el['norm'] for el in atab if int(el['spec']) == char_code), None)
-        pre = found if found else ""
-        byteini = int.to_bytes(int(pre), 4, byteorder='little')
-        normalized_string += byteini.decode('utf-32-le')
-    return normalized_string
-
-#%% applica la normalizzazione a una lista di stringhe
-def list_normalize(lista):
-    return ["'" + str_normalize(stringa.strip("'")) + "'" for stringa in lista]
-
-def db_results_decode (df):
-    columns = ['forma', 'lemma', 'cat_gr', 'disambiguatore']
-    for col in df.columns:
-        if col in columns or col.startswith('highlight'):
-            df[col] = df[col].apply(db_decode)
-    #df = df.applymap(lambda x: db_decode(x) if type(x) == str else x)
-    return df
-
-#%% funzione lista tabelle occorrenziario   
-def get_tables_occ(path):
-    conn = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    cursor = conn.cursor()
-    cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
-    table_names = cursor.fetchall()
-    occ_tables = [table[0] for table in table_names if table[0].startswith('Occ')]
-    cursor.close()
-    conn.close()
-    return occ_tables
-
-#funzione contatore risultati
-def counter (results):
-    if not results.empty:
-        trovati= len(results.index)
-        occorrenze= results['occ'].sum()
-        return ("Trovati=" + str(trovati) + " Occorrenze=" + str(occorrenze))   
-    
-#%% funzioni test
-def ricercaforme (entries, path, espansa, raddoppiata):
-    if espansa == 0: 
-        data=" OR spec LIKE ".join(entries)
-        doubleddata=" OR spec LIKE ".join(inizialeraddoppiata(entries))
-        
-        if raddoppiata == 1: 
-            theSimpleQuery = f"SELECT spec AS forma, nocc AS occ, cod FROM form WHERE spec LIKE {data} OR spec LIKE {doubleddata} ORDER BY idfor"
-        else:
-            theSimpleQuery = f"SELECT spec AS forma, nocc AS occ, cod FROM form WHERE spec LIKE {data} ORDER BY idfor"
-
-        con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-        answer_table = pd.read_sql(theSimpleQuery, con)
-        if answer_table.empty:
-            print ("Nessun risultato")
-            sys.exit(1)
-        else:
-            return answer_table
-
-    else:
-
-        data=" OR spec LIKE ".join(entries)
-        data_norm=" OR norm LIKE ".join(list_normalize(entries))
-        doubleddata_norm=" OR norm LIKE ".join(list_normalize(inizialeraddoppiata(entries)))
-        doubleddata=" OR spec LIKE ".join(inizialeraddoppiata(entries))
-
-        if raddoppiata == 1:
-            theSimpleQuery = f"SELECT DISTINCT spec AS forma, nocc AS occ, cod FROM form WHERE (spec LIKE {data}) OR (norm LIKE {data_norm}) OR (spec LIKE {doubleddata}) OR (norm LIKE {doubleddata_norm}) ORDER BY idfor"
-        else:
-            theSimpleQuery = f"SELECT DISTINCT spec AS forma, nocc AS occ, cod FROM form WHERE (spec LIKE {data}) OR (norm LIKE {data_norm}) ORDER BY idfor"
-
-        con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-        answer_table = pd.read_sql(theSimpleQuery, con)
-        if answer_table.empty:
-            print ("Nessun risultato")
-            sys.exit(1)
-        else:
-            return answer_table
-
-def findtexts(type, df, listOcc, path, index=None):
-    if index is None:
-        df = pd.DataFrame(df)
-    else:
-        if isinstance(index, range):
-            index = list(index)
-        elif not isinstance(index, list):
-            index = [index]
-        df = pd.DataFrame(df.loc[index])
-    textlist = pd.DataFrame()
-    codlist = list(df["cod"])
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    for table in listOcc:
-        strlist = ",".join(str(c) for c in codlist)
-        if type == 0:
-            Query = f"SELECT tab.cod, tab.ntx, tab.pitxt, tab.elemlen, tab.mappa, tab.numperiod, tab.links, tab.numorg, intbib.sigla, tab.vol, tab.pag, tab.riga, tab.col, tab.tipostanza, tab.stanza, tab.verso, tab.numbrano, lem.spec AS lemma, lem.cat AS cat_gr, lem.omo AS disambiguatore FROM {table} AS tab INNER JOIN intbib ON tab.ntx = intbib.ntx INNER JOIN lem ON tab.indlem = lem.cod WHERE tab.cod IN ({strlist})"
-            extendequeryReponse = pd.read_sql(Query, con)
-            textlist = pd.concat([textlist, extendequeryReponse])
-        elif type == 1:
-            Query = f"SELECT tab.cod, tab.ntx, tab.pitxt, tab.elemlen, tab.mappa, tab.numperiod, tab.links, tab.numorg, intbib.sigla, tab.vol, tab.pag, tab.riga, tab.col, tab.tipostanza, tab.stanza, tab.verso, tab.numbrano, lem.spec AS lemma, lem.cat AS cat_gr, lem.omo AS disambiguatore FROM {table} AS tab INNER JOIN intbib ON tab.ntx = intbib.ntx INNER JOIN lem ON tab.indlem = lem.cod WHERE tab.indlem IN ({strlist})"
-            extendequeryReponse = pd.read_sql(Query, con)
-            textlist = pd.concat([textlist, extendequeryReponse])
-        elif type == 2:
-            subquery = f"SELECT DISTINCT lemma, forma FROM pfl WHERE lemma IN ({strlist})"
-            subdf = pd.read_sql(subquery, con)
-            formcodlist = list(subdf["forma"])
-            strform = ",".join(str(c) for c in formcodlist)
-            Query = f"SELECT tab.cod, tab.ntx, tab.pitxt, tab.elemlen, tab.mappa, tab.numperiod, tab.links, tab.numorg, intbib.sigla, tab.vol, tab.pag, tab.riga, tab.col, tab.tipostanza, tab.stanza, tab.verso, tab.numbrano, lem.spec AS lemma, lem.cat AS cat_gr, lem.omo AS disambiguatore FROM {table} AS tab INNER JOIN intbib ON tab.ntx = intbib.ntx INNER JOIN lem ON tab.indlem = lem.cod WHERE tab.indlem IN ({strlist}) OR (tab.indlem = 0 AND tab.cod IN ({strform}))"
-            extendequeryReponse = pd.read_sql(Query, con)
-            textlist = pd.concat([textlist, extendequeryReponse])
-    return textlist
-
-def findcontexts(textlist, listOcc, path):
-    contexts = []
-    ampiezzacontesto = 31
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    for ind, row in textlist.iterrows():
-        pitxtLocal = row["pitxt"]
-        sigla = row["sigla"]
-        periodlocal = row["numperiod"]
-        ntxlocal = row["ntx"]
-        mappalocal = row["mappa"]
-        pointerlist = pd.DataFrame()
-        for table in listOcc:
-            query = f"SELECT tab.pitxt, tab.elemlen FROM {table} AS tab WHERE tab.ntx = {ntxlocal} AND tab.mappa <= {mappalocal+int(ampiezzacontesto/2)} AND tab.mappa >= {mappalocal-int(ampiezzacontesto/2)}"
-            queryresponse = pd.read_sql(query, con)
-            pointerlist = pd.concat([pointerlist, queryresponse])
-        with open(f"{path}/itxt/{sigla}", 'r', encoding="utf-32-le") as file1:
-            file1.seek(4*pointerlist["pitxt"].min())
-            cont = file1.read(pointerlist["pitxt"].max()-pointerlist["pitxt"].min())
-            contexts.append(cont)
-    textlist['contesto'] = contexts
-    return (textlist.reset_index())
-
-def findbib(contexts, path):
-    infobib = pd.DataFrame()
-    rif_org = pd.DataFrame()
-    for ind, row in contexts.iterrows():
-        con = sqlite3.connect(f"file:{path}/bibliografia/BiblioTLIO.db", uri=True)
-        Query = f"SELECT [Anno iniziale], [Anno finale], [Data codificata], [Titolo Abbreviato], [Autore], [Titolo], [Curatore], [Data descrittiva], [Area generica], [Area specifica], [Genere], [Forma], [Tipo], IQ FROM datibib WHERE Sigla='{row['sigla']}'"
-        bib = pd.read_sql(Query, con)
-        infobib = pd.concat([infobib, bib])
-        con2 = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-        Query2 = f"SELECT head AS Rif_organico, full AS Rif_completo FROM org WHERE (indice='{row['numorg']}' AND ntx='{row['ntx']}')"
-        rif = pd.read_sql(Query2, con2)
-        rif_org = pd.concat([rif_org, rif])
-    annoiniz = list(infobib['Anno iniziale'])
-    annofin = list(infobib['Anno finale'])
-    datacod = list(infobib['Data codificata'])
-    datadesc = list(infobib['Data descrittiva'])
-    titoloabb = list(infobib['Titolo Abbreviato'])
-    autore = list(infobib['Autore'])
-    titolo = list(infobib['Titolo'])
-    curatore = list(infobib['Curatore'])
-    areagen = list(infobib['Area generica'])
-    areaspec = list(infobib['Area specifica'])
-    genere = list(infobib['Genere'])
-    forma = list(infobib['Forma'])
-    tipo = list(infobib['Tipo'])
-    iq = list(infobib['IQ'])
-    rif1 = list(rif_org['Rif_organico'])
-    rif2 = list(rif_org['Rif_completo'])
-    contexts['Anno iniziale'] = annoiniz
-    contexts['Anno finale'] = annofin
-    contexts['Data codificata'] = datacod
-    contexts['Data descrittiva'] = datadesc
-    contexts['Autore'] = autore
-    contexts['Titolo Abbreviato'] = titoloabb
-    contexts['Titolo'] = titolo
-    contexts['Curatore'] = curatore
-    contexts['Area generica'] = areagen
-    contexts['Area specifica'] = areaspec
-    contexts['Genere'] = genere
-    contexts['Forma'] = forma
-    contexts['Tipo'] = tipo
-    contexts ['IQ'] = iq
-    contexts['Rif_organico'] = rif1
-    contexts['Rig_completo'] = rif2
-    contexts.pag = contexts.pag.astype(int)
-    chrono = contexts.sort_values(by=['Anno iniziale', 'Rif_organico', 'pag'])   
-    cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'Autore', 'Titolo',  'Anno iniziale', 'Anno finale', 'Data codificata', 'Data descrittiva', 'Area generica', 'Area specifica', 'Genere', 'Forma', 'Tipo', 'Curatore',  'cod', 'ntx', 'pitxt', 'elemlen', 'mappa', 'numperiod', 'numorg', 'sigla', 'vol', 'col', 'numbrano', 'Rig_completo']
-    clean_df = chrono[cols].reset_index()
-    return clean_df
-
-def highlight (bibliocontexts, path):
-    index = 0
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    for col in bibliocontexts.columns:
-        forme = []
-        if col.startswith('cod'):
-            for ind, row in bibliocontexts.iterrows():
-                Query = f"SELECT spec FROM form WHERE cod={row[col]}"
-                query_answer = pd.read_sql(Query, con)
-                forme += list(query_answer['spec'])
-            if index == 0:
-                bibliocontexts['highlight'] = forme
-            else:
-                bibliocontexts['highlight'+str(index)] = forme
-            index += 1
-    return bibliocontexts
-
-def contestimultipli (tipo_ricerca, ricerca, listOcc, path):
-    textlist = findtexts(tipo_ricerca, ricerca, listOcc, path)
-    contexts = findcontexts (textlist,listOcc, path)
-    bibliocontexts = findbib (contexts, path)
-    highlights = highlight(bibliocontexts, path)
-    return highlights
-
-def singlecontexts(textlist, index, parole, periodi, brani, listOcc, path):
-    context = textlist.iloc[index]
-    contexts = []
-    formats = []
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    sigla = textlist.loc[index, "sigla"]
-    periodlocal = textlist.loc[index, "numperiod"]
-    ntxlocal = textlist.loc[index, "ntx"]
-    mappalocal = textlist.loc[index, "mappa"]
-    linkslocal = textlist.loc[index, "links"]
-    if parole != 0:
-        pointerlist = pd.DataFrame()
-        for table in listOcc:
-            query = f"SELECT tab.pitxt, tab.elemlen FROM {table} AS tab WHERE tab.ntx = {ntxlocal} AND tab.mappa <= {mappalocal+int(parole/2)} AND tab.mappa >= {mappalocal-int(parole/2)}"
-            queryresponse = pd.read_sql(query, con)
-            pointerlist = pd.concat([pointerlist, queryresponse])
-        with open(f"{path}/itxt/{sigla}", 'r', encoding="utf-32-le") as file1:
-            file1.seek(4*pointerlist["pitxt"].min())
-            cont = file1.read(pointerlist["pitxt"].max()-pointerlist["pitxt"].min())
-            contexts.append(cont)
-        with open(f"{path}/ftxt/{sigla}", 'rb') as file1:
-            file1.seek(pointerlist["pitxt"].min()-1)
-            formBytes = file1.read(pointerlist["pitxt"].max()-pointerlist["pitxt"].min())
-            form = [byte for byte in formBytes]
-            formats.append(form)
-            context ['piniz'] = pointerlist["pitxt"].min()
-            context ['pfin'] = pointerlist["pitxt"].max()
-    elif periodi != 0:
-        query = f"SELECT piniz, pfin FROM periodi WHERE ntx = {ntxlocal} AND numperiod <= {periodlocal+int(periodi/2)} AND numperiod >= {periodlocal-int(periodi/2)}"
-        queryresponse = pd.read_sql(query, con)
-        with open(f"{path}/itxt/{sigla}", 'r', encoding="utf-32-le") as file1:
-            file1.seek(4*queryresponse["piniz"].min())
-            cont = file1.read(queryresponse["pfin"].max()-queryresponse["piniz"].min())
-            contexts.append(cont)
-            context ['piniz'] = queryresponse["piniz"].min()
-            context ['pfin'] = queryresponse["pfin"].max()
-    elif brani != 0:
-        if linkslocal == 0 or linkslocal == 1:
-            return "Nessun brano associato a questo contesto"
-        else:
-            numbranolocal = textlist.loc[index, "numbrano"]
-            query = f"SELECT piniz, pfin FROM linkbase WHERE {ntxlocal} = ntx AND tipo = 2 AND id BETWEEN {numbranolocal-int(brani/2)} AND {numbranolocal+int(brani/2)}"
-            queryresponse = pd.read_sql(query, con)
-            with open(f"{path}/itxt/{sigla}", 'r', encoding="utf-32-le") as file1:
-                file1.seek(4*queryresponse["piniz"].min())
-                cont = file1.read(queryresponse["pfin"].max()-queryresponse["piniz"].min())
-                contexts.append(cont)
-                context ['piniz'] = queryresponse["piniz"].min()
-                context ['pfin'] = queryresponse["pfin"].max() 
-    context['contesto'] = contexts [0]
-    context['formattazione'] = formats
-    return pd.DataFrame(context).T.reset_index(drop=True)
-
-
-#%% funzione di ricerca dei brani associati. Ha in input singlecontexts.
-def findlinks (context, path):
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    linkslocal = context.loc[0, "links"]
-    siglalocal = context.loc[0, "sigla"]
-    ntxlocal = context.loc[0, "ntx"]
-    pitxtlocal = context.loc[0, "pitxt"]
-    pinizlocal = context.loc[0, "piniz"]
-    pfinlocal = context.loc[0, "pfin"]
-    if linkslocal == 0:
-        return context
-    if linkslocal == 1:
-        query = f"SELECT ta.ntx, ta.id, ta.piniz, ta.pfin, tb.mappain, tb.mappafin FROM linkbase AS tb INNER JOIN linknoteass AS ta ON tb.ntx = ta.ntx AND tb.id = ta.id WHERE (((tb.tipo= 1) AND (tb.ntx = {ntxlocal})) AND ((tb.piniz BETWEEN {pinizlocal} AND {pfinlocal}) OR ({pitxtlocal} BETWEEN tb.piniz AND tb.pfin)))"
-        queryresponse = pd.read_sql(query, con)
-        with open(f"{path}/itxt/{siglalocal}", 'r', encoding="utf-32-le") as file1:
-                file1.seek(4*queryresponse["piniz"].min())
-                cont = file1.read(queryresponse["pfin"].max()-queryresponse["piniz"].min()-2)
-        context['nota'] = cont
-        return context
-    if linkslocal == 2:
-        query = f"SELECT ta.ntx, ta.id, ta.piniz, ta.pfin, tb.mappain, tb.mappafin FROM linkbase AS tb INNER JOIN linknoteass AS ta ON tb.ntx = ta.ntx AND tb.id = ta.id WHERE (((tb.tipo= 2) AND (tb.ntx = {ntxlocal})) AND ((tb.piniz BETWEEN {pinizlocal} AND {pfinlocal}) OR ({pitxtlocal} BETWEEN tb.piniz AND tb.pfin)))"
-        queryresponse = pd.read_sql(query, con)
-        with open(f"{path}/itxt/{siglalocal}", 'r', encoding="utf-32-le") as file1:
-                file1.seek(4*queryresponse["piniz"].min())
-                cont = file1.read(queryresponse["pfin"].max()-queryresponse["piniz"].min()-2)
-        context['testo associato'] = cont
-    if linkslocal == 3:
-        query = f"SELECT ta.ntx, ta.id, ta.piniz, ta.pfin, tb.piniz AS iniz, tb.pfin AS fin, tb.mappain, tb.mappafin FROM linkbase AS tb INNER JOIN linknoteass AS ta ON tb.ntx = ta.ntx AND tb.id = ta.id WHERE (((tb.tipo= 1) AND (tb.ntx = {ntxlocal})) AND ((tb.piniz BETWEEN {pinizlocal} AND {pfinlocal}) OR ({pitxtlocal} BETWEEN tb.piniz AND tb.pfin)))"
-        queryresponse = pd.read_sql(query, con)
-        with open(f"{path}/itxt/{siglalocal}", 'r', encoding="utf-32-le") as file1:
-                file1.seek(4*queryresponse["piniz"].min())
-                cont = file1.read(queryresponse["pfin"].max()-queryresponse["piniz"].min()-2)
-        context['nota'] = cont
-        query2 = f"SELECT ta.ntx, ta.id, ta.piniz, ta.pfin, tb.piniz AS iniz, tb.pfin AS fin, tb.mappain, tb.mappafin FROM linkbase AS tb INNER JOIN linknoteass AS ta ON tb.ntx = ta.ntx AND tb.id = ta.id WHERE (((tb.tipo= 2) AND (tb.ntx = {ntxlocal})) AND ((tb.piniz BETWEEN {pinizlocal} AND {pfinlocal}) OR ({pitxtlocal} BETWEEN tb.piniz AND tb.pfin)))"
-        queryresponse2 = pd.read_sql(query2, con)
-        with open(f"{path}/itxt/{siglalocal}", 'r', encoding="utf-32-le") as file2:
-                file2.seek(4*queryresponse2["piniz"].min())
-                cont2 = file2.read(queryresponse2["pfin"].max()-queryresponse2["piniz"].min()-2)
-        context['testo associato'] = cont2
-    return context
-
-#%% Ha in input links, associa i riferimenti bibliografici ad ogni contesto.
-def singlefindbib(contexts, path):
-    infobib = pd.DataFrame()
-    rif_org = pd.DataFrame()
-    for ind, row in contexts.iterrows():
-        con = sqlite3.connect(f"file:{path}/bibliografia/BiblioTLIO.db?mode=ro", uri=True)
-        Query = f"SELECT [Anno iniziale], [Titolo Abbreviato], IQ FROM datibib WHERE Sigla='{row['sigla']}'"
-        bib = pd.read_sql(Query, con)
-        infobib = pd.concat([infobib, bib])
-        con2 = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-        Query2 = f"SELECT head AS Rif_organico, full AS Rif_completo FROM org WHERE (indice='{row['numorg']}' AND ntx='{row['ntx']}')"
-        rif = pd.read_sql(Query2, con2)
-        rif_org = pd.concat([rif_org, rif])
-    anno = list(infobib['Anno iniziale'])
-    titolo = list(infobib['Titolo Abbreviato'])
-    iq = list(infobib['IQ'])
-    rif1 = list(rif_org['Rif_organico'])
-    rif2 = list(rif_org['Rif_completo'])
-    contexts['Anno iniziale'] = anno
-    contexts['Titolo Abbreviato'] = titolo
-    contexts ['IQ'] = iq
-    contexts['Rif_organico'] = rif1
-    contexts['Rig_completo'] = rif2
-    contexts.pag = contexts.pag.astype(int)
-    chrono = contexts.sort_values(by=['Anno iniziale', 'Rif_organico', 'pag'])   
-    if 'nota' in chrono.columns and 'testo associato' in chrono.columns:
-        cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'nota', 'testo associato', 'highlight']
-    elif 'nota' in chrono.columns:
-        cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'nota', 'highlight']
-    elif 'testo associato' in chrono.columns:
-        cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'testo associato', 'highlight']
-    else:
-        cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'highlight']
-    chrono = chrono.drop(chrono.columns[0], axis=1)
-    clean_df = chrono.reindex(columns=cols + list(chrono.columns.difference(cols)))
-    return clean_df
-
-# %% funzione contesti singoli
-
-def contestosingolo (contestimultipli, indice, parole, periodi, brani, listOcc, path):
-     contestosingolo = singlecontexts(contestimultipli, indice, parole, periodi, brani, listOcc, path)
-     braniassociati = findlinks(contestosingolo, path)
-     contestosingoloclean = singlefindbib (braniassociati, path)
-     return contestosingoloclean
-
-#%% funzioni decodifica contesti
-
-def GeneraKey (sigla=None):
-    # Genera i parametri di cifratura di un testo
-    valore = [0, 0, 0]
-    origine = None
-    global LengKey, KeyBody
-    con = sqlite3.connect(f"file:{path}/corpus.db?mode=ro", uri=True)
-    query = f"SELECT notea,noteb,notec FROM Intbib WHERE lower(sigla)='{sigla}'"
-    query_answer = pd.read_sql(query, con)
-    valore[0] = int(query_answer['notea'][0])
-    valore[1] = int(query_answer['noteb'][0])
-    valore[2] = int(query_answer['notec'][0])
-    print (valore)
-    dato = valore[0] + valore[1]
-    LengKey = 50 + (valore[2] % 300)
-    if (LengKey // 2) * 2 != LengKey:
-        LengKey = LengKey + 1
-    KeyBody = [0] * LengKey
-    iniziale = dato % (valore[2] + 123)
-    random.seed(iniziale)
-    for k in range(LengKey):
-        KeyBody[k] = int(1000 * random.random())
-path = "/Users/leonardocanova/Library/CloudStorage/OneDrive-ConsiglioNazionaledelleRicerche/TIGRO/Ricerche/db/ndg2.gat4"
-GeneraKey("d17")
-
-#%% funzione cifratura/decifratura
-def CifraS(df, verso):
-    # Cifra o decifra una stringa
-    # StartInFile = posizione, all'interno del testo cifrato, del primo carattere della stringa da cifrare (base 1)
-    # stringa = stringa da cifrare o decifrare
-    # verso = 1 => cifra; 2 => decifra
-    # FirstInStringa = indice del primo byte considerato all'interno del vettore da decifrare
-    # LastInStringa = indice dell'ultimo byte considerato all'interno del vettore da decifrare
-    # PosizInKey = indice del primo carattere da utilizzare all'interno della chiave fissa
-
-    global LengKey, KeyBody
-    print (KeyBody)
-    print(LengKey)
-    StartInFile = df['piniz'][0]
-    stringa = df['contesto'] [0]
-    print(StartInFile, stringa)
-    NumCharsToConv = 0
-    LastInStringa = 0
-    LengKey2 = LengKey // 2
-    while LastInStringa < len(stringa):
-        StartInFile = StartInFile + NumCharsToConv
-        NumKeyAppl = 1 + (StartInFile - 1) // LengKey2
-        FirstInStringa = LastInStringa + 1
-        PosizInKey = StartInFile % LengKey2
-        if PosizInKey == 0:
-            PosizInKey = LengKey2
-        MaxCharsToConv = LengKey - PosizInKey + 1
-        if MaxCharsToConv > LengKey2 - PosizInKey + 1:
-            MaxCharsToConv = LengKey2 - PosizInKey + 1
-        NumCharsToConv = len(stringa) - FirstInStringa + 1
-        if NumCharsToConv > MaxCharsToConv:
-            NumCharsToConv = MaxCharsToConv
-        LastInStringa = FirstInStringa + NumCharsToConv - 1
-        for k in range(FirstInStringa - 1, LastInStringa):
-            if verso == 1:
-                stringa = stringa[:k] + chr(ord(stringa[k]) + KeyBody[PosizInKey-1]) + stringa[k+1:]
-            else:
-                stringa = stringa[:k] + chr(ord(stringa[k]) - KeyBody[PosizInKey-1]) + stringa[k+1:]
-                print("Stringa: "+stringa)
-            PosizInKey += 1
-    return stringa
-
-#%% provine
-testdec = 'ӗЫГҨғϩҘМϩӲѢҨҘ'
-testdec2 = 'ӻ'
-testenc = "recomandaţion"
-testenc2 = "çà"
-testnorm = "fòra"
-path = "/Users/leonardocanova/Library/CloudStorage/OneDrive-ConsiglioNazionaledelleRicerche/TIGRO/Ricerche/db/ndg2.gat4"
-listOcc = get_tables_occ(path)
-ricerca = ricercaforme(interpreter(testenc), path, 1, 0)
-#dtale.show(db_results_decode(ricerca))
-contesti_multipli = contestimultipli(0, ricerca, listOcc, path)
-contesto_singolo = contestosingolo(contesti_multipli, 0, 31, 0, 0, listOcc, path)
-#dtale.show(db_results_decode(contesto_singolo))
-#CifraS(contesto_singolo, 2)
-# %%
-

flask_be/engine/decoder/test_decoder_kora.py

@@ -1,462 +0,0 @@
-# %%
-import csv
-
-'''
-## Premessa 1
-La mia prima versione di convertitore è stata fatta ad occhio. Ora, tornando sulla questione, ho individuato funzioni _built-in_ (e quindi, in teoria, altamente ottimizzate) che fanno il grosso del lavoro: in particolare:
-- int
-- hex
-- chr
-- ord
-'''
-'''
-## Premessa 2
-*Unicode* assegna ad 'ogni' (o meglio: ad un numero parecchio grande di) carattere un codice numerico. Seguendo lo standard, il codice Unicode di un carattere si scrive 'U+' seguito da un numero _esadecimale_ da 4 a 6 cifre (con le prime cifre che possono essere zeri).
-Ad esempio, le lettere latine maiuscole A-Z sono rappresentate dai codici
-
-U+0041 -- U+005A
-
-e le minuscole dai codici
-
-U+0061 -- U+007A .
-
-I codici dei primi 128 caratteri (da U+0000 a U+007F) corrispondono ai codici ASCII degli stessi caratteri.
-
-Questi codici hanno anche una versione _decimale_, che si ottiene semplicemente convertendo il numero dopo 'U+' da base 16 a base 10. Per fare la conversione in GATTO, ci occorrono entrambe le versioni.
-'''
-# %%
-# 1. Le funzioni 'int' e 'hex' permettono di convertire al volo numeri decimali in esadecimali e viceversa.
-
-# Da esadecimale a int:
-
-print('Da base 16 a base 10:', int("AF", 16) )
-
-# Da int a esadecimale:
-
-print ('Da base 10 a base 16 -- notare il prefisso:', hex(175) )
-
-'''
-Note:
-
-1. In 'int', il secondo parametro specifica la base: la funzione può essere usata anche per convertire numeri da altre basi.
-2. Sempre in 'int', l'input va dato come stringa, per evitare che il Python lo interpreti come variabile data la possibile presenza di lettere. La string *non* è case-sensitive.
-3. In 'hex', si può notare che l'output ha un prefisso '0x'. Questo serve per specificare 
-'''
-# Altri esempi:
-print('La stringa in int ignora il prefisso:', int('0xaf', 16) )
-print('e non è case-sensitive:', int('Af', 16) )
-# %%
-# Le funzioni 'ord' e 'chr' convertono un carattere nel suo codice Unicode *DECIMALE* e viceversa.
-
-print( 'Il codice decimale non è (chiaramente) uguale a quello esadecimale, altrimenti il prossimo carattere sarebbe una A:' )
-print( chr(41) )
-
-print( 'Ma combinando chr ed int:' )
-print( chr(int("41", 16)) )
-# %%
-# Credo convenga caricare 'vettSpec' una volta per tutte invece che inserire il caricamento della tabella nella funzione:
-with open("vettSpec.csv", 'r') as file1:
-    reader = csv.DictReader(file1)
-    vettSpec = [row for row in reader]
-# %%
-# Una volta che uno ha vettSpec, la conversione *di un singolo carattere* si fa in 3 passaggi:
-def db_decode(string0):
-    res = ""
-    for char0 in string0:
-        #1
-        char0Dec = ord(char0) # Dal carattere al codice Unicode DECIMALE corrispondente
-        #2
-        char0ConvDec = next((el['unicode'] for el in vettSpec if el['intcode'] == str(char0Dec)), None) # Il codice DECIMALE (passato come stringa) viene ricercato in vettSpec, ritornando l'Unicode ESADECIMALE del carattere decriptato o None se non c'è riscontro -- il che non DOVREBBE succedere.
-        #3
-        res += chr(int(char0ConvDec, 16)) # Si converte il codice esadecimale a decimale e si usa la built-in chr per recuperare il carattere
-    return res
-
-def db_encode(string0):
-    res = ""
-    for char0 in string0:
-        #1
-        char0Hex = hex(ord(char0)) # Dal carattere al codice Unicode ESADECIMALE corrispondente
-        #2
-        char0ConvDec = next((el['intcode'] for el in vettSpec if el['unicode'] == char0Hex[2:].upper()), None) # Il codice ESADECIMALE, senza il prefisso '0x' (rimosso tramite [2:]) e convertito in maiuscole per rispettare il formato di vettSpec, viene ricercato in vettSpec, ritornando l'Unicode DECIMALE del carattere criptato o None se non c'è riscontro -- il che non DOVREBBE succedere.
-        #3
-        res += chr(int(char0ConvDec)) # Si usa la built-in chr per recuperare il carattere
-    return res
-# %%
-# Test:
-testEncrNorm = 'КѢӗГԂғМϩϩ'
-testEncrSpec = 'ГѢӗГԂғМϩϩ'
-
-testDecrNorm = db_decode(testEncrNorm)
-testDecrSpec = db_decode(testEncrSpec)
-print( testDecrNorm )
-print( testDecrSpec )
-
-print( db_encode(testDecrNorm) )
-print( db_encode(testDecrSpec) )
-# %%
-# Altri test:
-testdec = 'ӗЫГҨғϩҘМϩӲѢҨҘ'
-testenc = "recomandaţion"
-testdec2 = 'ӻ'
-testenc2 = "çà"
-print( db_decode(testdec) )
-print( db_encode(testenc) )
-print( db_decode(testdec2) )
-print( db_encode(testenc2) )
-# %%
-# La prova sui testi!
-# %%
-def GenerateKeyParam(sigla, parametersObj):
-    vals = []
-    vals.append(parametersObj[sigla]['notea'])
-    vals.append(parametersObj[sigla]['noteb'])
-    vals.append(parametersObj[sigla]['notec'])
-    partial = vals[0] + vals[1]
-    keyLength = 50 + (vals[2] % 300)
-    if (keyLength // 2) * 2 != keyLength:
-        keyLength = keyLength + 1
-    seed = partial % (vals[2] + 123)
-    return seed, keyLength
-# %%
-priva = {'p07': {'notea': 557968080, 'noteb': 8457403318, 'notec': 561881}}
-
-print( GenerateKeyParam('p07', priva) )
-
-with open("key_p07.csv", 'r') as file1:
-    aaa = csv.reader(file1)
-    key_p07 = [int(val[0]) for val in aaa]
-
-with open('../../../db/ndg2.gat4/itxt/p07', 'rb') as file1:
-    file1.seek(4)
-    p07 = file1.read().decode(encoding="utf-32-le")
-# %%
-def code(char0, shift):
-    return chr(ord(char0) + shift)
-
-def decodeText(text, key, startInFile):
-    initialOffset = startInFile % len(key)
-    res = ""
-    for k, char0 in enumerate(text):
-        offset = k + initialOffset
-        if offset >= len(key):
-            offset = offset % len(key)
-        res += code(char0, -key[offset])
-    return res
-# %%
-p07micro = p07[:100]
-
-ii = 0
-for char in p07micro:
-    ii = ii+1
-    if ii>20:
-        break
-    print(ii, ord(char), char)
-# %%
-decodeText(p07micro, key_p07, 6)
-# %%
-def CifraS(stringa, StartInFile, key, verso):
-    # Cifra o decifra una stringa
-    # StartInFile = posizione, all'interno del testo cifrato, del primo carattere della stringa da cifrare (base 1)
-    # stringa = stringa da cifrare o decifrare
-    # verso = 1 => cifra; 2 => decifra
-    # FirstInStringa = indice del primo byte considerato all'interno del vettore da decifrare
-    # LastInStringa = indice dell'ultimo byte considerato all'interno del vettore da decifrare
-    # PosizInKey = indice del primo carattere da utilizzare all'interno della chiave fissa
-
-    NumCharsToConv = 0
-    LastInStringa = 0
-    LengKey2 = len(key) // 2
-    while LastInStringa < len(stringa):
-        StartInFile = StartInFile + NumCharsToConv
-        NumKeyAppl = 1 + (StartInFile - 1) // LengKey2
-        FirstInStringa = LastInStringa + 1
-        PosizInKey = StartInFile % LengKey2
-        if PosizInKey == 0:
-            PosizInKey = LengKey2
-        MaxCharsToConv = len(key) - PosizInKey + 1
-        if MaxCharsToConv > LengKey2 - PosizInKey + 1:
-            MaxCharsToConv = LengKey2 - PosizInKey + 1
-        NumCharsToConv = len(stringa) - FirstInStringa + 1
-        if NumCharsToConv > MaxCharsToConv:
-            NumCharsToConv = MaxCharsToConv
-        LastInStringa = FirstInStringa + NumCharsToConv - 1
-        for k in range(FirstInStringa - 1, LastInStringa):
-            if verso == 1:
-                stringa = stringa[:k] + chr(ord(stringa[k]) + key[PosizInKey-1]) + stringa[k+1:]
-            else:
-                stringa = stringa[:k] + chr(ord(stringa[k]) - key[PosizInKey-1]) + stringa[k+1:]
-                print("Stringa: "+stringa)
-            PosizInKey += 1
-    return stringa
-# %%
-CifraS(p07micro, 1, key_p07, 1)
-# %%
-## ANCORA!
-###
-# %%
-def code(char0, shift):
-    return chr(ord(char0) + shift)
-
-def decodeText(text, key, startInFile):
-    initialOffset = startInFile % len(key)
-    res = ""
-    for k, char0 in enumerate(text):
-        offset = k + initialOffset
-        if offset >= len(key):
-            offset = offset % len(key)
-        res += code(char0, -key[offset])
-    return res
-
-def CifraS(stringa, StartInFile, key, verso):
-    # Cifra o decifra una stringa
-    # StartInFile = posizione, all'interno del testo cifrato, del primo carattere della stringa da cifrare (base 1)
-    # stringa = stringa da cifrare o decifrare
-    # verso = 1 => cifra; 2 => decifra
-    # FirstInStringa = indice del primo byte considerato all'interno del vettore da decifrare
-    # LastInStringa = indice dell'ultimo byte considerato all'interno del vettore da decifrare
-    # PosizInKey = indice del primo carattere da utilizzare all'interno della chiave fissa
-
-    NumCharsToConv = 0
-    LastInStringa = 0
-    LengKey2 = len(key) // 2
-    while LastInStringa < len(stringa):
-        StartInFile = StartInFile + NumCharsToConv
-        #NumKeyAppl = 1 + (StartInFile - 1) // LengKey2
-        FirstInStringa = LastInStringa + 1
-        PosizInKey = StartInFile % LengKey2
-        if PosizInKey == 0:
-            PosizInKey = LengKey2
-        MaxCharsToConv = len(key) - PosizInKey + 1
-        if MaxCharsToConv > LengKey2 - PosizInKey + 1:
-            MaxCharsToConv = LengKey2 - PosizInKey + 1
-        NumCharsToConv = len(stringa) - FirstInStringa + 1
-        if NumCharsToConv > MaxCharsToConv:
-            NumCharsToConv = MaxCharsToConv
-        LastInStringa = FirstInStringa + NumCharsToConv - 1
-        for k in range(FirstInStringa - 1, LastInStringa):
-            if verso == 1:
-                stringa = stringa[:k] + chr(ord(stringa[k]) + key[PosizInKey-1]) + stringa[k+1:]
-            else:
-                stringa = stringa[:k] + chr(ord(stringa[k]) - key[PosizInKey-1]) + stringa[k+1:]
-                #print("Stringa: "+stringa)
-            PosizInKey += 1
-    return stringa
-# %%
-# Tira fuori la chiave A FORZA!
-with open('../../../db/ndg2.gat4/itxt/p07', 'rb') as file1:
-    file1.seek(4)
-    p07_enc = file1.read().decode(encoding="utf-32-le")
-with open('../../../db/first_db/itxt/p07', 'rb') as file1:
-    file1.seek(4)
-    p07_dec = file1.read().decode(encoding="utf-32-le")
-# %%
-# Stesso testo? Check lunghezza!
-len(p07_enc)==len(p07_dec)
-# %%
-ii = 0
-for char in p07_dec[:1000]:
-    ii = ii+1
-    if ii>20:
-        break
-    print(ii, ord(char), char)
-caz_dec = [ord(char) for char in p07_dec[:1000]]
-caz_enc = [ord(char) for char in p07_enc[:1000]]
-# %%
-appela = []
-for i in range(len(caz_dec)):
-    appela.append(caz_enc[i] - caz_dec[i])
-# %%
-with open('matto.csv', 'w') as file1:
-    wtr = csv.writer(file1)
-    for row in appela:
-        wtr.writerow([row])
-# %%
-affa = appela[:332]
-nculo = appela[332:664]
-# %%
-affa == nculo
-# %%
-min(appela)
-# %%
-with open('furioso.csv', 'w') as file1:
-    wtr = csv.writer(file1)
-    for row in appela[:332]:
-        wtr.writerow([row])
-# %%
-# Ok, 'furioso.csv' è -- sperabilmente -- la chiave
-# Riapro furioso
-
-with open('furioso.csv', 'r') as file1:
-    rdr = csv.reader(file1)
-    affa2 = [int(row[0]) for row in rdr]
-# %%
-decodeText(p07_enc[:100], affa2, 0)
-# %%
-chiaro = decodeText(p07_enc, affa2, 0)
-print(chiaro)
-# %%
-CifraS(p07_enc[:100], 1, affa2, 2) == decodeText(p07_enc[:100], affa2, 0)
-
-# ... e funziona!
-# %%
-'''
-
-Programmino in VB che DOVREBBE tirar fuori la chiave (è copiato praticamente verbatim da GeneraKey di Gatto4), ma non lo fa -- differenza di implementazione di Rnd? Altro?
-
-Module VBModule
-    Sub Main()
-      Dim k, a, dato, iniziale, valore(3) As Integer
-      Dim LengKey, KeyBody() as Integer 
-      
-      valore(1) = 557968080
-      valore(2) = 845740318
-      valore(3) = 561881
-
-      dato = valore(1) + valore(2)
-      LengKey = 50 + (valore(3) Mod (300))
-      If (LengKey \ 2) * 2 <> LengKey Then LengKey = LengKey + 1
-      ReDim KeyBody(LengKey)
-      iniziale = dato Mod (valore(3) + 123)
-      a = Rnd(-1)
-      Randomize(iniziale)
-      Console.WriteLine("Iniziale: " + Str(iniziale))
-      Console.WriteLine("Lunghezza chiave: " + Str(LengKey))
-      For k = 1 To LengKey
-         KeyBody(k) = 1000 * Rnd()
-         Console.WriteLine(Str(k) + ": " + Str(KeyBody(k)))
-      Next k
-    End Sub
-End Module
-
-'''
-# %%
-# Un esperimento
-
-
-aVB = 1140671485
-cVB = 12820163
-mVB = 2**24
-
-aMS = 214013
-cMS = 2531011
-mMS = 2**31
-
-class randomLCG:
-    def __init__(self, a=134775813, c=1, m=2**32, seed=0):
-        self.seed = seed
-        self._initial_seed = seed
-        self.a = a
-        self.c = c
-        self.m = m
-    
-    def random(self):
-        pre = (self.a*self.seed + self.c) % self.m
-        self.seed = pre
-        return pre/self.m
-    
-    def setSeed(self, seed):
-        self.seef = seed
-
-    def reset(self):
-        self.seed = self._initial_seed
-# %%
-seed0 = 384410
-rnd1 = randomLCG(seed=seed0)
-rnd2 = randomLCG(aVB, cVB, mVB, seed0+327680)
-rnd3 = randomLCG(aMS, cMS, mMS, seed=seed0)
-# %%
-rnd1.reset()
-for ind in range(4):
-    print( round(1000*rnd1.random()) )
-# %%
-rnd2.reset()
-for ind in range(4):
-    print( round(1000*rnd2.random()) )
-# %%
-rnd3.reset()
-for ind in range(4):
-    print( round(1000*rnd3.random()) )
-# %%
-
-# THE LAST TEST
-import csv
-
-def getKeyByCode(keyFile):
-    with open(keyFile, 'r') as file1:
-        reader = csv.reader(file1)
-        key = [int(row[0]) for index, row in enumerate(reader) if index>1]
-        # Apparently, only the first half of the key is actually used!
-        halfKeyLen = len(key)//2
-        key=key[:halfKeyLen]
-        return key
-
-def decodeTextByKey(text, key, startInFile):
-    initialOffset = startInFile % len(key)
-    res = ""
-    for k, char0 in enumerate(text):
-        offset = k + initialOffset
-        if offset >= len(key):
-            offset = offset % len(key)
-        try:
-            res += shiftchar(char0, -key[offset])
-        except:
-            res+=' -- Error in key!'
-            break
-    return res
-#
-def codeTextByKey(text, key, startInFile):
-
-    initialOffset = startInFile % len(key)
-    res = ""
-    for k, char0 in enumerate(text):
-        offset = k + initialOffset
-        if offset >= len(key):
-            offset = offset % len(key)
-        try:
-            res += shiftchar(char0, +key[offset])
-        except:
-            res+=' -- Error in key!'
-            break
-    return res
-#
-def shiftchar(char0, shift):
-    return chr(ord(char0) + shift)
-
-# %%
-from os import listdir
-
-keyPath = 'keys/'
-itxtPath = '../../../db/ndg2.gat4/itxt/'
-
-files = listdir(keyPath)
-keyFiles = [file for file in files if (file.startswith('key_') and file.endswith('.csv'))]
-
-keys = {}
-files = {}
-for keyFile in keyFiles:
-    code = keyFile.replace('key_', '').replace('.csv', '')
-    try:
-        keys[code] = getKeyByCode(keyPath+keyFile)
-        with open('../../../db/ndg2.gat4/itxt/'+code, 'rb') as file1:
-            file1.seek(4)
-            files[code] = file1.read().decode(encoding="utf-32-le")
-    except:
-        pass
-#
-codes = keys.keys()
-# %%
-import random
-
-decoded = {}
-for ind, code in enumerate(codes):
-    rand1 = random.randint(1, 15)
-    rand2 = random.randint(1, 15)+500
-    decoded[code] = decodeTextByKey(files[code][rand1:rand2], keys[code], rand1)
-    print(ind, code)
-    print(decoded[code])
-    print()
-# %%
-codes
-# %%
-decoded['fq']
-# %%

flask_be/engine/decoder/vettSpec.csv

@@ -1,7785 +0,0 @@
-intcode,unicode
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flask_be/engine/test/format.py

@@ -1,35 +0,0 @@
-
-# %%
-import sqlite3
-import pandas as pd
-import dtale
-import unicodedata
-
-with open("../db/ftxt/aa1", 'rb') as file1:
-    formByte = file1.read()
-    form = [byte for byte in formByte]
-# %%
-form
-# %%
-list( filter(lambda el: el>0, appa) ) 
-# %%
-for index, byte in enumerate(appa):
-    if byte > 0:
-        print(index, byte)
-# %%
-with open("../db/itxt/aa1", 'r', encoding="utf-32-le") as file1:
-    file1.seek(4*179)
-    text = file1.read(188-179 + 1)
-    print(text)
-# %%
-with open("../db/itxt/aa1", 'r', encoding="utf-32-le") as file1:
-    textfull = file1.read()
-# %%
-text[179:188]
-# %%
-len(appa)
-# %%
-len(text)
-# %%
-textfull[179+1:188+1]
-# %%

flask_be/engine/test/more_tests_kora/engine/basic_queries.py

@@ -1,162 +0,0 @@
-#%%
-from .parsing_utilities import interpreter, inizialeraddoppiata, list_normalize
-
-# Basic data provider class; can be instantiated to handle different kinds
-# of data-providing connections or interfaces based on config options
-from .data_interface.data_providers_setup import queryHandlerFactory
-
-import pandas as pd
-
-# Main class for basic queries contains:
-# - a data provider instance
-# - methods to submit queries to the data provider instance
-class basicQueries:
-
-    def __init__(self, dataConfig):
-        self.queryHandler = queryHandlerFactory(dataConfig)
-        self.listOcc = dataConfig.get('listOcc')
-
-    # Prepares and sends query OBJECTS which will be processed by the data provider
-    def sendBasicQuery(self, text, queryType, espansa, raddoppiata, pandas=False, dbFile=None):
-        
-        entries = interpreter(text)
-        
-        data = entries
-        dataNorm = []
-        if raddoppiata==1:
-            data = entries + inizialeraddoppiata(entries)
-        if espansa==1 and raddoppiata==0:
-            dataNorm = list_normalize(entries)
-        elif espansa==1 and raddoppiata==1:
-            dataNorm = entries + list_normalize(inizialeraddoppiata(entries))
-
-        return self.queryHandler.query({'data': data, 'dataNorm': dataNorm, 'queryType': queryType}, pandas, dbFile)
-    
-    #%% ha in input le funzioni di ricerca, cerca nell'occorrenziario i puntatori ai contesti e altri elementi ad essi associati. 
-    #l'attributo type definisce il tipo di ricerca in input (0 per forme, 1 per lemmi, 2 per lemmi con opzione "mostra occorrenze non lemmatizzate")
-    def findtexts(self, type, df, index = None):
-        if index is None:
-            df = pd.DataFrame(df)
-        else:
-            if isinstance(index, range):
-                index = list(index)
-            elif not isinstance(index, list):
-                index = [index]
-            df = pd.DataFrame(df.loc[index])
-        textlist = pd.DataFrame()
-        codList = list(df["cod"])
-        listOcc = self.listOcc
-        
-        queryData = {'queryType': 'texts', 'querySubtype': type, 'codList': codList}
-
-        for table in listOcc:
-            queryData['table'] = table
-            if type==2:
-                subQueryData = {'queryType': 'pfl', 'codList': codList}
-                subdf = self.queryHandler.query(subQueryData, pandas=True)
-                queryData['formCodList'] = list(subdf["forma"])
-
-            extendequeryReponse = self.queryHandler.query(queryData, pandas=True)
-
-            textlist = pd.concat([textlist, extendequeryReponse])
-
-        return textlist
-
-    # %% ha in input findtexts, restituisce i contesti associati agli elementi localizzati.
-    # Il range dei contesti è impostato di default a 30 parole e può essere rimodulato nel passaggio al contesto singolo.
-
-    def findcontexts(self, textlist):
-        parole = 31
-        listOcc = self.listOcc
-        contexts = []
-        for ind, row in textlist.iterrows():
-            sigla = row["sigla"]
-            queryData = {'queryType': 'contexts', 'ntxlocal': row["ntx"], 'mappalocal': row['mappa'], 'parole': parole}
-            pointerlist = pd.DataFrame()
-            for table in listOcc:
-                queryData['table'] = table
-                queryresponse = self.queryHandler.query(queryData, pandas=True)
-                pointerlist = pd.concat([pointerlist, queryresponse])
-            
-            fileQueryData = {'sigla': sigla, 'minChar': pointerlist["pitxt"].min(), 'maxChar': pointerlist["pitxt"].max()}
-            cont = self.queryHandler.textQuery(fileQueryData)
-            contexts.append(cont)
-        textlist['contesto'] = contexts
-        return (textlist.reset_index(drop=True))
-
-    # %% Ha in input findcontexts, associa i riferimenti bibliografici ad ogni contesto.
-
-    def findbib(self, contexts):
-        infobib = pd.DataFrame()
-        rif_org = pd.DataFrame()
-        for ind, row in contexts.iterrows():
-            queryData = {'queryType': 'bib', 'row': row}
-            bib = self.queryHandler.query(queryData, pandas=True, dbFile='bibliografia/BiblioTLIO.db')
-            infobib = pd.concat([infobib, bib])
-            queryData = {'queryType': 'rif', 'row': row}
-            rif = self.queryHandler.query(queryData, pandas=True)
-            rif_org = pd.concat([rif_org, rif])
-        annoiniz = list(infobib['Anno iniziale'])
-        annofin = list(infobib['Anno finale'])
-        datacod = list(infobib['Data codificata'])
-        datadesc = list(infobib['Data descrittiva'])
-        titoloabb = list(infobib['Titolo Abbreviato'])
-        autore = list(infobib['Autore'])
-        titolo = list(infobib['Titolo'])
-        curatore = list(infobib['Curatore'])
-        areagen = list(infobib['Area generica'])
-        areaspec = list(infobib['Area specifica'])
-        genere = list(infobib['Genere'])
-        forma = list(infobib['Forma'])
-        tipo = list(infobib['Tipo'])
-        iq = list(infobib['IQ'])
-        rif1 = list(rif_org['Rif_organico'])
-        rif2 = list(rif_org['Rif_completo'])
-        contexts['Anno iniziale'] = annoiniz
-        contexts['Anno finale'] = annofin
-        contexts['Data codificata'] = datacod
-        contexts['Data descrittiva'] = datadesc
-        contexts['Autore'] = autore
-        contexts['Titolo Abbreviato'] = titoloabb
-        contexts['Titolo'] = titolo
-        contexts['Curatore'] = curatore
-        contexts['Area generica'] = areagen
-        contexts['Area specifica'] = areaspec
-        contexts['Genere'] = genere
-        contexts['Forma'] = forma
-        contexts['Tipo'] = tipo
-        contexts ['IQ'] = iq
-        contexts['Rif_organico'] = rif1
-        contexts['Rig_completo'] = rif2
-        contexts.pag = contexts.pag.astype(int)
-        chrono = contexts.sort_values(by=['Anno iniziale', 'Rif_organico', 'pag'])   
-        cols = ['links','Titolo Abbreviato', 'Rif_organico', 'tipostanza', 'stanza', 'verso', 'pag', 'riga', 'IQ', 'lemma', 'cat_gr', 'disambiguatore', 'contesto', 'Autore', 'Titolo',  'Anno iniziale', 'Anno finale', 'Data codificata', 'Data descrittiva', 'Area generica', 'Area specifica', 'Genere', 'Forma', 'Tipo', 'Curatore', 'ntx', 'pitxt', 'elemlen', 'mappa', 'numperiod', 'numorg', 'sigla', 'vol', 'col', 'numbrano', 'Rig_completo', 'cod']
-        clean_df = chrono.reindex(columns=cols + list(chrono.columns.difference(cols)))
-        return (clean_df.reset_index(drop=True))
-    
-    #%% funzione stringa/stringhe da evidenziare
-
-    def highlight (self, bibliocontexts):
-        index = 0
-        for col in bibliocontexts.columns:
-            forme = []
-            if col.startswith('cod'):
-                for ind, row in bibliocontexts.iterrows():
-                    queryData = {'queryType': 'highlight', 'row': row, 'col': col}
-                    forma = self.queryHandler.query(queryData, pandas=True)
-                    forme += list(forma['spec'])        
-                if index == 0:
-                    bibliocontexts['highlight'] = forme
-                else:
-                    bibliocontexts['highlight'+str(index)] = forme
-                index += 1
-        return bibliocontexts
-
-    #%% funzione contesti multipli cumulativa
-
-    def contestimultipli (self, tipo_ricerca, ricerca, index = None):
-        textlist = self.findtexts(tipo_ricerca, ricerca, index)
-        contexts = self.findcontexts (textlist)
-        bibliocontexts = self.findbib (contexts)
-        highlights = self.highlight(bibliocontexts)
-        return highlights

flask_be/engine/test/more_tests_kora/engine/cooccorrenze.py

@@ -1,97 +0,0 @@
-# %%
-import pandas as pd
-import time
-
-from .basic_queries import basicQueries
-
-
-# Executes query sequences to recover contexts with co-occurrences according to user input
-# Returns Pandas dataframes
-class cooccorrenze(basicQueries):
-    
-    def __init__(self, dataConfig):
-        super().__init__(dataConfig)
-
-#%% funzione ricerca per cooccorrenze. 
-    # Ha in input un array del tipo [forma/lemma_cercati, tipo_ricerca, ricerca_espansa, iniziale_raddoppiata].
-    # l'attributo tipo_ricerca definisce il tipo di ricerca in input (0 per forme, 1 per lemmi, 2 per lemmi con opzione "mostra occorrenze non lemmatizzate").
-    # Permette di definire l'intervallo di ricerca (in numero di parole), la possibilità di cercare soltanto all'interno dello stesso periodo (0/1) e/o di cercare le occorrenze in modo ordinato (0/1)
-    
-    def ricerca_cooccorrenze (self, listaricerche, intervallo, periodo, ordinate):
-        listatesti = pd.DataFrame()
-        cod = 1
-        if listaricerche[0][1] == 0:
-            ricerca = self.sendBasicQuery(listaricerche[0][0], 'forma', listaricerche[0][2], listaricerche[0][3], pandas=True)
-            listatesti = self.findtexts(0, ricerca)
-        elif listaricerche[0][1] == 1:
-            ricerca = self.sendBasicQuery(listaricerche[0][0], 'lemma', listaricerche[0][2], listaricerche[0][3], pandas=True)
-            listatesti = self.findtexts(1, ricerca)
-        elif listaricerche[0][1] == 2:
-            ricerca = self.sendBasicQuery(listaricerche[0][0], 'lemma', listaricerche[0][2], listaricerche[0][3], pandas=True)
-            listatesti = self.findtexts(2, ricerca)
-        
-        if listatesti.empty:
-            return []
-
-        for ricerca, tipo, espansa, raddoppiata in listaricerche[1:]:
-            if tipo == 0:
-                search = self.sendBasicQuery(ricerca, 'forma', espansa, raddoppiata, pandas=True)
-            elif tipo == 1:
-                search = self.sendBasicQuery(ricerca, 'lemma', espansa, raddoppiata, pandas=True)
-            elif tipo == 2:
-                search = self.sendBasicQuery(ricerca, 'lemma', espansa, raddoppiata, pandas=True)
-     
-            textlist = self.findtexts(tipo, search)
-            df_new = pd.DataFrame(columns=list(listatesti.columns))
-            cod_cols = []
-
-            t1 = time.time()
-            ##########################################
-            # KORA: questo blocco sembra troppo lento!
-            ##########################################
-#             for index1, row1 in listatesti.iterrows():
-#                 for index2, row2 in textlist.iterrows():
-#                     cond1 = row1['ntx'] == row2['ntx']
-#                     cond2 = row1['numperiod'] == row2['numperiod'] if periodo == 1 else True
-#                     cond3 = ((row1['mappa'] - row2['mappa']) != 0) and ((row1['mappa'] - row2['mappa']) in range(-intervallo, intervallo)) if ordinate == 0 else ((row2['mappa'] - row1['mappa']) > 0) and ((row2['mappa'] - row1['mappa']) <= intervallo)
-
-#                     if cond1 and cond2 and cond3:
-#                         row1[f'cod{cod}'] = textlist['cod'].iloc[index2]
-# #                        print (type(textlist.loc[index2, 'cod'].iloc[1]))
-#                         cod_cols.append(f'cod{cod}')
-#                         df_new = pd.concat([df_new, row1.to_frame().T])
-
-            ##########################################
-            # KORA: fino a qui
-            ##########################################
-            t2 = time.time()
-
-            df_new = pd.DataFrame(columns=list(listatesti.columns))
-            for index1, row1 in listatesti.iterrows():
-                ntx1 = row1['ntx']
-                mappa1 = row1['mappa']
-
-                df_temp = textlist[(textlist['ntx'].astype(int) == ntx1) & (textlist['mappa'].astype(int) > mappa1-intervallo)  & (textlist['mappa'].astype(int) < mappa1+intervallo)  & (textlist['mappa'].astype(int) != mappa1)]
-
-                #(textlist['ntx'].astype(int) == ntx1) & (textlist['mappa'].astype(int) in range(mappa1-intervallo, mappa1+intervallo)) & 
-                #& (textlist['mappa'] in range(mappa1-intervallo, mappa1+intervallo)) & (textlist['mappa'] != mappa1)]
-                df_new = pd.concat([df_new, df_temp])
-
-            t3 = time.time()
-            print('Muglio', round(t2 - t1, 1), round(t3 - t2, 1))
-
-
-            listatesti = df_new
-
-            cod += 1
-
-            if listatesti.empty:
-                return []
-            else:
-                contexts = self.findcontexts(listatesti)
-                bibliocontexts = self.findbib(contexts)
-                clean = bibliocontexts.drop_duplicates(subset="contesto")
-                highlights = self.highlight (clean)
-        return  highlights.to_dict(orient='records') # is this slow? CHECK!
-        #return clean.to_json(orient='records') # possibilità alternativa -- molte opzioni possibili!
-

flask_be/engine/test/more_tests_kora/engine/data_interface/QueryHandlerAbstract.py

@@ -1,12 +0,0 @@
-# An abstract class template for query handler factory return object
-# try a 'naive' implementation without using abc
-class QueryHandlerAbstract():
-    def __init__(self):
-        if type(self) is QueryHandlerAbstract:
-            raise Exception("QueryHandlerAbstract is an abstract class and can't be instantiated")
-    
-    def query(self, queryData, pandas=False, dbFile=None):
-        raise Exception("Method not implemented")
-    
-    def textQuery(self, queryData):
-        raise Exception("Method not implemented")