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Cleaned unnecesary code + changed name and url to be unique with priority to verified.csv

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doctor_dev 2025-05-25 10:56:49 +00:00
parent 0adba9be1f
commit 358c8594a6
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2 changed files with 56 additions and 38 deletions
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1
.gitignore vendored
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@ -5,4 +5,5 @@ scripts/__pycache__/**
.env
env/
submissions/submission.csv
venv/

89
scripts/lantern.py
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@ -229,43 +229,60 @@ Maintenance:
newrow=[instance,category,name,url,sensi,desc,'YES','100']
print_colors(f"[+] NEWROW= {newrow}")
# (rest is automatic: status, score, instance is = '' because it is your own instance)
# delete existing entries in verified.csv
vdf_same_url_filter = vdf["URL"] == url # check for same url
vdf_same_url_filter_count = vdf_same_url_filter.sum() # total url matches
if vdf_same_url_filter_count > 0:
print(f"Found {vdf_same_url_filter_count} row(s) with the same url in verified.csv")
for index, row in vdf[vdf_same_url_filter].iterrows():
print_colors(f"[+] ROW[{index}]= {list(row)}")
vdf = vdf[~vdf_same_url_filter].reset_index(drop=True) # keep only entries that do not match filter
print(f"Deleted {vdf_same_url_filter_count} row(s) with the same url in verified.csv")
if desc == '': # if the description is empty = it means that it goes in unverified.csv, so save modified verified.csv file now
vdf.to_csv(verifiedcsvfile, index=False)
# delete existing entries in unverified.csv
uvdf_same_url_filter = uvdf["URL"] == url # check for same url
uvdf_same_url_filter_count = uvdf_same_url_filter.sum() # total url matches
if uvdf_same_url_filter_count > 0:
print(f"Found {uvdf_same_url_filter_count} row(s) with the same url in unverified.csv")
for index, row in uvdf[uvdf_same_url_filter].iterrows():
print_colors(f"[+] ROW[{index}]= {list(row)}")
uvdf = uvdf[~uvdf_same_url_filter].reset_index(drop=True) # keep only entries that do not match filter
print(f"Deleted {uvdf_same_url_filter_count} row(s) with the same url in unverified.csv")
if desc != '': # if the description isnt empty = it means that it goes in verified.csv, so save modified unverified.csv file now
uvdf.to_csv(unverifiedcsvfile, index=False)
if desc == '': # if the description is empty = it means that it goes in unverified.csv
print("Adding new row in unverified.csv since description is empty")
uvdf.loc[-1] = newrow # adding a row
uvdf.index = uvdf.index + 1 # shifting index
uvdf = uvdf.sort_index() # sorting by index
uvdf = uvdf.sort_values(by=["Category","Score"], ascending=[True,False]) # sorting categories
print_colors("[+] New row added! now writing the csv file")
###### REMOVED THE NEXT CODE - changed this to clean both the verified and unverified csvs
###### from any duplications(will only clean the unverified if no desc)
#
#
# vdf_same_url_filter = vdf["URL"] == url # check for same url
# vdf_same_url_filter_count = vdf_same_url_filter.sum() # total url matches
# if vdf_same_url_filter_count > 0:
# print(f"Found {vdf_same_url_filter_count} row(s) with the same url in verified.csv")
# for index, row in vdf[vdf_same_url_filter].iterrows():
# print_colors(f"[+] ROW[{index}]= {list(row)}")
# vdf = vdf[~vdf_same_url_filter].reset_index(drop=True) # keep only entries that do not match filter
# print(f"Deleted {vdf_same_url_filter_count} row(s) with the same url in verified.csv")
# if desc == '': # if the description is empty = it means that it goes in unverified.csv, so save modified verified.csv file now
# vdf.to_csv(verifiedcsvfile, index=False)
# # delete existing entries in unverified.csv
# uvdf_same_url_filter = uvdf["URL"] == url # check for same url
# uvdf_same_url_filter_count = uvdf_same_url_filter.sum() # total url matches
# if uvdf_same_url_filter_count > 0:
# print(f"Found {uvdf_same_url_filter_count} row(s) with the same url in unverified.csv")
# for index, row in uvdf[uvdf_same_url_filter].iterrows():
# print_colors(f"[+] ROW[{index}]= {list(row)}")
# uvdf = uvdf[~uvdf_same_url_filter].reset_index(drop=True) # keep only entries that do not match filter
# print(f"Deleted {uvdf_same_url_filter_count} row(s) with the same url in unverified.csv")
# if desc != '': # if the description isnt empty = it means that it goes in verified.csv, so save modified unverified.csv file now
# uvdf.to_csv(unverifiedcsvfile, index=False)
##### THIS NEW CODE WILL NOT WORK ON RETRO DATA, ONLY ON NEW ENTRIES AND THEIR DUPLICATIONS AFTER THE CHANGE, please advise if to add or its another issue
# Checks if new input is in verified.csv and prevents if exist
if (vdf['URL'] == url).any() or (vdf['Name'] == name).any():
print("Name or url already exist in verified.csv")
else:
# Delete existing entries from unverified.csv
uvdf = uvdf[(uvdf['URL'] != url) & (uvdf['Name'] != name)]
# if the description is empty = it means that it goes in unverified.csv else it goes in verified.csv
if desc == '':
print("Adding new row in unverified.csv since description is empty")
uvdf.loc[-1] = newrow # adding a row
###DEAD CODE uvdf.index = uvdf.index + 1 # shifting index
###DEAD CODE uvdf = uvdf.sort_index() # sorting by index
uvdf = uvdf.sort_values(by=["Category","Score"], ascending=[True,False]) # sorting categories
print_colors("[+] New row added! now writing the csv file")
else:
print("Adding new row in verified.csv since descriptioln is not empty")
vdf.loc[-1] = newrow # adding a row
###DEAD CODE vdf.index = vdf.index + 1 # shifting index
###DEAD CODE vdf = vdf.sort_index() # sorting by index
vdf = vdf.sort_values(by=["Category","Score"], ascending=[True,False]) # sorting categories
print_colors("[+] New row added! now writing the csv file")
uvdf.to_csv(unverifiedcsvfile, index=False)
else: # if the description isnt empty = it means that it goes in verified.csv
print("Adding new row in verified.csv since description is not empty")
vdf.loc[-1] = newrow # adding a row
vdf.index = vdf.index + 1 # shifting index
vdf = vdf.sort_index() # sorting by index
vdf = vdf.sort_values(by=["Category","Score"], ascending=[True,False]) # sorting categories
print_colors("[+] New row added! now writing the csv file")
vdf.to_csv(verifiedcsvfile, index=False)
choice=input("\n[+] Want to add another website ? (y/n) ")