mirror of
http://git.nowherejezfoltodf4jiyl6r56jnzintap5vyjlia7fkirfsnfizflqd.onion/nihilist/darknet-lantern.git
synced 2025-07-01 19:16:41 +00:00
Fixed conflicts
This commit is contained in:
doctor_dev
commit
35f2c500b8
5 changed files with 215 additions and 146 deletions
2
.gitignore
vendored
2
.gitignore
vendored
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@ -6,4 +6,6 @@ __pycache__/
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env/
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submissions/submission.csv
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venv/
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local_testing/*
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!your_folder/.gitkeep
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@ -533,53 +533,61 @@ Maintenance:
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case 4:
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print_colors("4) Synchronize new links from new or existing webring participants, into your local csv files")
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print_colors('[+] Syncing official webrings to local webrings')
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try:
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webring_df = get_local_webring_participants()
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print_colors('[+] Syncing official webrings to local webrings')
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current_instance = get_current_instance()
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webring_df = get_local_webring_participants()
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for participant in webring_df.itertuples(index=False, name='columns'):
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# Check if the participant is my instance
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if current_instance in participant:
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continue
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current_instance = get_current_instance()
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if not is_participant_reachable(participant.URL):
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print_colors("[-] Webring {participant.URL} isn't reachable, skipping", is_error=True)
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continue
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for participant in webring_df.itertuples(index=False, name='columns'):
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# Check if the participant is my instance
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if current_instance in participant:
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continue
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print_colors('[+] Downloading participant\'s files to store locally')
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lantern.download_participant_data(participant.URL)
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if not is_participant_reachable(participant.URL):
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print_colors("[-] Webring {participant.URL} isn't reachable, skipping", is_error=True)
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continue
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print_colors('[+] Reading local blacklist and sensitive words')
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local_blacklist, local_sensitive = get_local_blacklist_and_sensitive()
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print_colors('[+] Downloading participant\'s files to store locally')
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lantern.download_participant_data(participant.URL)
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print_colors('[+] Reading local verified and unverified')
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local_verified_df, local_unverified_df = get_local_verified_and_unverified()
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print_colors('[+] Reading local blacklist and sensitive words')
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local_blacklist, local_sensitive = get_local_blacklist_and_sensitive()
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participant_url = generate_local_participant_dir(participant.URL)
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print_colors('[+] Reading local verified and unverified')
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local_verified_df, local_unverified_df = get_local_verified_and_unverified()
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print_colors('[+] Reading webrring participant\'s verified and unverified, and removing unverified and blacklisted rows')
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participant_verified_df = lantern.clean_csv(pd.read_csv(f'{participant_url}verified.csv'), local_blacklist)
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participant_unverified_df = lantern.clean_csv(pd.read_csv(f'{participant_url}unverified.csv'), local_blacklist)
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participant_url = generate_local_participant_dir(participant.URL)
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print_colors('[+] Marking sensitive rows')
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participant_verified_df = lantern.mark_sensitive(participant_verified_df, local_sensitive)
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participant_unverified_df = lantern.mark_sensitive(participant_unverified_df, local_sensitive)
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print_colors('[+] Reading webrring participant\'s verified and unverified')
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participant_verified_df, participant_unverified_df = get_participant_local_verified_and_unverified(participant_url)
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if participant.Trusted == 'YES':
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print_colors('[+] This participant is trusted, copying participant\'s verified to local verified')
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local_verified_df = merge_verification_df(local_verified_df, participant_verified_df)
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print_colors('[+] Removing unvalidated and blacklisted rows')
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participant_verified_df = lantern.clean_csv(participant_verified_df, local_blacklist)
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participant_unverified_df = lantern.clean_csv(participant_unverified_df, local_blacklist)
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else:
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print_colors('[+] This participant is not trusted, copying participant\'s verified to local unverified')
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local_unverified_df = merge_verification_df(local_unverified_df, participant_verified_df)
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print_colors('[+] Marking sensitive rows')
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participant_verified_df = lantern.mark_sensitive(participant_verified_df, local_sensitive)
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participant_unverified_df = lantern.mark_sensitive(participant_unverified_df, local_sensitive)
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print_colors('[+] Copying participant\'s unverified to local unverified')
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local_unverified_df = merge_verification_df(local_unverified_df, participant_unverified_df)
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if participant.Trusted == 'YES':
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print_colors('[+] This participant is trusted, copying participant\'s verified to local verified')
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local_verified_df = merge_verification_df(local_verified_df, participant_verified_df)
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print_colors('[+] Saving local verified and unverified')
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save_local_verified_and_unverified(local_verified_df, local_unverified_df)
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else:
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print_colors('[+] This participant is not trusted, copying participant\'s verified to local unverified')
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local_unverified_df = merge_verification_df(local_unverified_df, participant_verified_df)
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print_colors('[+] Copying participant\'s unverified to local unverified')
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local_unverified_df = merge_verification_df(local_unverified_df, participant_unverified_df)
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print_colors('[+] Saving local verified and unverified')
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save_local_verified_and_unverified(local_verified_df, local_unverified_df)
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except Exception as err:
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print_colors("[-] Option 4 failed suddently, please try again", is_error=True)
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break
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@ -997,93 +1005,50 @@ Maintenance:
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case 9:
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print_colors("[+] 9) Cleaning up all duplicates in your own unverified + verified.csv (based on the url)")
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for w in ['verified.csv', 'unverified.csv']:
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csvfilepath = os.path.join(instancepath, w)
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print_colors(f"Processing file: {csvfilepath}")
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try:
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csvdf = pd.read_csv(csvfilepath, on_bad_lines='skip')
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print_colors(f"Removing duplicates in {csvfilepath}")
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#print_colors(f"{csvdf[['URL']]}")
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csvdf = csvdf.drop_duplicates(subset=['URL'], keep="first", inplace=False)
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#print_colors(f"{csvdf[['URL']]}")
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csvdf.to_csv(csvfilepath, index=False)
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print_colors(f"Cleaned data:\n{csvdf[['URL']]}")
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except FileNotFoundError:
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print_colors(f"File not found: {csvfilepath}")
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except Exception as e:
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print_colors(f"An error occurred while processing {csvfilepath}: {e}")
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break
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try:
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print_colors('[+] Reading local verified and unverified')
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verified_df, unverified_df = get_local_verified_and_unverified()
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print_colors('[+] Removing cross dataframe replications')
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verified_df, unverified_df = remove_cross_dataframe_replications(verified_df, unverified_df)
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print_colors('[+] Saving local verified and unverified')
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save_local_verified_and_unverified(verified_df, unverified_df)
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except Exception as err:
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print_colors("[-] Option 9 failed suddently, please try again", is_error=True)
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break
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case 10:
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print_colors("[+] 10) perform sanity checks on all csv files (to mark them as sensitive / or remove the ones that are blacklisted)")
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participantspath = rootpath+'www/participants/'
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for participant in os.listdir(participantspath):
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print_colors(f"Participant: {participant}")
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#read=input("Continue?")
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participantdir= participantspath+participant
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################ BEGIN SANITY CHECKS FOR EACH PARTICIPANTS ##############
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# iterate through the participant's verified.csv and unverified.csv files
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for w in ['verified.csv','unverified.csv']:
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csvfilepath=participantdir+'/'+w
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print_colors(f"{csvfilepath}")
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csvdf = pd.read_csv(csvfilepath, on_bad_lines='skip')
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rows2delete= [] # it is an empty list at first
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for i,j in csvdf.iterrows():
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row=csvdf.loc[i,:].values.tolist()
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#print_colors(f"{row}")
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try:
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print_colors('[+] Reading local blacklist and sensitive words')
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local_blacklist, local_sensitive = get_local_blacklist_and_sensitive()
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for participant in os.listdir(conf.PARTICIPANT_DIR):
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participant_local_dir = conf.PARTICIPANT_DIR + participant + '/'
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################################ SANITY CHECKS ####################################
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### SANITY CHECK 0: make sure that ✔️ and x are replaced with YES/NO, as it changed since v1.0.1 ###
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if csvdf.at[i, 'Status'] == "✔️" or csvdf.at[i, 'Status'] == "YES" :
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csvdf.at[i, 'Status'] = "YES"
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csvdf.to_csv(csvfilepath, index=False)
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else:
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csvdf.at[i, 'Status'] = "NO"
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csvdf.to_csv(csvfilepath, index=False)
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print_colors('[+] Reading webrring participant\'s verified and unverified')
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participant_verified_df, participant_unverified_df = get_participant_local_verified_and_unverified(participant_local_dir)
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if csvdf.at[i, 'Sensitive'] == "✔️" or csvdf.at[i, 'Sensitive'] == "YES" :
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csvdf.at[i, 'Sensitive'] = "YES"
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csvdf.to_csv(csvfilepath, index=False)
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else:
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csvdf.at[i, 'Sensitive'] = "NO"
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csvdf.to_csv(csvfilepath, index=False)
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print_colors('[+] Removing unverified and blacklisted rows')
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participant_verified_df = lantern.clean_csv(participant_verified_df, local_blacklist)
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participant_unverified_df = lantern.clean_csv(participant_unverified_df, local_blacklist)
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### SANITY CHECK 1: Mark all the rows that have incorrect formatting for deletion###
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if IsURLValid(csvdf.at[i, 'Instance']) is False or IsCategoryValid(csvdf.at[i, 'Category']) is False or IsNameValid(csvdf.at[i, 'Name']) is False or IsURLValid(csvdf.at[i, 'URL']) is False or IsStatusValid(csvdf.at[i, 'Sensitive']) is False or IsDescriptionValid(csvdf.at[i, 'Description']) is False or IsStatusValid(csvdf.at[i, 'Status']) is False or IsScoreValid(csvdf.at[i, 'Score']) is False:
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if i not in rows2delete:
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print_colors(f"Marking row {i} for deletion, as it has invalid inputs")
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#print_colors(f"{row}")
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print(IsURLValid(csvdf.at[i, 'Instance']), IsCategoryValid(csvdf.at[i, 'Category']), IsNameValid(csvdf.at[i, 'Name']), IsURLValid(csvdf.at[i, 'URL']), IsStatusValid(csvdf.at[i, 'Sensitive']), IsDescriptionValid(csvdf.at[i, 'Description']), IsStatusValid(csvdf.at[i, 'Status']), IsScoreValid(csvdf.at[i, 'Score']))
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rows2delete.append(i)
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read=input("Continue?")
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print_colors('[+] Marking sensitive rows')
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participant_verified_df = lantern.mark_sensitive(participant_verified_df, local_sensitive)
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participant_unverified_df = lantern.mark_sensitive(participant_unverified_df, local_sensitive)
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### SANITY CHECK 2: Mark all rows that are not allowed (blacklist) for deletion ###
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for k,l in bldf.iterrows():
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blword=bldf.at[k, 'blacklisted-words']
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if any(blword in str(x) for x in row) == True:
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if i not in rows2delete:
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print_colors(f"Marking row {i} for deletion, as it matches with the blacklisted word {blword}")
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rows2delete.append(i)
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#read=input("Continue?")
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### SANITY CHECK 3: Mark all rows that match sensitive words to be sensitive = YES
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for k,l in sedf.iterrows():
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seword=sedf.at[k, 'sensitive-words']
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if any(seword in str(x) for x in row) == True:
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print_colors(f"Marking row {i} as sensitive, as it matches with the sensitive word {seword}")
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csvdf.at[i, 'Sensitive']="YES"
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csvdf.to_csv(csvfilepath, index=False)
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#read=input("Continue?")
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print_colors('[+] Saving local participant verified and unverified')
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save_local_participant_verified_and_unverified(participant_verified_df, participant_unverified_df, participant_local_dir)
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except Exception as err:
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print_colors("[-] Option 10 failed suddently, please try again", is_error=True)
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for i in rows2delete:
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row=csvdf.loc[i,:].values.tolist()
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print_colors(f'[+] REMOVING ROW : {i} {row}')
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csvdf.drop(i, inplace= True)
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csvdf.to_csv(csvfilepath, index=False)
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#read=input("Continue?")
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break
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case 11:
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0
scripts/local_testing/.gitkeep
Normal file
0
scripts/local_testing/.gitkeep
Normal file
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@ -43,7 +43,7 @@ def download_participant_data(participant):
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utils.print_colors(f"[+] Downloaded webring {participant} csv files and banner")
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except Exception:
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except Exception as err:
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print_colors("[-] Downloading webring participant's files failed.", is_error=True)
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def clean_csv(df, blacklist):
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@ -66,7 +66,7 @@ def clean_csv(df, blacklist):
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if not df.empty:
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df = df[df.apply(utils.is_row_valid, axis=1)]
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except Exception:
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except Exception as err:
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print_colors("[-] cleaning dataframe failed", is_error=True)
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return df
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@ -90,7 +90,7 @@ def mark_sensitive(df, sensitive_list):
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df.loc[sensitive_rows, 'Sensitive'] = 'YES'
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df.loc[~sensitive_rows, 'Sensitive'] = 'NO'
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except Exception:
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except Exception as err:
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print_colors("[-] MArking sensitive words failed.", is_error=True)
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return df
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152
scripts/utils.py
152
scripts/utils.py
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@ -152,7 +152,7 @@ def is_participant_reachable(instance):
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status = requests.get(f'{url}{file_name}',proxies=conf.PROXIES, timeout=10).status_code
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if status != 200:
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return False
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except Exception:
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except Exception as err:
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return False
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return True
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@ -278,17 +278,17 @@ def is_row_valid(row):
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"""
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try:
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return (
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IsUrlValid(row['Instance']) and
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IsURLValid(row['Instance']) and
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IsCategoryValid(row['Category']) and
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IsNameValid(row['Name']) and
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IsUrlValid(row['URL']) and
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IsURLValid(row['URL']) and
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IsStatusValid(row['Sensitive']) and
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IsDescriptionValid(row['Description']) and
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IsStatusValid(row['Status']) and
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IsScoreValid(row['Score'])
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)
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except Exception:
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except Exception as err:
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return False
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###################### General ######################
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@ -316,7 +316,7 @@ def merge_verification_df(receiving_df, merging_df):
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else:
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return pd.concat([receiving_df, filtered_df], ignore_index=True)
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except Exception:
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except Exception as err:
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return receiving_df
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def remove_duplications(df):
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@ -333,11 +333,38 @@ def remove_duplications(df):
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df = df.drop_duplicates(subset='Name')
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df = df.drop_duplicates(subset='URL')
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except Exception:
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pass
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except Exception as err:
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print_colors('[-] Removing duplication failed',is_error=True)
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return df
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def remove_cross_dataframe_replications(main_df, sub_df):
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"""
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remove replications from sub_df that exist in main_df
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Parameters:
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main_df (Dataframe): the dataframe to keep replications
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sub_df (Dataframe): the dataframe to remove replications
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Returns:
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Dataframe: the main_df with removed duplications
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Dataframe: the sub_df with removed duplications and removed replications
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"""
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try:
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main_df = remove_duplications(main_df)
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sub_df = remove_duplications(sub_df)
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mask = sub_df['URL'].isin(main_df['URL']) | sub_df['Name'].isin(main_df['Name'])
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sub_df = sub_df[~mask]
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except Exception as err:
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print_colors('[-] Removing cross dataframe duplications failed',is_error=True)
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return main_df, sub_df
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###TODO: can later remove the inputs and have a "global" local verified and unverified or a class of the local(lantern host) participant
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def save_local_verified_and_unverified(verified_df, unverified_df):
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"""
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@ -348,7 +375,7 @@ def save_local_verified_and_unverified(verified_df, unverified_df):
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unverified_df (Dataframe): local unverified rows dataframe
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Returns:
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Dataframe: the combined dataframe will be returned
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bool: True if successful, False if not
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"""
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try:
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current_instance = get_current_instance() + '/'
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@ -357,10 +384,38 @@ def save_local_verified_and_unverified(verified_df, unverified_df):
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unverified_df.to_csv(f'{conf.PARTICIPANT_DIR}{current_instance}unverified.csv', index=False)
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print_colors('[+] Verified and unverified saved successfully')
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return True
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except Exception:
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print_colors('[-] Saving verified and unverified failed',is_error=True )
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except Exception as err:
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print_colors('[-] Saving verified and unverified failed',is_error=True)
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return False
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def save_local_participant_verified_and_unverified(verified_df, unverified_df, participant):
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"""
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saves the local verified and unverified of a participant
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Parameters:
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verified_df (Dataframe): local verified rows dataframe
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unverified_df (Dataframe): local unverified rows dataframe
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participant (str): participant's onion local path
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Returns:
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bool: True if successful, False if not
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"""
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try:
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verified_df.to_csv(f'{participant}verified.csv', index=False)
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unverified_df.to_csv(f'{participant}unverified.csv', index=False)
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print_colors('[+] Verified and unverified saved successfully')
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return True
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||||
except Exception as err:
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print_colors('[-] Saving verified and unverified failed',is_error=True)
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return False
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||||
|
||||
###################### Getters/Generators ######################
|
||||
|
|
@ -390,6 +445,35 @@ def generate_local_participant_dir(participant):
|
|||
|
||||
return f'{conf.PARTICIPANT_DIR}{participant}/'
|
||||
|
||||
def get_participant_local_verified_and_unverified(participant):
|
||||
"""
|
||||
reads the local verified csv and the local unverified csv of a participant
|
||||
|
||||
Parameters:
|
||||
participant (str): participant's local files path
|
||||
|
||||
Returns:
|
||||
verified_df(Dataframe): verified.csv as dataframe
|
||||
unverified_df(Dataframe): unverified.csv as dataframe
|
||||
"""
|
||||
|
||||
try:
|
||||
verified_df = pd.read_csv(f'{participant}verified.csv')
|
||||
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] File not found: verified.csv", is_error=True)
|
||||
return pd.Dataframe(), pd.Dataframe()
|
||||
|
||||
try:
|
||||
unverified_df = pd.read_csv(f'{participant}unverified.csv')
|
||||
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] Participant File not found: unverified.csv", is_error=True)
|
||||
return pd.Dataframe(), pd.Dataframe()
|
||||
|
||||
return verified_df, unverified_df
|
||||
|
||||
|
||||
def get_official_participants():
|
||||
"""
|
||||
reads all the official webring participants
|
||||
|
|
@ -404,7 +488,7 @@ def get_official_participants():
|
|||
with open(conf.OFFICIAL_PARTICIPANTS_FILE, 'r') as file:
|
||||
return [line.strip() for line in file if current_instance not in line]
|
||||
|
||||
except Exception:
|
||||
except Exception as err:
|
||||
print_colors('[-] Couldn\'t read official webring participants file',is_error=True )
|
||||
|
||||
def get_local_blacklist_and_sensitive():
|
||||
|
|
@ -417,22 +501,32 @@ def get_local_blacklist_and_sensitive():
|
|||
"""
|
||||
try:
|
||||
current_instance = get_current_instance() + '/'
|
||||
try:
|
||||
blacklist_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}blacklist.csv')
|
||||
blacklist = blacklist_df.iloc[:, 0].tolist()
|
||||
|
||||
blacklist_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}blacklist.csv')
|
||||
blacklist = blacklist_df.iloc[:, 0].tolist()
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] File not found: blacklist.csv", is_error=True)
|
||||
|
||||
try:
|
||||
sensitive_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}sensitive.csv')
|
||||
sensitive_list = sensitive_df.iloc[:, 0].tolist()
|
||||
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] File not found: sensitive.csv", is_error=True)
|
||||
|
||||
sensitive_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}sensitive.csv')
|
||||
sensitive_list = sensitive_df.iloc[:, 0].tolist()
|
||||
|
||||
return blacklist, sensitive_list
|
||||
|
||||
except Exception:
|
||||
print_colors('[-] Failed reading the blacklist and sensitive words file',is_error=True )
|
||||
return [], []
|
||||
|
||||
except Exception as err:
|
||||
print_colors('[-] Failed reading the blacklist and sensitive words file',is_error=True)
|
||||
|
||||
return [], []
|
||||
|
||||
def get_local_verified_and_unverified():
|
||||
"""
|
||||
reads the local verified csv and the local unverified csv
|
||||
reads the local verified csv and the local unverified csv of the instance
|
||||
|
||||
Returns:
|
||||
verified_df(Dataframe): verified.csv as dataframe
|
||||
|
|
@ -441,16 +535,24 @@ def get_local_verified_and_unverified():
|
|||
|
||||
try:
|
||||
current_instance = get_current_instance() + '/'
|
||||
try:
|
||||
verified_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}verified.csv')
|
||||
|
||||
verified_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}verified.csv')
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] File not found: verified.csv", is_error=True)
|
||||
|
||||
unverified_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}unverified.csv')
|
||||
try:
|
||||
unverified_df = pd.read_csv(f'{conf.PARTICIPANT_DIR}{current_instance}unverified.csv')
|
||||
|
||||
except FileNotFoundError:
|
||||
print_colors("[-] File not found: unverified.csv", is_error=True)
|
||||
|
||||
return verified_df, unverified_df
|
||||
|
||||
except Exception:
|
||||
print_colors('[-] Failed reading the verified and unverified files',is_error=True )
|
||||
return pd.DataFrame(), pd.DataFrame()
|
||||
except Exception as err:
|
||||
print_colors('[-] Failed reading the verified and unverified files',is_error=True)
|
||||
|
||||
return pd.DataFrame(), pd.DataFrame()
|
||||
|
||||
def get_local_webring_participants():
|
||||
"""
|
||||
|
|
@ -474,7 +576,7 @@ def get_local_webring_participants():
|
|||
|
||||
return webring_df
|
||||
|
||||
except Exception:
|
||||
except Exception as err:
|
||||
print_colors(f'[-] failed reading webring participants file',is_error=True )
|
||||
return pd.DataFrame()
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue