comment_filename = 'comments_data.txt' # where to save the treated comments load_backup = True # Using the file with the saved comments normalized_rep = 1000 # Score normalization ## general normalized_rep = 1000. team = ['null'] bots = [] blacklist = [] # Welcome message print("Start of the run on:", time.asctime(time.localtime(time.time())), '\n') # Get all steemstem votes s = Steem() all_votes = s.get_account_votes("steemstem") # Method to get each post reputation value, and adding it to the associated author def get_scores(excluded=[]): author_scores = {} comment_scores = {} comment_backup = {} # saving a comment score def save(dico, author, val): if not author in excluded: if not author in dico.keys(): dico[author] = [val, 1] else: dico[author] = [dico[author][0] + val, dico[author][1] + 1]
witnessDf=pd.DataFrame(s.get_witnesses_by_vote('',30)) witnesses = witnessDf['owner'].tolist() print(s.get_account('jaredcwillis')['sbd_balance']) print(witnesses) selfVoteslist=[] totalVoteslist=[] ##### #Pulls voting lists for active witnesses #### for currentWitness in witnesses: print(currentWitness) ##### #Count number of total votes and make sure it isn't 0 #### print(len(s.get_account_votes(currentWitness))) if len(s.get_account_votes(currentWitness)) > 0: totalVoteslist.append(len(s.get_account_votes(currentWitness))) ##### #Convert voting activity to csv file, #splitting individual post URLs into author name and title #### tempDf=pd.DataFrame(s.get_account_votes(currentWitness)) tempDf["authorName"], tempDf["postName"] = zip(*tempDf["authorperm"].str.split(pat="/").tolist()) del tempDf["authorperm"] tempDf.to_csv("votes_%s.csv" % currentWitness) ##### #Count number of self votes #### numberSelfvotes=tempDf.authorName.value_counts()[currentWitness] print(numberSelfvotes)