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How to use list_domain_names method in localstack

Best Python code snippet using localstack_python

get_cocitation_network.py

Source:get_cocitation_network.py

1import ast2import pandas as pd3pd.options.mode.chained_assignment = None  # default='warn'4import prince5import plotly.express as px6import numpy as np7import time8import networkx as nx9from matplotlib import pyplot as plt10from pandas.api.types import CategoricalDtype11from ural import get_domain_name12from utils import (import_data,13                    save_data,14                    save_figure,15                    save_numpy_array,16                    save_list)17from create_twitter_users_lists import get_lists_and_followers18from sklearn.preprocessing import StandardScaler19from sklearn.decomposition import PCA20def add_type(var1, var2, df):21    list_scientists, list_activists, list_delayers, df_followers = get_lists_and_followers()22    df[var1] = ''23    df[var1] = np.where(df[var2].isin(list_scientists), 'scientist', df[var1])24    df[var1] = np.where(df[var2].isin(list_activists), 'activist', df[var1])25    df[var1] = np.where(df[var2].isin(list_delayers), 'delayer', df[var1])26    return df27def intersection(lst1, lst2):28    lst3 = [value for value in lst1 if value in lst2]29    return lst330def get_tweets():31    df = import_data ('twitter_data_climate_tweets_2022_03_15.csv')32    df = df[~df['query'].isin(['f'])]33    df = add_type('type', 'username', df)34    df['hashtags'] = df['hashtags'].str.lower()35    print('number of tweets', len(df))36    return df37def aggregate_domains_per_user():38    df = get_tweets()39    for index, row in df.iterrows():40        df.at[index, 'domain_name']=ast.literal_eval(row['domain_name'])41    u = df.groupby(['username', 'type'])['domain_name'].apply(list).reset_index(name='list_domain_names')42    #u['list_domain_names'] = u['list_domain_names'].apply(lambda list_items: list({x for l in list_items for x in l}))43    u['list_domain_names'] = u['list_domain_names'].apply(lambda list_items: list(x for l in list_items for x in l))44    list_platforms = ['twitter.com', 'youtube.com', 'bit.ly', ]45    u['list_domain_names'] = u['list_domain_names'].apply(lambda list_items: list(x for x in list_items if x not in list_platforms))46    u['len_list'] = u['list_domain_names'].apply(len)47    u = u.sort_values(by = 'type')48    print(u.info())49    print(u['len_list'].describe())50    return u51def get_cocitation(limit_cocitations):52    timestr = time.strftime('%Y_%m_%d')53    df = aggregate_domains_per_user()54    list_individuals = df['username'].tolist()55    save_list(list_individuals, 'list_individuals_cocitations.txt')56    print(list_individuals[0:10])57    n = len(list_individuals)58    print('number of individuals', n)59    matrix = np.zeros((n,n))60    matrix_lim = np.zeros((n,n))61    for user_i in list_individuals:62        print(user_i)63        for user_j in list_individuals:64            if user_i != user_j:65                i = df.index[df['username'] == user_i]66                j = df.index[df['username'] == user_j]67                a = intersection(df['list_domain_names'].iloc[i[0]], df['list_domain_names'].iloc[j[0]])68                matrix[i,j] = len(a)69                matrix[i,i] = len(df['list_domain_names'].iloc[i[0]])70                matrix_lim[i,i] = 071                if matrix[i,j] > limit_cocitations:72                    matrix_lim[i,j] = 173                else:74                    matrix_lim[i,j] = 075    save_numpy_array(matrix, 'cocitations_{}.npy'.format(timestr))76    #print(matrix)77    #print(matrix_lim[1,:])78    s = np.sum(matrix_lim, axis=1)79    G = nx.from_numpy_matrix(matrix_lim)80    print(G.nodes)81    for index, row in df.iterrows():82        G.nodes[index]['type'] = row['type']83        G.nodes[index]['username'] = row['username']84    nx.write_gexf(G, './data/{}_network_climate_cocitations_{}.gexf'.format(limit_cocitations, timestr))85    #print(G.nodes[0]['type'])86    n_zeros = np.count_nonzero(s==0)87    print(s)88    print(len(s))89    print(n_zeros)90    return matrix91def to_1D(series):92 return pd.Series([x for _list in series for x in _list], name = 'hashtag_count')93def get_hashtags(limit_occurence):94    df = get_tweets()95    df['hashtags'] = df['hashtags'].apply(eval)96    df['len_hashtags']= df['hashtags'].apply(len)97    series = to_1D(df['hashtags']).value_counts()98    df1 = series.to_frame()99    print(df1['hashtag_count'].describe())100    df1.index.name='hashtags'101    #df1['hashtags'] = df1['hashtags'].str.lower()102    df1 = df1.reset_index(level=0)103    df1 = df1[df1['hashtag_count']> limit_occurence]104    print(df1['hashtags'].head(20))105    return df1106def get_hashtags_by_type() :107    df = get_tweets()108    df = df[['username', 'hashtags', 'type_of_tweet', 'id', 'text', 'followers_count', 'type']]109    a = len(df[df['type'].isin(['activist'])])110    b = len(df[df['type'].isin(['delayer'])])111    c = len(df[df['type'].isin(['scientist'])])112    #df = df[~df['type_of_tweet'].isin(['replied_to'])]113    for index, row in df.iterrows():114        df.at[index, 'hashtags']=ast.literal_eval(row['hashtags'])115    df['nb_hashtags'] = df['hashtags'].apply(len)116    print(df['nb_hashtags'].head(20))117    print('number of tw with hashtags', len(df[df['nb_hashtags']>0]))118    df = df.explode('hashtags')119    df = df.dropna(subset=['hashtags'])120    print(df.head(40))121    print('There are', df['hashtags'].nunique(), 'unique hastag')122    print(df.groupby(['type'], as_index = False).size())123    df1 = df[df['nb_hashtags']>0].groupby(['type'], as_index = False).size()124    df1['share_tw_hashtags'] = 0125    df1['share_tw_hashtags'].iloc[0] =  df1['size'].iloc[0]/a126    df1['share_tw_hashtags'].iloc[1] =  df1['size'].iloc[1]/b127    df1['share_tw_hashtags'].iloc[2] =  df1['size'].iloc[2]/c128    print(df1)129    print(df[df['nb_hashtags']>0].groupby(['type'], as_index = False).size())130    return df131if __name__ == '__main__':132    #get_cocitation(limit_cocitations = 30)133    get_hashtags(limit_occurence = 50)...

data_preprocessing.py

Source:data_preprocessing.py

1#!/usr/bin/python22import re, pygeoip3import server_locations4def parseXMLFile( name ):5    file = open( name )6    data = file.read()7    dataLines = data.split( '\n' )8    # Patterns to match9    dirOpenPattern = re.compile(r'<Directory .*>', re.MULTILINE )10    parentDirClosePattern = re.compile(r'^</Directory>', re.MULTILINE )11    subDirClosePattern = re.compile(r'(\s)*</Directory>', re.MULTILINE )12    regexName = re.compile( r'LocalSite .*', re.DOTALL|re.IGNORECASE )13    regexURL = re.compile( r'HttpProxy .*', re.DOTALL|re.IGNORECASE )14    parentDirFlag = False15    subDirFlag = False16    foundLocalSite = False17    foundURLs = False18    parentDirName = ''19    subDirName = ''20    list_domain_names = []21    serverNamesDict = {}22    23    for line in dataLines:24        if not parentDirFlag:25            dirOpenMatch = dirOpenPattern.findall( line )26            if dirOpenMatch:27                parentDirFlag = True28                parentDirName = dirOpenMatch[0].split( '"' )[1][1:3]29                continue30        if not subDirFlag and parentDirFlag:31            assert parentDirFlag32            # Each ParentDir has atleast one Subdir33            dirOpenMatch = dirOpenPattern.findall( line )34            if dirOpenMatch:35                subDirFlag = True36                continue37        if not foundLocalSite and subDirFlag:38            assert subDirFlag and parentDirFlag39            matchName = regexName.findall( line )40            41            if matchName:42                foundLocalSite = True43                x = matchName[0]44                x = x.split()[-1][1:-1]45                subDirName = parentDirName + '/' + x46                continue47    48        if not foundURLs and foundLocalSite:49            assert foundLocalSite and subDirFlag and parentDirFlag50            list_domain_URLs = []51            matchURL = regexURL.findall( line ) 52            if matchURL:53                foundURLs = True54                matchURL = matchURL[0]55                pattern = r'http://.*?:'56                regex = re.compile( pattern, re.DOTALL|re.IGNORECASE )57                match = regex.findall( matchURL )58                match = [ x[:-1] for x in match ]59                serverNamesDict[ subDirName ] = match60                continue61        subDirCloseMatch = subDirClosePattern.findall( line )62        if subDirCloseMatch:63            subDirFlag = False64            foundLocalSite = False65            foundURLs = False66        parentDirCloseMatch = parentDirClosePattern.findall( line )67        if parentDirCloseMatch:68            parentDirFlag = False69            parentDirName = ''70    return serverNamesDict71def getServerNameAddr():72    patternName = r'LocalSite .*'73    patternURL = r'HttpProxy .*'74    list_domain_URLs = []75    list_domain_names = []76    while True:77        try:78            string = raw_input()79        except EOFError:80            break81        regexName = re.compile( patternName, re.DOTALL|re.IGNORECASE )82        regexURL = re.compile( patternURL, re.DOTALL|re.IGNORECASE )83        matchName = regexName.findall( string )84        matchURL = regexURL.findall( string )85        if matchName:86            for x in matchName:87                x = x.split()[-1][1:-1]88                list_domain_names.append( x )89        if matchURL:90            for x in matchURL:91                x = x.split()[-1][1:-1]92                list_domain_URLs.append( x )93    N = len( list_domain_names )    94    serverDict = {}95    # Make a dictionary from this information96    for i in range( N ):97        name = list_domain_names[ i ]98        99        # Getting all URLs from the URL string100        URLs = list_domain_URLs[ i ]101        pattern = r'http://.*?:'102        regex = re.compile( pattern, re.DOTALL|re.IGNORECASE )103        match = regex.findall( URLs )104        URLsFinal = []105        for x in match:106            URLsFinal.append( x[:-1] )107        serverDict[ name ] = URLsFinal108    return serverDict109def getServerLocations( serverDict ):110    gi = pygeoip.GeoIP( "/usr/local/share/GeoIP/GeoIPCity.dat",111                        pygeoip.STANDARD )112    import socket113    serverDictLocation = {}114    for name, urls in serverDict.iteritems():115        for url in urls:116            url = url[7:]117            gir = None118            try:119                gir = gi.record_by_name( url )120            except socket.gaierror:121                print 'socket error in', url122            except pygeoip.GeoIPError:123                print 'geoip error in', url124            if gir != None:125                break126        127        if gir != None:128            serverDictLocation[ name ] = \129            { 'url': urls, 'latitude': gir[ 'latitude' ], 130              'longitude': gir[ 'longitude' ] }131        #else:132        #    # NF = Not Found133        #    serverDictLocation[ name ] = \134        #    { 'url': urls, 'latitude': "NF", 'longitude': "NF" }135    return serverDictLocation136def main():137    # Parsing geolist.txt to get the names and addresses of all servers138    #serverDict = getServerNameAddr()139    serverDict = parseXMLFile( "geolist.txt" )140    print len(serverDict.items())141    # Get locations of all servers142    serverDictLocation = getServerLocations( serverDict )143    f = open( "location", "w" )144    for name, detail in serverDictLocation.iteritems():145        location = ( detail[ 'longitude' ], detail[ 'latitude' ] )146        urls = detail[ 'url' ]147        urlStr = ''148        for url in urls:149            urlStr = urlStr + ',' + url150        f.write( name + ' ' + str( location[0] ) + ' ' +151                 str( location[1] ) + ' ' + urlStr + '\n' )152    f.close()153    print len( serverDictLocation.items() )154    155    #server_locations.main( PointsMap )156        157if  __name__ == "__main__":...

es.py

Source:es.py

...11        else:12            self.client = sess.client(self.SERVICE, region_name=region)13    def get(self):14        resources = {}15        list_domain_names = self.client.list_domain_names()16        for es in list_domain_names["DomainNames"]:17            domain = self.client.describe_elasticsearch_domain(18                DomainName=es["DomainName"]19            )20            21            self.logger.debug("Inspecting ES domain %s", es["DomainName"])22            23            if domain["DomainStatus"]["Created"] == False:24                self.logger.debug(25                    "Skipping ES domain as it's still being provisioned"26                )27                continue28            if domain["DomainStatus"]["Deleted"] == True:29                self.logger.debug(...

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