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How to use default_attributes method in localstack

Best Python code snippet using localstack_python

graph.py

Source:graph.py

1import heapq2import collections3from Compiler.exceptions import *4class GraphError(CompilerError):5    pass6class SparseDiGraph(object):7    """ Directed graph suitable when each node only has a small number of edges.8    Edges are stored as a list instead of a dictionary to save memory, leading9    to slower searching for dense graphs.10    Node attributes must be specified in advance, as these are stored in the11    same list as edges.12    """13    def __init__(self, max_nodes, default_attributes=None):14        """ max_nodes: maximum no of nodes15        default_attributes: dict of node attributes and default values """16        if default_attributes is None:17            default_attributes = { 'merges': None }18        self.default_attributes = default_attributes19        self.attribute_pos = dict(list(zip(list(default_attributes.keys()), list(range(len(default_attributes))))))20        self.n = max_nodes21        # each node contains list of default attributes, followed by outgoing edges22        self.nodes = [list(self.default_attributes.values()) for i in range(self.n)]23        self.succ = [collections.OrderedDict() for i in range(self.n)]24        self.pred = [set() for i in range(self.n)]25        self.weights = {}26    def __len__(self):27        return self.n28    def __getitem__(self, i):29        """ Get list of the neighbours of node i """30        return self.succ[i].keys()31    def __iter__(self):32        pass #return iter(self.nodes)33    def __contains__(self, i):34        return i >= 0 and i < self.n35    def add_node(self, i, **attr):36        if i >= self.n:37            raise CompilerError('Cannot add node %d to graph of size %d' % (i, self.n))38        node = self.nodes[i]39        for a,value in list(attr.items()):40            if a in self.default_attributes:41                node[self.attribute_pos[a]] = value42            else:43                raise CompilerError('Invalid attribute %s for graph node' % a)44    def set_attr(self, i, attr, value):45        if attr in self.default_attributes:46            self.nodes[i][self.attribute_pos[attr]] = value47        else:48            raise CompilerError('Invalid attribute %s for graph node' % attr)49    def get_attr(self, i, attr):50        return self.nodes[i][self.attribute_pos[attr]]51    def remove_node(self, i):52        """ Remove node i and all its edges """53        succ = self[i]54        pred = self.pred[i]55        for v in succ:56            self.pred[v].remove(i)57            #del self.weights[(i,v)]58        for v in pred:59            del self.succ[v][i]60            #del self.weights[(v,i)]61            #self.nodes[v].remove(i)62        self.pred[i] = []63        self.nodes[i] = list(self.default_attributes.values())64    def add_edge(self, i, j, weight=1):65        if j not in self[i]:66            self.pred[j].add(i)67            self.succ[i][j] = None68        self.weights[(i,j)] = weight69    def add_edges_from(self, tuples):70        for edge in tuples:71            if len(edge) == 3:72                # use weight73                self.add_edge(edge[0], edge[1], edge[2])74            else:75                self.add_edge(edge[0], edge[1])76    def remove_edge(self, i, j):77        del self.succ[i][j]78        self.pred[j].remove(i)79        del self.weights[(i,j)]80    def remove_edges_from(self, pairs):81        for i,j in pairs:82            self.remove_edge(i, j)83    def degree(self, i):84        return len(self.succ[i])85def topological_sort(G, nbunch=None, pref=None):86    seen={}87    order_explored=[] # provide order and 88    explored={}       # fast search without more general priorityDictionary89    90    if pref is None:91        def get_children(node):92            return G[node]93    else:94        def get_children(node):95            if node in pref:96                pref_set = set(pref[node])97                for i in G[node]:98                    if i not in pref_set:99                        yield i100                for i in reversed(pref[node]):101                    yield i102            else:103                for i in G[node]:104                    yield i105    if nbunch is None:106        nbunch = reversed(list(range(len(G))))107    for v in nbunch:     # process all vertices in G108        if v in explored: 109            continue110        fringe=[v]   # nodes yet to look at111        while fringe:112            w=fringe[-1]  # depth first search113            if w in explored: # already looked down this branch114                fringe.pop()115                continue116            seen[w]=1     # mark as seen117            # Check successors for cycles and for new nodes118            new_nodes=[]119            for n in get_children(w):120                if n not in explored:121                    if n in seen: #CYCLE !!122                        raise GraphError("Graph contains a cycle at %d (%s,%s)." % \123                                                        (n, G[n], G.pred[n]))124                    new_nodes.append(n)125            if new_nodes:   # Add new_nodes to fringe126                fringe.extend(new_nodes)127            else:           # No new nodes so w is fully explored128                explored[w]=1129                order_explored.append(w)130                fringe.pop()    # done considering this node131    132    order_explored.reverse() # reverse order explored133    return order_explored134def dag_shortest_paths(G, source):135    top_order = topological_sort(G)136    dist = [None] * len(G)137    dist[source] = 0138    for u in top_order:139        if dist[u] is None:140            continue141        for v in G[u]:142            if dist[v] is None or dist[v] > dist[u] + G.weights[(u,v)]:143                dist[v] = dist[u] + G.weights[(u,v)]144    return dist145def reverse_dag_shortest_paths(G, source):146    top_order = reversed(topological_sort(G))147    dist = [None] * len(G)148    dist[source] = 0149    for u in top_order:150        if u ==68273:151            print('dist[68273]', dist[u])152            print('pred[u]', G.pred[u])153        if dist[u] is None:154            continue155        for v in G.pred[u]:156            if dist[v] is None or dist[v] > dist[u] + G.weights[(v,u)]:157                dist[v] = dist[u] + G.weights[(v,u)]158    return dist159def single_source_longest_paths(G, source, reverse=False):160    # make weights negative, then do shortest paths161    for edge in G.weights:162        G.weights[edge] = -G.weights[edge]163    if reverse:164        dist = reverse_dag_shortest_paths(G, source)165    else:166        dist = dag_shortest_paths(G, source)167    #dist = johnson(G, sources)168    # reset weights169    for edge in G.weights:170        G.weights[edge] = -G.weights[edge]171    for i,n in enumerate(dist):172        if n is None:173            dist[i] = 0174        else:175            dist[i] = -dist[i]176    #for k, v in dist.iteritems():177    #    dist[k] = -v178    return dist179def longest_paths(G, sources=None):180    # make weights negative, then do shortest paths181    for edge in G.weights:182        G.weights[edge] = -G.weights[edge]183    dist = {}184    for source in sources:185        print(('%s, ' % source), end=' ')186        dist[source] = dag_shortest_paths(G, source)187    #dist = johnson(G, sources)188    # reset weights189    for edge in G.weights:190        G.weights[edge] = -G.weights[edge]...

models.py

Source:models.py

1import datetime2from contextlib import closing3import copy4def utcnow():5  return datetime.datetime.utcnow()6class Model:7  def create(self, content):8    message = dict()9    for key in self.default_attributes.keys():10      if key in content.keys():11        message[key] = content[key]12      else:13        message[key] = self.default_attributes[key]()14    15    columns = ', '.join(message.keys())16    named_map = ':' + ', :'.join(message.keys())17    query_string = '''18    INSERT INTO {} 19    ({})20    VALUES21    ({});22    '''.format(self.table_name, columns, named_map)23    return query_string, message24  def delete(self, where):25    values = []26    conditions = []27    for key in where.keys():28      if key in self.default_attributes.keys():29        conditions.append(key + where[key][0] + ':' + key)30        values.append(where[key][1])31    query_string = '''32    DELETE FROM {} 33    WHERE ({})34    '''.format(self.table_name, ', '.join(conditions))35    return query_string, values36  def find(self, where=None, order=None, limit=None):37    values = []38    query_string = '''39    SELECT * FROM {} 40    '''.format(self.table_name)41    if where:42      conditions = []43      for key in where.keys():44        if key in self.default_attributes.keys():45          conditions.append(key + where[key][0] + ':' + key)46          values.append(where[key][1])47      query_string += '''48      WHERE ({})49      '''.format(', '.join(conditions))50    if order:51      query_string += '''52      ORDER BY {} {}53      '''.format(order[0], order[1])54    55    if limit:56      query_string += '''57      LIMIT {}58      '''.format(limit)59    60    return query_string, values61  62  def formatResult(self, result):63    formattedResult = copy.deepcopy(self.default_attributes)64    i = 065    for key in self.default_attributes.keys():66      defaultType = self.default_attributes[key]()67      if type(defaultType) == datetime.datetime:68        formattedResult[key] = datetime.datetime.fromisoformat(result[i])69      elif type(defaultType) == str:70        formattedResult[key] = result[i]71      elif type(defaultType) == bool:72        formattedResult[key] = bool(result[i])73      i += 174    return formattedResult75class Messages(Model):76  table_name = 'Messages'77  default_attributes = {78    'Timestamp': utcnow,79    'Message': str,80    'User': str,81    'ID': str82  }83  84  def __init__(self, conn):85    create_table_query = '''86      CREATE TABLE IF NOT EXISTS Messages (87        Timestamp DATE,88        Message TEXT,89        User TEXT,90        ID INTEGER PRIMARY KEY91      );92    '''93    with closing(conn.cursor()) as cursor:94      cursor.execute(create_table_query)95    conn.commit()96class Members(Model):97  table_name = 'Members'98  default_attributes = {99    'JoinAt': utcnow,100    'Verified': bool,101    'ID': str102  }103  104  def __init__(self, conn):105    create_table_query = '''106      CREATE TABLE IF NOT EXISTS Members (107        JoinAt DATE,108        Verified BOOLEAN,109        ID INTEGER PRIMARY KEY110      );111    '''112    with closing(conn.cursor()) as cursor:113      cursor.execute(create_table_query)...

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