Merge pull request #31 from GeoDecConsensus/feat/logs

chore: improve logging

.gitignore

@@ -141,7 +141,7 @@ node
 client
 
 mytestnet/
-persistent_peer.txt
+*.txt
 
 frontend/node_modules
 

benchmark/geo_logs.py

@@ -1,12 +1,13 @@
+import math
 from glob import glob
 from os.path import join
 from re import findall, split
 
-import math
 import pandas as pd
 
 from benchmark.utils import PathMaker
 
+
 #########################################################################################
 #########################################################################################
 #### GeoDec emulator to study impacts of geospatial diversity on blockchain networks ####
@@ -21,75 +22,52 @@ def count_votes_props(run_id):
         proposals = []
         node_num = []
         total_block_commits = 0
-        for filename in sorted(glob(join(directory, 'node-*.log'))):
-            node_num.append(int(filename.split('-')[1].split('.')[0]))
-            with open(filename, 'r') as f:
+        for filename in sorted(glob(join(directory, "node-*.log"))):
+            node_num.append(int(filename.split("-")[1].split(".")[0]))
+            with open(filename, "r") as f:
                 data = f.read()
-                addr_line = findall(r'Node .* successfully booted', data)
-                addr = split(' ', addr_line[0])[1]
+                addr_line = findall(r"Node .* successfully booted", data)
+                addr = split(" ", addr_line[0])[1]
                 addresses.append(addr)
-                prop = findall(r'\[(.*Z) .* Created B\d+ -> ([^ ]+=)', data)
+                prop = findall(r"\[(.*Z) .* Created B\d+ -> ([^ ]+=)", data)
                 proposals.append(len(prop))
-                commits = findall(r'QC for block: Round:\d.*', data)
+                commits = findall(r"QC for block: Round:\d.*", data)
                 total_block_commits = max(total_block_commits, len(commits))
-                    
+
         votes = [0] * len(addresses)
-        
-        for filename in sorted(glob(join(directory, 'node-*.log'))):
+
+        for filename in sorted(glob(join(directory, "node-*.log"))):
             votes_temp = [0] * len(addresses)
-            with open(filename, 'r') as f:
+            with open(filename, "r") as f:
                 logs = f.read()
-                qc_lines = findall(r'QC for block: Round:\d.*', logs)
+                qc_lines = findall(r"QC for block: Round:\d.*", logs)
                 for n in range(len(qc_lines)):
                     line = qc_lines[n]
                     for i in range(len(addresses)):
                         if addresses[i] in line:
                             votes_temp[i] = votes_temp[i] + 1
                             votes[i] = max(votes[i], votes_temp[i])
-    
+
         votes_data = pd.DataFrame(
-            {'address': addresses,
-            'votes': votes,
-            'proposals': proposals,
-            'node_num' : node_num,
-            'run_id' : ([run_id] * len(addresses))
-            })
+            {
+                "address": addresses,
+                "votes": votes,
+                "proposals": proposals,
+                "node_num": node_num,
+                "run_id": ([run_id] * len(addresses)),
+            }
+        )
         return GeoLogParser._calculate_liveliness(votes_data, total_block_commits)
-    
+
     @staticmethod
     def _calculate_liveliness(data, total_block_commits):
         committe_size = len(data)
-        total_committed  = (data['votes'].sum()/ math.ceil((2/3)*committe_size))
-
-        total_blocks = max(total_committed, total_block_commits)
-
-        data['liveliness'] = (data['votes']/total_blocks) * 100
-
-        total_props = data['proposals'].sum()
-        data['liveliness_woprops'] = ((data['votes']+data['proposals'])/total_props) * 100
-        return data
-
-    @staticmethod
-    def get_new_run_id():
-        data = pd.read_csv('/home/ubuntu/results/geo-dec-metrics.csv')
-        return (data['run_id'].max() + 1)
-
-    @staticmethod
-    def aggregate_runs(run_id_array):
-        data = pd.read_csv('/home/ubuntu/results/geo-dec-metrics.csv')
-
-        data = data.loc[data['run_id'].isin(run_id_array)]
-        by_name = data.groupby(['name'])
+        total_committed = data["votes"].sum() / math.ceil((2 / 3) * committe_size)
 
-        # for name, liveliness in by_name:
-        #     print(f"entries for {name!r}")
-        #     print("------------------------")
-        #     print(liveliness.head(3), end="\n\n")
+        total_blocks = max(total_committed, total_block_commits)
 
-        liveliness_mean = by_name['liveliness'].mean(numeric_only= True).reset_index()
-        liveliness_mean.rename(columns = {'liveliness':'liveliness_avg'}, inplace = True)
+        data["liveliness"] = (data["votes"] / total_blocks) * 100
 
-        data_first = data.loc[data['run_id'] == run_id_array[0]]
-        result = pd.merge(data_first, liveliness_mean, on='name')
-        result['runs'] = ([len(run_id_array)] * len(result))
-        return result
+        total_props = data["proposals"].sum()
+        data["liveliness_woprops"] = ((data["votes"] + data["proposals"]) / total_props) * 100
+        return data