updated the scripts

Author: hseera

merge_multiple_file_columns.py

@@ -9,10 +9,18 @@
 Make sure the files that needs to be merged have unique names from other file. 
 https://jdhao.github.io/2019/06/24/python_glob_case_sensitivity/
 '''
-files = glob.glob("./sample_files/result_TestPlan_results_*.csv")
 
-dataframes = [pd.read_csv(p) for p in files]
+FILES_TO_READ = "./sample_files/result_TestPlan_results_*.csv"
+FILE_TO_WRITE = "./sample_files/merged.csv"
 
-merged_dataframe = pd.concat(dataframes, axis=1)
-merged_dataframe.to_csv("./sample_files/merged.csv", index=False)
+def merge_columns(FILES_TO_READ):
+    files = glob.glob(FILES_TO_READ)
+    dataframes = [pd.read_csv(p) for p in files]
+    merged_dataframe = pd.concat(dataframes, axis=1)
+    merged_dataframe.to_csv(FILE_TO_WRITE, index=False)
 
+def main():
+    merge_columns(FILES_TO_READ)
+    
+if __name__ == "__main__":
+    main()

randomize_data.py

@@ -5,8 +5,16 @@
 '''Shuffle rows in a file. Useful when you want to have a random order data file for test.
 
 '''
-FILE = './sample_files/random.csv'
+FILE_TO_READ = './sample_files/random.csv'
 
-original_order = pd.read_csv(FILE)
-random_order = original_order.sample(frac=1) #frac = 1 means randomize whole data set
-random_order.to_csv(FILE, index=False)
+
+def randomize(FILE_TO_READ):
+    original_order = pd.read_csv(FILE_TO_READ)
+    random_order = original_order.sample(frac=1) #frac = 1 means randomize whole data set
+    random_order.to_csv(FILE_TO_READ, index=False)
+
+def main():
+    randomize(FILE_TO_READ)
+    
+if __name__ == "__main__":
+    main()

swap_columns.py

@@ -7,11 +7,20 @@
 
 '''
 # rearranged column here
-columns =['timeStamp','label','elapsed','Latency','Connect','IdleTime','responseCode',
+COLUMNS =['timeStamp','label','elapsed','Latency','Connect','IdleTime','responseCode',
           'responseMessage','bytes','dataType','success',
           'failureMessage','sentBytes','URL','threadName','allThreads','grpThreads']
 
-original_order = pd.read_csv('./sample_files/swap_001.csv')
-swapped_order = original_order[columns] 
-swapped_order.to_csv('./sample_files/swap_001.csv', index=False)
-    
+FILE_TO_READ = './sample_files/swap_001.csv'
+
+def swap_columns(FILE_TO_READ):
+    original_order = pd.read_csv(FILE_TO_READ)
+    swapped_order = original_order[COLUMNS] 
+    swapped_order.to_csv(FILE_TO_READ, index=False)
+    
+
+def main():
+    swap_columns(FILE_TO_READ)
+    
+if __name__ == "__main__":
+    main()

unique_and_sorted.py

@@ -14,23 +14,28 @@
 '''
 
 
-count_list =[]
 
 FILE_TO_READ = "./sample_files/unique_and_sorted.csv" #replace with your file name
 FILE_TO_WRITE = "./sample_files/file_to_write.csv"
 
-with open(FILE_TO_READ,'r') as fread, open(FILE_TO_WRITE,'w') as fwrite:
-    for line in fread: #split the row and add the values into the list
-        #print(line)
-        str = line.split(',')
-        #print(str)
-        if (str[1] != "\n"):
-            count_list.append(int(str[1]))
-    count_list = list(set(count_list)) #save the value into a new list and sort it
-    count_list.sort()
-    for item in count_list:
-        fwrite.write('%s\n' %item)
-fread.close()
-fwrite.close()
+
+def unique_and_sorted(FILE_TO_READ, FILE_TO_WRITE):
+    count_list =[]
+    with open(FILE_TO_READ,'r') as fread, open(FILE_TO_WRITE,'w') as fwrite:
+        for line in fread: #split the row and add the values into the list
+            str = line.split(',')
+            if (str[1] != "\n"):
+                count_list.append(int(str[1]))
+        count_list = list(set(count_list)) #save the value into a new list and sort it
+        count_list.sort()
+        for item in count_list:
+            fwrite.write('%s\n' %item)
+    fread.close()
+    fwrite.close()
 
+def main():
+    unique_and_sorted(FILE_TO_READ, FILE_TO_WRITE)
 
+if __name__ == "__main__":
+    main()
+