add sleep sort and quick sort in place

Author: dli98

CSV_files/assets/course_name.csv

@@ -1,6 +1,5 @@
-name,course
-Noura,python40python401
-Mahmoud,python401
-Nizar,python401
-Raneem,python401
-Omer,python401
+Name,Score
+Omar,82
+Mahmoud,86
+Noura,84
+Raneem,65

CSV_files/read_csv.py

@@ -1,32 +1,34 @@
 import csv
+
 import pandas as pd
- 
+
+
 def read_using_DictReader(path):
     # opening the CSV file
-    with open(path, mode ='r') as file:   
-       # reading the CSV file
-       csvFile = csv.DictReader(file)
-       main_dic=[]
-       # displaying the contents of the CSV file
-       for lines in csvFile:
-           main_dic.append(lines)
-       return main_dic
-
-#retrun the top 5 rows in CSV file
+    with open(path, mode='r') as file:
+        # reading the CSV file
+        csvFile = csv.DictReader(file)
+        main_dic = []
+        # displaying the contents of the CSV file
+        for lines in csvFile:
+            main_dic.append(lines)
+        return main_dic
+
+
+# return the top 5 rows in CSV file
 def read_by_pandas_head(path):
-    data=pd.read_csv(path)
-    return data.head()       
+    data = pd.read_csv(path)
+    return data.head()
 
 
-#retrun the bottom 5 rows in CSV file
+# return the bottom 5 rows in CSV file
 def read_by_pandas_tail(path):
-    data=pd.read_csv(path)
-    return data.tail() 
-  
-if __name__=="__main__":
-    
-    path='./assets/addresses.csv'
+    data = pd.read_csv(path)
+    return data.tail()
+
+
+if __name__ == "__main__":
+    path = './assets/addresses.csv'
     print(read_using_DictReader(path))
     print(read_by_pandas_head(path))
     print(read_by_pandas_tail(path))
-

CSV_files/write_csv.py

@@ -1,45 +1,45 @@
 import csv
-import pandas as pd
 
+import pandas as pd
 
- 
 
-def write_to_csv_files_using_DictWriter_class(data,fields,filename):
-   
-    with open(filename, 'w') as csvfile: 
+def write_to_csv_files_using_DictWriter_class(data, fields, filename):
+    with open(filename, 'w') as csvfile:
         # creating a csv dict writer object 
-        writer = csv.DictWriter(csvfile, fieldnames = fields) 
-            
+        writer = csv.DictWriter(csvfile, fieldnames=fields)
+
         # writing headers (field names) 
-        writer.writeheader() 
-            
+        writer.writeheader()
+
         # writing data rows 
-        writer.writerows(data) 
-
-def write_by_pandas(name_dict):
-        df = pd.DataFrame(name_dict)
-        return df
-
-if __name__=="__main__":
-     # my data rows as dictionary objects 
-    mydata =[{'name': 'Noura', 'course': 'python40python401'}, 
-            {'name': 'Mahmoud', 'course': 'python401'}, 
-            {'name': 'Nizar', 'course': 'python401'}, 
-            {'name': 'Raneem', 'course': 'python401'}, 
-            {'name': 'Omer', 'course': 'python401'}, ] 
-        
+        writer.writerows(data)
+
+
+def write_by_pandas(name_dict, filename):
+    df = pd.DataFrame(name_dict)
+    df.to_csv(filename, index=False)
+    return df
+
+
+if __name__ == "__main__":
+    # my data rows as dictionary objects
+    mydata = [{'name': 'Noura', 'course': 'python40python401'},
+              {'name': 'Mahmoud', 'course': 'python401'},
+              {'name': 'Nizar', 'course': 'python401'},
+              {'name': 'Raneem', 'course': 'python401'},
+              {'name': 'Omer', 'course': 'python401'}, ]
+
     # field names 
-    fields = ['name','course'] 
-        
+    fields = ['name', 'course']
+
     # name of csv file 
     filename = "assets/course_name.csv"
-        
-    # writing to csv file 
-    print(write_to_csv_files_using_DictWriter_class(mydata,fields,filename))
 
+    # writing to csv file 
+    print(write_to_csv_files_using_DictWriter_class(mydata, fields, filename))
 
     name_dict = {
-        'Name': ['Omar','Mahmoud','Noura','Raneem'],
-        'Score': [82,86,84,65]
-        }
-    print(write_by_pandas(name_dict))
+        'Name': ['Omar', 'Mahmoud', 'Noura', 'Raneem'],
+        'Score': [82, 86, 84, 65]
+    }
+    write_by_pandas(name_dict, filename)

Data Structures and Algorithms/quick_sort_v2.py

@@ -0,0 +1,30 @@
+from typing import List
+
+
+def partition(nums, low, high) -> int:
+    piv = nums[high]
+    i = low
+    for j in range(low, high):
+        if nums[j] <= piv:
+            nums[i], nums[j] = nums[j], nums[i]
+            i += 1
+
+    nums[i], nums[high] = nums[high], nums[i]
+    return i
+
+
+def quick_sort(nums: List, low, high):
+    if low < high:
+        p = partition(nums, low, high)
+        quick_sort(nums, low, p - 1)
+        quick_sort(nums, p + 1, high)
+
+
+def sort(nums):
+    quick_sort(nums, 0, len(nums) - 1)
+    return nums
+
+
+print(sort([5, 8, 1, 4, 7, 9, 6, 3, 2]))
+print(sort([]))
+print(sort([0, 1, 2, 6, -1]))

Data Structures and Algorithms/sleep_sort.py

@@ -0,0 +1,14 @@
+import threading
+import time
+
+items = [2, 4, 5, 2, 1, 7]
+
+
+# just fun
+def sleep_sort(i):
+    time.sleep(i)
+    print(i)
+
+
+ts = [threading.Thread(target=sleep_sort, args=(i,)) for i in items]
+[t.start() for t in ts]