fix(Packagers): changed to first time run

ReadDB.py

@@ -5,12 +5,10 @@ import time
 
 from NoSheet import NoSheet
 import datetime
-import os
-
 
 """
-TODO update to possibly not use pandas and update to use the new template
+TODO change to use new tempate
-TODO update name of function to be more clear
+TODO change names to be more clear
 """
 
 def ReadDatabase():
@@ -33,54 +31,51 @@ def ReadDatabase():
     excel_file_path = f"OR{year_donation}-L-Interview Data.xlsx"
     lock_file_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
 
-    if not (os.path.isfile(excel_file_path) or os.path.isfile(lock_file_path)):
+    # Retry parameters
-        NoSheet()
+    max_retries = 60  # Maximum number of retries if the file is locked
-    else:
+    retry_interval = 0.5  # Wait time (in seconds) between retries
-        # Retry parameters
-        max_retries = 60  # Maximum number of retries if the file is locked
-        retry_interval = 0.5  # Wait time (in seconds) between retries
 
-        retries = 0
+    retries = 0
-        while retries < max_retries:
+    while retries < max_retries:
-            try:
+        try:
-                # Attempt to acquire a shared read (non-blocking) access
+            # Attempt to acquire a shared read (non-blocking) access
-                with FileLock(lock_file_path, timeout=0):  # Non-blocking, checks if the lock exists
+            with FileLock(lock_file_path, timeout=0):  # Non-blocking, checks if the lock exists
-                    # Load the Excel file into a pandas DataFrame
+                # Load the Excel file into a pandas DataFrame
-                    df = pd.read_excel(excel_file_path)
+                df = pd.read_excel(excel_file_path)
 
-                    # Initialize the dictionary to store the structured data
+                # Initialize the dictionary to store the structured data
-                    interview_data = {}
+                interview_data = {}
 
-                    # Group the DataFrame by Date, Start Time, and Slot for organization
+                # Group the DataFrame by Date, Start Time, and Slot for organization
-                    for _, row in df.iterrows():
+                for _, row in df.iterrows():
-                        date = str(row['Date'])
+                    date = str(row['Date'])
-                        start_time = str(row['Start Time'])
+                    start_time = str(row['Start Time'])
-                        slot = int(row['Slot']) if not pd.isna(row['Slot']) else 0
+                    slot = int(row['Slot']) if not pd.isna(row['Slot']) else 0
 
-                        # Returns the number of interviewees in the slot; returns 0 if empty
+                    # Returns the number of interviewees in the slot; returns 0 if empty
-                        interviewee_amount = len(str(row['Interviewee Name']).split()) if str(row['Interviewee Name']) != "nan" else 0
+                    interviewee_amount = len(str(row['Interviewee Name']).split()) if str(row['Interviewee Name']) != "nan" else 0
 
-                        # Check if the slot is available for an interviewee to attend
+                    # Check if the slot is available for an interviewee to attend
-                        available_slots = interviewee_amount != slot
+                    available_slots = interviewee_amount != slot
-                        if available_slots:
+                    if available_slots:
-                            # Initialize nested structure if not present
+                        # Initialize nested structure if not present
-                            if date not in interview_data:
+                        if date not in interview_data:
-                                interview_data[date] = {}
+                            interview_data[date] = {}
-                            # Add the start time and duration if not present
+                        # Add the start time and duration if not present
-                            if start_time not in interview_data[date]:
+                        if start_time not in interview_data[date]:
-                                interview_data[date][start_time] = {
+                            interview_data[date][start_time] = {
-                                    'Meeting Duration': row['Meeting Duration'],
+                                'Meeting Duration': row['Meeting Duration'],
-                                }
+                            }
-                    return interview_data  # Successfully read the database
+                return interview_data  # Successfully read the database
 
-            except Timeout:
+        except Timeout:
-                # File is locked; wait and retry
+            # File is locked; wait and retry
-                retries += 1
+            retries += 1
-                print(f"File is locked, retrying ({retries}/{max_retries})...")
+            print(f"File is locked, retrying ({retries}/{max_retries})...")
-                time.sleep(retry_interval)
+            time.sleep(retry_interval)
 
-        # If max retries are exceeded, raise an error
+    # If max retries are exceeded, raise an error
-        raise RuntimeError("Unable to access the database after multiple attempts due to a file lock.")
+    raise RuntimeError("Unable to access the database after multiple attempts due to a file lock.")
 
 # Example usage of the ReadDatabase function
 if __name__ == "__main__":

WriteDB.py

@@ -4,15 +4,13 @@ from openpyxl import load_workbook
 from send_email import send_email
 from filelock import FileLock 
 
-from NoSheet import NoSheet
 import datetime
-import os
 
 """
-TODO update to possibly not use pandas and update to use the new template
+TODO make it work with the new template
-TODO update name of functions to be more clear
+TODO update names to be more clear
+TODO try to remove pandas  
 """
-
 def ReadDatabase():
     """ 
     Reads the Database to retrieve available interview slots
@@ -30,41 +28,37 @@ def ReadDatabase():
     # name based off the 2025 naming system
     file_path = f"OR{year_donation}-L-Interview Data.xlsx"
     lock_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
+    
+    # Use a file-based lock for thread-safe and process-safe access
+    with FileLock(lock_path):
+        # Load the Excel file into a pandas DataFrame with specific columns
+        df = pd.read_excel(file_path, usecols=['Date', 'Start Time', 'Slot', 'Interviewee Name', 'Interviewee Email', 'Meeting Duration'])
 
-    # checks for if the file exisits for the year otherwise it will create one
+    # Initialize the dictionary to store structured data for available slots
-    if not (os.path.isfile(file_path) or os.path.isfile(lock_path)):
-        NoSheet()
-    else:
-        # Use a file-based lock for thread-safe and process-safe access
-        with FileLock(lock_path):
-            # Load the Excel file into a pandas DataFrame with specific columns
-            df = pd.read_excel(file_path, usecols=['Date', 'Start Time', 'Slot', 'Interviewee Name', 'Interviewee Email', 'Meeting Duration'])
-
-        # Initialize the dictionary to store structured data for available slots
         interview_data = {}
 
-        # Process each row in the DataFrame to structure data by date and time
+    # Process each row in the DataFrame to structure data by date and time
-        for _, row in df.iterrows():
+    for _, row in df.iterrows():
-            # Convert Date and Start Time to string format for easier comparison
+        # Convert Date and Start Time to string format for easier comparison
-            date = str(row['Date']).split(" ")[0]  # Format date to YYYY-MM-DD
+        date = str(row['Date']).split(" ")[0]  # Format date to YYYY-MM-DD
-            start_time = str(row['Start Time'])
+        start_time = str(row['Start Time'])
             
-            # Calculate the slot capacity and current number of interviewees
+        # Calculate the slot capacity and current number of interviewees
-            slot_capacity = int(row['Slot']) if not pd.isna(row['Slot']) else 0
+        slot_capacity = int(row['Slot']) if not pd.isna(row['Slot']) else 0
-            interviewee_names = [name.strip() for name in str(row['Interviewee Name']).split(',') if name.strip()]
+        interviewee_names = [name.strip() for name in str(row['Interviewee Name']).split(',') if name.strip()]
-            interviewee_count = len(interviewee_names) if interviewee_names != ["nan"] else 0
+        interviewee_count = len(interviewee_names) if interviewee_names != ["nan"] else 0
 
-            # Check if there are available slots for more interviewees
+        # Check if there are available slots for more interviewees
-            if interviewee_count < slot_capacity:
+        if interviewee_count < slot_capacity:
-                # Organize data by date and time, keeping track of available slots and meeting duration
+            # Organize data by date and time, keeping track of available slots and meeting duration
-                if date not in interview_data:
+            if date not in interview_data:
-                    interview_data[date] = {}
+                interview_data[date] = {}
-                interview_data[date][start_time] = {
+            interview_data[date][start_time] = {
-                    'Meeting Duration': row['Meeting Duration'],
+                'Meeting Duration': row['Meeting Duration'],
-                    'Available Slots': slot_capacity - interviewee_count
+                'Available Slots': slot_capacity - interviewee_count
-                }
+            }
 
-        return interview_data
+    return interview_data
 
 def AppendAppointment(date, start_time, interviewee_name, interviewee_email):
     """ 
@@ -84,46 +78,41 @@ def AppendAppointment(date, start_time, interviewee_name, interviewee_email):
     file_path = f"OR{year_donation}-L-Interview Data.xlsx"
     lock_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
 
-    # checks for if the file exisits for the year otherwise it will create one
+    available_slots = ReadDatabase()
-    if not (os.path.isfile(file_path) or os.path.isfile(lock_path)):
+    
-        NoSheet()
+    # Check if the requested slot is available in the `available_slots` structure
-    else:
+    if date in available_slots and start_time in available_slots[date]:
+        with FileLock(lock_path):  # Ensure process-safe access to the file
+            # Load workbook and select "Sheet1" for updating appointments
+            workbook = load_workbook(file_path)
+            sheet = workbook["Interview Timetable"]
+            df = pd.read_excel(file_path)
 
-        available_slots = ReadDatabase()
+            # Find and update the row that matches the provided date and start time
-        
+            for index, row in df.iterrows():
-        # Check if the requested slot is available in the `available_slots` structure
+                row_date = str(row['Date']).split(" ")[0]
-        if date in available_slots and start_time in available_slots[date]:
+                row_start_time = str(row['Start Time'])
-            with FileLock(lock_path):  # Ensure process-safe access to the file
-                # Load workbook and select "Sheet1" for updating appointments
-                workbook = load_workbook(file_path)
-                sheet = workbook["Interview Timetable"]
-                df = pd.read_excel(file_path)
 
-                # Find and update the row that matches the provided date and start time
+                if row_date == date and row_start_time == start_time:
-                for index, row in df.iterrows():
+                    # Current entries for names and emails, and append new data with comma and space
-                    row_date = str(row['Date']).split(" ")[0]
+                    current_names = str(row['Interviewee Name']).strip()
-                    row_start_time = str(row['Start Time'])
+                    current_emails = str(row['Interviewee Email']).strip()
+                    
+                    updated_names = f"{current_names}, {interviewee_name}" if current_names != "nan" else interviewee_name
+                    updated_emails = f"{current_emails}, {interviewee_email}" if current_emails != "nan" else interviewee_email
 
-                    if row_date == date and row_start_time == start_time:
+                    # Update the cells with new names and emails
-                        # Current entries for names and emails, and append new data with comma and space
+                    name_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Name') + 1)
-                        current_names = str(row['Interviewee Name']).strip()
+                    email_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Email') + 1)
-                        current_emails = str(row['Interviewee Email']).strip()
+                    name_cell.value = updated_names
-                        
+                    email_cell.value = updated_emails
-                        updated_names = f"{current_names}, {interviewee_name}" if current_names != "nan" else interviewee_name
-                        updated_emails = f"{current_emails}, {interviewee_email}" if current_emails != "nan" else interviewee_email
 
-                        # Update the cells with new names and emails
+                    workbook.save(file_path)
-                        name_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Name') + 1)
+                    send_email(interviewee_email, interviewee_name, date, start_time)
-                        email_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Email') + 1)
+                    return True
-                        name_cell.value = updated_names
-                        email_cell.value = updated_emails
 
-                        workbook.save(file_path)
+    # If no slots available, return that the slot is unavailable
-                        send_email(interviewee_email, interviewee_name, date, start_time)
+    return False
-                        return True
-
-        # If no slots available, return that the slot is unavailable
-        return False
 
 
 def run_tests():

interviewPackagers.py

@@ -0,0 +1,62 @@
+from ReadDB import ReadDatabase
+
+
+def getSchedulePackager():
+    """ 
+    Packages up the response for a http response
+
+    ``REQUIRES``: None
+
+    ``PROMISES``: ``JSON`` http response ready
+
+    ``Develop in part by``: Brock T
+
+    ``Contact``: darkicewolf50@gmail.ocm
+
+    """
+    return {
+            "interviewDates": ReadDatabase()
+        }
+
+from WriteDB import AppendAppointment
+from email_validator import validate_email, EmailNotValidError
+
+
+def SelectAppointment (appointmentJson):
+    """ 
+    Packages up a response for a http request
+
+    ``REQUIRES``: ``JSON`` with the data of interviewee name, date, starttime and  interviewee email
+    
+    ``PROMISES``: ``JSON`` Returns if the booking was a success
+
+    ``Developed in part by``: Brock
+
+    ``Contact``: darkicewolf50@gmail.com
+
+    """
+    """
+    Example of an incoming http post body
+    {
+        "intervieweeName": "Brock",
+        "date": "2024-09-16",
+        "startTime": "10:30:00",
+        "intervieweeEmail": "darkicewolf50@gmail.com"
+    }
+    """
+    try:
+        validEmail = validate_email(appointmentJson["intervieweeEmail"], check_deliverability=True)
+        if validEmail:
+            status = AppendAppointment(date=appointmentJson["date"], start_time=appointmentJson["startTime"], interviewee_name=appointmentJson["intervieweeName"], interviewee_email=appointmentJson["intervieweeEmail"])
+            
+            if status:
+                resBody = {"Success": True, "validEmail": "true"}
+            else:
+                resBody = {"Success": False, "validEmail": "true"}
+            
+            # resBody["message"] = appointmentJson for testing
+            return resBody
+        
+    except EmailNotValidError as e:
+        return {"Success": False, "validEmail": "false"}
+

main.py

@@ -1,8 +1,18 @@
-import json
 from fastapi import FastAPI
 from fastapi.responses import JSONResponse
 from pydantic import BaseModel
 
+from NoSheet import NoSheet
+import datetime
+import os
+
+year_donation = int(str(datetime.datetime.now().year)[2:]) + 1 # gets the last two digits of the current year then adds 1 for the current season
+# name based off the 2025 naming system
+# Define the path to the Excel file and the lock file
+file_name = f"OR{year_donation}-L-Interview Data.xlsx"
+if not os.path.isfile(file_name):
+    NoSheet()
+
 app = FastAPI()
 
 @app.get("/")