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fix(Packagers): changed to first time run
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85
ReadDB.py
85
ReadDB.py
@ -5,12 +5,10 @@ import time
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from NoSheet import NoSheet
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import datetime
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import os
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"""
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TODO update to possibly not use pandas and update to use the new template
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TODO update name of function to be more clear
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TODO change to use new tempate
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TODO change names to be more clear
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"""
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def ReadDatabase():
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@ -33,54 +31,51 @@ def ReadDatabase():
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excel_file_path = f"OR{year_donation}-L-Interview Data.xlsx"
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lock_file_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
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if not (os.path.isfile(excel_file_path) or os.path.isfile(lock_file_path)):
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NoSheet()
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else:
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# Retry parameters
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max_retries = 60 # Maximum number of retries if the file is locked
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retry_interval = 0.5 # Wait time (in seconds) between retries
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# Retry parameters
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max_retries = 60 # Maximum number of retries if the file is locked
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retry_interval = 0.5 # Wait time (in seconds) between retries
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retries = 0
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while retries < max_retries:
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try:
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# Attempt to acquire a shared read (non-blocking) access
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with FileLock(lock_file_path, timeout=0): # Non-blocking, checks if the lock exists
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# Load the Excel file into a pandas DataFrame
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df = pd.read_excel(excel_file_path)
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retries = 0
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while retries < max_retries:
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try:
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# Attempt to acquire a shared read (non-blocking) access
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with FileLock(lock_file_path, timeout=0): # Non-blocking, checks if the lock exists
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# Load the Excel file into a pandas DataFrame
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df = pd.read_excel(excel_file_path)
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# Initialize the dictionary to store the structured data
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interview_data = {}
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# Initialize the dictionary to store the structured data
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interview_data = {}
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# Group the DataFrame by Date, Start Time, and Slot for organization
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for _, row in df.iterrows():
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date = str(row['Date'])
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start_time = str(row['Start Time'])
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slot = int(row['Slot']) if not pd.isna(row['Slot']) else 0
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# Group the DataFrame by Date, Start Time, and Slot for organization
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for _, row in df.iterrows():
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date = str(row['Date'])
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start_time = str(row['Start Time'])
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slot = int(row['Slot']) if not pd.isna(row['Slot']) else 0
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# Returns the number of interviewees in the slot; returns 0 if empty
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interviewee_amount = len(str(row['Interviewee Name']).split()) if str(row['Interviewee Name']) != "nan" else 0
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# Returns the number of interviewees in the slot; returns 0 if empty
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interviewee_amount = len(str(row['Interviewee Name']).split()) if str(row['Interviewee Name']) != "nan" else 0
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# Check if the slot is available for an interviewee to attend
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available_slots = interviewee_amount != slot
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if available_slots:
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# Initialize nested structure if not present
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if date not in interview_data:
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interview_data[date] = {}
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# Add the start time and duration if not present
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if start_time not in interview_data[date]:
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interview_data[date][start_time] = {
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'Meeting Duration': row['Meeting Duration'],
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}
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return interview_data # Successfully read the database
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# Check if the slot is available for an interviewee to attend
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available_slots = interviewee_amount != slot
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if available_slots:
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# Initialize nested structure if not present
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if date not in interview_data:
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interview_data[date] = {}
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# Add the start time and duration if not present
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if start_time not in interview_data[date]:
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interview_data[date][start_time] = {
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'Meeting Duration': row['Meeting Duration'],
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}
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return interview_data # Successfully read the database
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except Timeout:
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# File is locked; wait and retry
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retries += 1
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print(f"File is locked, retrying ({retries}/{max_retries})...")
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time.sleep(retry_interval)
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except Timeout:
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# File is locked; wait and retry
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retries += 1
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print(f"File is locked, retrying ({retries}/{max_retries})...")
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time.sleep(retry_interval)
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# If max retries are exceeded, raise an error
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raise RuntimeError("Unable to access the database after multiple attempts due to a file lock.")
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# If max retries are exceeded, raise an error
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raise RuntimeError("Unable to access the database after multiple attempts due to a file lock.")
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# Example usage of the ReadDatabase function
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if __name__ == "__main__":
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127
WriteDB.py
127
WriteDB.py
@ -4,15 +4,13 @@ from openpyxl import load_workbook
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from send_email import send_email
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from filelock import FileLock
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from NoSheet import NoSheet
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import datetime
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import os
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"""
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TODO update to possibly not use pandas and update to use the new template
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TODO update name of functions to be more clear
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TODO make it work with the new template
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TODO update names to be more clear
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TODO try to remove pandas
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"""
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def ReadDatabase():
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"""
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Reads the Database to retrieve available interview slots
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@ -30,41 +28,37 @@ def ReadDatabase():
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# name based off the 2025 naming system
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file_path = f"OR{year_donation}-L-Interview Data.xlsx"
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lock_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
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# Use a file-based lock for thread-safe and process-safe access
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with FileLock(lock_path):
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# Load the Excel file into a pandas DataFrame with specific columns
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df = pd.read_excel(file_path, usecols=['Date', 'Start Time', 'Slot', 'Interviewee Name', 'Interviewee Email', 'Meeting Duration'])
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# checks for if the file exisits for the year otherwise it will create one
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if not (os.path.isfile(file_path) or os.path.isfile(lock_path)):
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NoSheet()
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else:
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# Use a file-based lock for thread-safe and process-safe access
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with FileLock(lock_path):
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# Load the Excel file into a pandas DataFrame with specific columns
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df = pd.read_excel(file_path, usecols=['Date', 'Start Time', 'Slot', 'Interviewee Name', 'Interviewee Email', 'Meeting Duration'])
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# Initialize the dictionary to store structured data for available slots
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# Initialize the dictionary to store structured data for available slots
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interview_data = {}
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# Process each row in the DataFrame to structure data by date and time
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for _, row in df.iterrows():
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# Convert Date and Start Time to string format for easier comparison
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date = str(row['Date']).split(" ")[0] # Format date to YYYY-MM-DD
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start_time = str(row['Start Time'])
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# Process each row in the DataFrame to structure data by date and time
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for _, row in df.iterrows():
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# Convert Date and Start Time to string format for easier comparison
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date = str(row['Date']).split(" ")[0] # Format date to YYYY-MM-DD
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start_time = str(row['Start Time'])
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# Calculate the slot capacity and current number of interviewees
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slot_capacity = int(row['Slot']) if not pd.isna(row['Slot']) else 0
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interviewee_names = [name.strip() for name in str(row['Interviewee Name']).split(',') if name.strip()]
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interviewee_count = len(interviewee_names) if interviewee_names != ["nan"] else 0
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# Calculate the slot capacity and current number of interviewees
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slot_capacity = int(row['Slot']) if not pd.isna(row['Slot']) else 0
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interviewee_names = [name.strip() for name in str(row['Interviewee Name']).split(',') if name.strip()]
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interviewee_count = len(interviewee_names) if interviewee_names != ["nan"] else 0
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# Check if there are available slots for more interviewees
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if interviewee_count < slot_capacity:
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# Organize data by date and time, keeping track of available slots and meeting duration
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if date not in interview_data:
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interview_data[date] = {}
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interview_data[date][start_time] = {
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'Meeting Duration': row['Meeting Duration'],
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'Available Slots': slot_capacity - interviewee_count
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}
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# Check if there are available slots for more interviewees
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if interviewee_count < slot_capacity:
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# Organize data by date and time, keeping track of available slots and meeting duration
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if date not in interview_data:
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interview_data[date] = {}
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interview_data[date][start_time] = {
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'Meeting Duration': row['Meeting Duration'],
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'Available Slots': slot_capacity - interviewee_count
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}
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return interview_data
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return interview_data
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def AppendAppointment(date, start_time, interviewee_name, interviewee_email):
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"""
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@ -84,46 +78,41 @@ def AppendAppointment(date, start_time, interviewee_name, interviewee_email):
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file_path = f"OR{year_donation}-L-Interview Data.xlsx"
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lock_path = f"OR{year_donation}-L-Interview Data.xlsx.lock"
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# checks for if the file exisits for the year otherwise it will create one
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if not (os.path.isfile(file_path) or os.path.isfile(lock_path)):
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NoSheet()
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else:
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available_slots = ReadDatabase()
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# Check if the requested slot is available in the `available_slots` structure
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if date in available_slots and start_time in available_slots[date]:
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with FileLock(lock_path): # Ensure process-safe access to the file
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# Load workbook and select "Sheet1" for updating appointments
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workbook = load_workbook(file_path)
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sheet = workbook["Interview Timetable"]
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df = pd.read_excel(file_path)
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available_slots = ReadDatabase()
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# Check if the requested slot is available in the `available_slots` structure
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if date in available_slots and start_time in available_slots[date]:
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with FileLock(lock_path): # Ensure process-safe access to the file
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# Load workbook and select "Sheet1" for updating appointments
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workbook = load_workbook(file_path)
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sheet = workbook["Interview Timetable"]
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df = pd.read_excel(file_path)
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# Find and update the row that matches the provided date and start time
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for index, row in df.iterrows():
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row_date = str(row['Date']).split(" ")[0]
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row_start_time = str(row['Start Time'])
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# Find and update the row that matches the provided date and start time
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for index, row in df.iterrows():
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row_date = str(row['Date']).split(" ")[0]
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row_start_time = str(row['Start Time'])
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if row_date == date and row_start_time == start_time:
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# Current entries for names and emails, and append new data with comma and space
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current_names = str(row['Interviewee Name']).strip()
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current_emails = str(row['Interviewee Email']).strip()
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updated_names = f"{current_names}, {interviewee_name}" if current_names != "nan" else interviewee_name
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updated_emails = f"{current_emails}, {interviewee_email}" if current_emails != "nan" else interviewee_email
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if row_date == date and row_start_time == start_time:
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# Current entries for names and emails, and append new data with comma and space
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current_names = str(row['Interviewee Name']).strip()
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current_emails = str(row['Interviewee Email']).strip()
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updated_names = f"{current_names}, {interviewee_name}" if current_names != "nan" else interviewee_name
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updated_emails = f"{current_emails}, {interviewee_email}" if current_emails != "nan" else interviewee_email
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# Update the cells with new names and emails
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name_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Name') + 1)
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email_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Email') + 1)
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name_cell.value = updated_names
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email_cell.value = updated_emails
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# Update the cells with new names and emails
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name_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Name') + 1)
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email_cell = sheet.cell(row=index + 2, column=df.columns.get_loc('Interviewee Email') + 1)
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name_cell.value = updated_names
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email_cell.value = updated_emails
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workbook.save(file_path)
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send_email(interviewee_email, interviewee_name, date, start_time)
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return True
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workbook.save(file_path)
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send_email(interviewee_email, interviewee_name, date, start_time)
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return True
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# If no slots available, return that the slot is unavailable
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return False
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# If no slots available, return that the slot is unavailable
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return False
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def run_tests():
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BIN
__pycache__/interviewPackagers.cpython-313.pyc
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BIN
__pycache__/interviewPackagers.cpython-313.pyc
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@ -0,0 +1,62 @@
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from ReadDB import ReadDatabase
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def getSchedulePackager():
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"""
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Packages up the response for a http response
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``REQUIRES``: None
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``PROMISES``: ``JSON`` http response ready
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``Develop in part by``: Brock T
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``Contact``: darkicewolf50@gmail.ocm
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"""
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return {
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"interviewDates": ReadDatabase()
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}
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from WriteDB import AppendAppointment
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from email_validator import validate_email, EmailNotValidError
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def SelectAppointment (appointmentJson):
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"""
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Packages up a response for a http request
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``REQUIRES``: ``JSON`` with the data of interviewee name, date, starttime and interviewee email
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``PROMISES``: ``JSON`` Returns if the booking was a success
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``Developed in part by``: Brock
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``Contact``: darkicewolf50@gmail.com
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"""
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"""
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Example of an incoming http post body
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{
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"intervieweeName": "Brock",
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"date": "2024-09-16",
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"startTime": "10:30:00",
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"intervieweeEmail": "darkicewolf50@gmail.com"
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}
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"""
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try:
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validEmail = validate_email(appointmentJson["intervieweeEmail"], check_deliverability=True)
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if validEmail:
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status = AppendAppointment(date=appointmentJson["date"], start_time=appointmentJson["startTime"], interviewee_name=appointmentJson["intervieweeName"], interviewee_email=appointmentJson["intervieweeEmail"])
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if status:
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resBody = {"Success": True, "validEmail": "true"}
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else:
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resBody = {"Success": False, "validEmail": "true"}
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# resBody["message"] = appointmentJson for testing
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return resBody
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except EmailNotValidError as e:
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return {"Success": False, "validEmail": "false"}
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12
main.py
12
main.py
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import json
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from fastapi import FastAPI
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from fastapi.responses import JSONResponse
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from pydantic import BaseModel
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from NoSheet import NoSheet
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import datetime
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import os
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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
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# name based off the 2025 naming system
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# Define the path to the Excel file and the lock file
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file_name = f"OR{year_donation}-L-Interview Data.xlsx"
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if not os.path.isfile(file_name):
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NoSheet()
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app = FastAPI()
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@app.get("/")
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