mirror of
https://github.com/UofCBaja/Interview-Backend.git
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Docker Test
MockDB
__pycache__
composetest
djangotutorial
AfterMergeCodeapceTestResults.png
ConversionToExcel.py
FastAPI test 1000 requests.png
GetSchedulePackager.py
README.md
ReadDB.py
TestBookAppointment.py
TestResultsCodeSpace.png
WriteDB.py
interview_database.xlsx
interview_database.yaml
main.py
newMain.py
postSelectAppointment.py
send_email.py
testhttp.py
web1.html
43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
import pandas as pd
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import json
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def ReadDatabase():
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"""
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Reads the Database
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``REQUIRES``: None
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``PROMISES``: JSON (Interview Avaiable Slots)
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``Develop in part by``: Ahmad
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``Contact``: ahmad.ahmad1@ucalgary.ca
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"""
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# Load the updated Excel file into a pandas DataFrame
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excel_file_path = "./interview_database.xlsx"
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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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# 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 amount of interviewees in the slot and if it's empty it will return 0
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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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avaliable_slots = interviewee_amount != slot
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if avaliable_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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#Adds 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
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