abin-m / interview-scheduler

Optimizing Interview Scheduling for HR Professionals

Optimizing Interview Scheduling for HR Professionals

Streamlining interview scheduling is a complex task for HR teams. Utilizing Django, Django REST framework, and Redis for caching becomes essential for an efficient solution. These frameworks, coupled with dedicated scheduling software, significantly enhance scheduling capabilities, simplifying the management of interview schedules by integrating technology effectively.

Mind Map

Installation

1. Clone repository

2. Create Virtualenv & activate

    virtualenv venv
    source venv/bin/activate
   

3. Install the packages

    pip install -r requirement.txt
   

Getting started

1. start the Django application

    cd interview_scheduler
    python3 manage.py runserver
   

2. Start the redis server on port 6376(refer settings.py)

    redis-server --port 6376
   

API documentation

As a first step we need to create the interviewer and candidate,

Create a candidate

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/register/candidates/

• Headers: No specific headers are required.

• Body:

  {
    "full_name": "Namith Prasad",
    "email": "[e-mail]",
    "contact": "9864565289"
  }
  
  

Response

Status Code: 201 Created
Response Body:
{
"candidate_id": 76053,
"full_name": "Namith Prasad",
"email": "[e-mail]",
"contact": "9864565289"
}

Create an Interviewer

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/register/interviewers/

• Headers: No specific headers are required.

• Body:

  {
    "full_name": "Bharath",
    "email": "[e-mail]",
    "contact": "9188292137"
  }
  
  

Response

Status Code: 201 Created
Response Body:
{
"interviewer_id": 93717,
"full_name": "Bharath",
"email": "[e-mail]",
"contact": "9188292137"
}

create An Interview with the details of Candidate and interviewer

Create Interview

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/interview/

• Headers: No specific headers are required.

• Body:

  {
    "interview_date": "2023-12-05",
    "role": "Django Backend developer", 
    "candidate_id": 76053, // Candidate ID
    "interviewer_id": 93717 // Interviewer ID
  }
  
  

Response

Status Code: 201 Created
Response Body:
{
"interview_date": "2023-12-05",
"role": "Django Backend developer",
"interview_code": "72245",
"candidate_id": 76053,
"interviewer_id": 93717,
"interview_time_slot": "NULL"
}

Now we need to obtain the availabilty of the Interviewer and Candidate

Candidate Availability

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/register/availability/candidate/

• Headers: No specific headers are required.

• Body:

  {
    "candidate_id": 76053,
    "interview_code": "72245", 
    "start_time": "09:00 AM",
    "end_time": "03:00 PM"
  }
  
  
  
  

Response

Status Code: 201 Created
Response Body:
{
"candidate_id": 76053,
"interview_code": "72245",
"start_time": "09:00 AM",
"end_time": "03:00 PM"
}

Interviewer Availability

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/register/availability/interviewer/

• Headers: No specific headers are required.

• Body:

  {
    "interviewer_id": 93717,
    "interview_code": "72245",
    "start_time": "12:00 PM",
    "end_time": "03:00 PM"
  }
  
  
  
  

Response

Status Code: 201 Created
Response Body:
{
"interviewer_id": 93717,
"interview_code": "72245",
"start_time": "12:00 PM",
"end_time": "03:00 PM"
}

Now we need to obtain the available slots

Get Availabile Slots

Request

• Method: POST

• URL: http://127.0.0.1:8000/api/scheduler/find-slots/76053/93717/

• Headers: No specific headers are required.

• Body:

  {
    "interview_code": "72245"
  }
  
  
  
  

Response

Status Code: 201 Created
Response Body:
{
"interview_code": "72245",
"available_slots": "['12:00 PM , 01:00 PM', '01:00 PM , 02:00 PM', '02:00 PM , 03:00 PM']"
}

Note : I have included the remaining API operations in the Postman collection. As this is in the initial stage, if you discover any issues in the system design, please let me know.