In this lab, we'll be building a CSV parser with Python! This will help us get comfortable with using standard Python libraries, data manipulation, and working with tuples.

• Read and parse csv files into an easier to manipulate format.
• Build a functional Python CSV parser
• Write data to an easier to read JSON file

• Fork and clone this repository
• We'll be working in the parser.py file

We have a raw CSV file in our data folder. It contains useful information about employees for a company but the data isn't accessible in its current state.

Our backend engineers would love to work with the data, but aren't having any success with it. This is why we're being hired, to convert the data into a useful JSON file!

How are we going to do this?

• First, we'll need to get the data from the CSV file
• Then we'll need to format each employee into a Python dictionary
• Finally, we'll need to convert a list of employee dictionaries into a JSON file

To start out, we'll need to import a few standard Python modules and create a few global variables at the top of our script

Let's add in our imports first at the top of the file

import csv
import json

• Were importing the CSV module to make reading and writing CSV files more accessible. More on the CSV module here.
• We're importing the JSON library to give ourselves access to useful JSON encoding/decoding methods like json.dump() and json.loads(). More on the JSON module here

Now let's add in a few global variables. They'll all be empty lists to start:

read_data = []
# for CSV data read and stored as tuples
fields = []
# for the name of each column in the CSV file's rows
employee_list = []
# for formatted data, a dictionary for each row in the CSV file

And with that, we've set up our script with the proper imports and global variables! We can move on to the fun part now - manipulating the data in our parsing function!

Let's start out with defining our function. It should take in 2 arguments: one for the path of our CSV file, and on for an output path to create a new JSON file. This way, we'll be able to take in any CSV file and convert it to JSON.

def csv_to_json(csv_path, json_path):
  # your code here

...

csv_to_json('data/employee_data.csv','data/employees.json')

We'll write out each part of the function in the steps below. Make sure that each part is within the indented block of csv_to_json!

The first thing we'll want to do here is extract the data from our CSV file. Once we've read the data, we'll append each entry into our read_data list.

But first, how do we read a CSV file?

with open(csv_path, mode='r', encoding='utf-8-sig') as csv_file:
  csv_data = csv.reader(csv_file, delimiter=',')

• More on Python's open() method here.
• More on Python with ... as statements here.
• More on using the CSV module's reader() method here.

With our read CSV data stored in csv_data, we can now add it into our read_data list.

• After setting the data to csv_data you'll need to loop through each entry in csv_data and append each entry as a tuple to our read_data list

We're setting these entries as tuples to ensure that the original data entries aren't changed.

Finally, outside of our with open block, let's create two new variables for the headers of the CSV rows and the employee entries. These variables will be sub-lists of read_data.

• One variable should be for the headers, the column titles of the CSV data.

• The next variable should be for the employees, the data entries representing each employee in data_list. Since the headers will be at the first index of read_data, everything else should be an employee's data entries. everything after the first index of read_data

Try print()ing your headers variable below to check that you've set it correcty.

('Emp ID', 'First Name', 'Middle Initial', 'Last Name', 'Gender', 'EMail', 'Date of Birth', 'Age', 'Weight', 'Date of Joining', 'Quarter of Joining', 'Year of Joining', 'Month of Joining', 'Month Name of Joining', 'Short Month', 'Day of Joining', 'Age in Company', 'Salary', 'Last % Hike', 'SSN', 'Phone Num', 'Place Name', 'County', 'City', 'State', 'Zip')

We know that we have access to the data in read_data now, but what about formatting it before we convert it into JSON?

First, let's format the headers and store them in our fields list in a more accessible form.

Since the headers are currently stored as a tuple, we'll need to use Python's enumerate() method to iterate over them with a for loop.

for i, some_value in enumerate(some_tuple):

• Set a variable name to represent each header inside the loop. It's value should:
  • Replace the empty spaces in each header with underscores and lowercase the whole string
  • Append the formatted header name to our fields list

A few useful Python string methods:

• replace
• lower

If done properly, your fields list should now have properly formatted Python strings! Try printing the fields list below the loop to check.

['emp_id', 'first_name', 'middle_initial', 'last_name', 'gender', 'email', 'date_of_birth', 'age', 'weight', 'date_of_joining', 'quarter_of_joining', 'year_of_joining', 'month_of_joining', 'month_name_of_joining', 'short_month', 'day_of_joining', 'age_in_company', 'salary', 'last_%_hike', 'ssn', 'phone_num', 'place_name', 'county', 'city', 'state', 'zip']

Now that we have a list of the fields needed for each employee, let's add their data! We'll store each employee as a dictionary within employee_list.

We'll need to loop through the employees list that we set as a variable above. Inside the loop we'll also need to enumerate through each employee tuple, just like we did with the headers above. Inside the main loop of employees, the following needs to happen:

• An empty dictionary should be created for each employee
• Each employee's data entries should be accessed by enumerating over the employee
• For each entry in the enumerated employee loop, we'll need to create a key value pair for the dictionary
  • The key should be equal to the field at the same index as the entry
  • The value should be equal to the entry
• Update the dictionary with each key value pair for an employee's entries
• After updating the dictionary, append it to our employee_list and clear the dictionary by setting it back to an empty dictionary so the next employee can be added

Once finished, try printing employee_list[1] to check if you're getting the right values. You should be getting a properly formatted dictionary in your console.

{'emp_id': '178566', 
'first_name': 'Juliette', 
'middle_initial': 'M', 
'last_name': 'Rojo', 
'gender': 'F', 'email': 
'[email protected]', 
'date_of_birth': '5/8/1967', 
'age': '50.26', 
'weight': '55', 
'date_of_joining': '6/4/2011', 
'quarter_of_joining': 'Q2', 
'year_of_joining': '2011', 
'month_of_joining': '6', 
'month_name_of_joining': 'June', 
'short_month': 'Jun', 
'day_of_joining': '4', 
'age_in_company': '6.15', 
'salary': '193912', 
'last_%_hike': '27%', 
'ssn': '671-48-9915', 
'phone_num': '215-254-9594', 
'place_name': 'Glenside', 
'county': 'Montgomery', 
'city': 'Glenside', 
'state': 'PA', 
'zip': '19038'}

If you're getting the right return, we're done with formatting! Yay!

The final step in this process is converting our employee_list into JSON and writing it into a readable JSON file.

Like we did to open the CSV file to start, we'll use the with open as python statement, but this time we'll be giving it a mode of 'w' to specify that we're writing a new file.

with open(json_path, mode='w') as output_file:
  

We've done two things here:

• Specified the path for a new JSON file we're creating from the path input in our function call
• Stored the file that we'll be writing to in a variable called output_file

We need to do one last thing to create our new employees.json file from the CSV data:

• Use the JSON package to dump our employee_list data into our output_file. We'll give it an indent of 2 for it to be nicely formatted.

with open(json_path, mode='w') as output_file:
  # json.dump(???, ???, indent=2)

If everything was done correctly, you should have a brand new, cleanly formatted employees.json file in your data folder! Congrats, we've done it!

• The csv_to_json function should create a new employees.json file with properly formatted data when it is run

• Read about one important reason that CSV files are used with Python

• Python CSV Module
• Python JSON Module
• Python Math Library
• Python Enumerating Tuples
• Python string.replace()
• Python string.lower()