samkit-jain

#!/usr/bin/env bash 
set -xe

# install packages and dependencies
go get github.com/dgrijalva/jwt-go

# build command
go build -o bin/application application.go

samkit-jain

# initializing variables
w_i = index of withdrawal column  # from BANK_DETAILS
d_i = index of deposit column     # from BANK_DETAILS
b_i = index of balance column     # from BANK_DETAILS
is_negative = False               # flag for default checking
final_result = []                 # transactions with label assigned

# iterate over all transactions
for transaction in transactions:
    # debit leading to a negative balance

samkit-jain

# reading table using tabula
rows = tabula.read_pdf(filepath,
                       pages='all',
                       silent=True,
                       pandas_options={
                           'header': None,
                           'error_bad_lines': False,
                           'warn_bad_lines': False
                       })
# converting to list

samkit-jain

# initializing variables
transactions = []                 # list to store single row entries
d_i = index of date column        # from BANK_DETAILS
p_i = index of particular column  # from BANK_DETAILS

# iterate over all transactions
for v_t in valid_transactions:
    # date exists in the row
    if v_t[d_i] is not None:
        transactions.append(v_t)

samkit-jain

# ----- get header row ----- #

# list to contain all headers
headers = []

# iterate over all rows
for row in rows:
    if last column empty:
        headers.append(rows)
    else:

samkit-jain

BANK_DETAILS = {
    'HDFC': {
        'particulars': 1,    # index of particulars column
        'withdrawal': 4,     # index of withdrawal column
        'deposit': 5,        # index of deposit column
        'balance': 6,        # index of balance column
        'date': 0,           # index of date column
        'chq': 2,            # index of cheque no. column
        'value_date': 3      # index of value date column
   },

samkit-jain

# method to categorize a particular
def categorize(particular):
    # tokenizing
    word_list = tokenize(particular)
    
    # multiple similar statements
    if keyword in word_list:
        return category

# iterate over all transactions