initial

.gitignore

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+*/.DS_Store/*
+.env
+*/.idea/*
+CapitalOne.csv
+Chase.csv
+*/__pychache__/*

process_csv.py

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+import logging
+import os
+import csv
+import subprocess
+
+from datetime import date, datetime
+from collections import namedtuple
+
+from tx_categories import TX_TO_CATEGORY, Category
+
+logging.basicConfig(level=logging.INFO)
+# poetry run python process_csv.py
+# DESIRED_MONTH = date.today().month
+DESIRED_MONTH = 2
+CSV_TX = namedtuple('CSV_TX', ['TX_DATE', 'POST_DATE', 'DESCRIPTION', 'CATEGORY', 'TYPE', 'AMOUNT', 'MEMO'])
+
+class Transaction:
+	def __init__(self, date, payee, type, amount):
+		# self.date = date.replace(tzinfo=pytz.utc).astimezone(pytz.timezone('America/Chicago'))
+		self.date = date
+		self.payee = payee
+		self.type = type
+		self.amount = amount
+		self.category = self.get_category()
+
+	def get_category(self):
+		category = None
+		for agent, cat in TX_TO_CATEGORY.items():
+			if agent.lower() in self.payee.lower():
+				category = cat
+
+		return category or Category.OTHER
+
+def load_chase_csv():
+	working_dir = os.path.abspath(os.getcwd())
+	filenames = os.listdir(working_dir)
+	tx_filename = None
+	for filename in filenames:
+		if filename.lower().startswith("chase"):
+			tx_filename = os.path.join(working_dir, filename)
+			break
+
+	if not tx_filename:
+		exit("Could not find tx file")
+
+	with open(tx_filename) as csvfile:
+		reader = csv.reader(csvfile, delimiter=',', quotechar='|')
+		output = list(reader)
+
+	all_transactions = []
+	for raw_tx in output[1:]:
+		all_transactions.append(CSV_TX(*raw_tx))
+
+	return all_transactions
+
+def get_transactions(all_transactions):
+	formatted_transactions = []
+	for tx in all_transactions:
+		tx_post_date = datetime.strptime(tx.POST_DATE, '%m/%d/%Y')
+		if tx_post_date.month != DESIRED_MONTH or tx_post_date.year != date.today().year:
+			continue
+		cc_trans = Transaction(
+			date=tx_post_date,
+			payee=tx.DESCRIPTION,
+			type=tx.TYPE,
+			amount=tx.AMOUNT
+		)
+
+		formatted_transactions.append(cc_trans)
+
+	sorted_transactions = sorted(formatted_transactions, key=lambda x: x.date, reverse=False)
+	return sorted_transactions
+
+def print_transactions(transactions):
+	for tx in transactions:
+		print(f"{tx.date} - {tx.payee} - {tx.amount} - {tx.category}")
+
+def convert_tx_to_csv(transactions):
+	output = ""
+	for tx in transactions:
+		output += f"{tx.date.strftime('%m/%d/%Y')},{tx.payee},{tx.amount},{tx.category.value}\n"
+	return output
+
+if __name__ == "__main__":
+	all_transactions = load_chase_csv()
+	transactions = get_transactions(all_transactions)
+	print_transactions(transactions)
+	output = convert_tx_to_csv(transactions)
+	subprocess.run("pbcopy", universal_newlines=True, input=output)
+	print("TXs copied to clipboard!")

tx_categories.py

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+from enum import Enum
+
+class Category(Enum):
+	RECURRING = "Recurring"
+	FOOD = "Food"
+	GROCERY = "Groceries"
+	CLOTHING = "Clothing"
+	OTHER = "Other"
+	TRAVEL = "Vacation"
+	GAS = "Gas"
+	CAR = "Car"
+	EXCLUDED = "N/A"
+	MEDICAL = "Medical"
+	UTILITIES = "Utilities"
+	COUNSELING = "Counseling"
+
+TX_TO_CATEGORY = {
+	"NYTimes": Category.RECURRING,
+	"Easy Tiger": Category.FOOD,
+	"Doordash": Category.FOOD,
+	"H-E-B": Category.GROCERY,
+	"HEB": Category.GROCERY,
+	"its organic": Category.GROCERY,
+	"Poshmark": Category.CLOTHING,
+	"Apple": Category.RECURRING,
+	"AMZN": Category.OTHER,
+	"farmbox delivery": Category.GROCERY,
+	"central market": Category.GROCERY,
+	"black star": Category.FOOD,
+	"Southwes": Category.TRAVEL,
+	"Honest marys": Category.FOOD,
+	"Cabo Bobs": Category.FOOD,
+	"disneyplus": Category.RECURRING,
+	"peloton": Category.RECURRING,
+	"ATT*Bill": Category.UTILITIES,
+	"google *fiber": Category.UTILITIES,
+	"Sunrise citgo mini mart": Category.OTHER,
+	"celis": Category.FOOD,
+	"barrett?s": Category.FOOD,
+	"cava": Category.FOOD,
+	"shell oil": Category.GAS,
+	"American eagle": Category.CLOTHING,
+	"turnstile": Category.FOOD,
+	"turo": Category.TRAVEL,
+	"o'reilly auto parts": Category.CAR,
+	"modern market": Category.FOOD,
+	"enchiladas-y-mas": Category.FOOD,
+	"spotify": Category.RECURRING,
+	"automatic payment": Category.EXCLUDED,
+	"fresh plus": Category.GROCERY,
+	"fwb hancock": Category.FOOD,
+	"vuori": Category.CLOTHING,
+	"american ai": Category.TRAVEL,
+	"titayas": Category.FOOD,
+	"central machine work": Category.FOOD,
+	"lazarus brewing": Category.FOOD,
+	"nervous charlies": Category.FOOD,
+	"trader joe": Category.GROCERY,
+	"peached tortilla": Category.FOOD,
+	"that burger": Category.FOOD,
+	"BROTZMAN SPORTS MEDICINE": Category.MEDICAL,
+	"Jack allens kitchen": Category.FOOD,
+	"airbnb": Category.TRAVEL,
+	"buddys burgers": Category.TRAVEL,
+	"SHELLEY GAUNTT MOELLER": Category.COUNSELING,
+	"marine layer": Category.CLOTHING,
+	"disney plus": Category.RECURRING,
+	"tylers": Category.CLOTHING,
+	"state farm insurance": Category.RECURRING,
+	"lululemon": Category.CLOTHING,
+	"chick-fil-a": Category.FOOD,
+	"going.com": Category.RECURRING,
+	"progressive ins": Category.RECURRING,
+	"VERACRUZALLNATURA.COM": Category.FOOD,
+	"epoch coffee": Category.FOOD,
+	"Mondo sports": Category.MEDICAL,
+	"tri county practice": Category.MEDICAL,
+	"aspire fertility": Category.MEDICAL,
+	"juiceland": Category.FOOD,
+	"MONDOSPORTSTHERAPY": Category.MEDICAL,
+	"chatgpt": Category.RECURRING,
+	"WWW.PERPLEXITY.AI": Category.RECURRING,
+	"payment thank you": Category.EXCLUDED,
+	"public storage": Category.RECURRING,
+}