My Closet: A “Consumerism Graveyard”
Last Saturday, while organizing my closet, I sighed at the sight of my overflowing wardrobe—12 jackets with tags still on, 20 pairs of shoes worn only once, 3 dusty bags, and a mountain of “impulse buys” (hair clips for 9.9 yuan, aromatherapy for 19.9 yuan, decorative paintings for 39.9 yuan). My mobile banking app pinged with a reminder: “Total expenditure this month: 12,000 yuan, savings balance: 800 yuan.” I suddenly remembered the goal I set at the beginning of the year: “Save 30,000 yuan and quit impulse buying”—now, my bank balance was thinner than a freshly made dumpling skin.
This has been the daily routine in my “spending diary” over the past two years:
- Unboxing deliveries: Three packages a day, halfway through I regret, “Do I really need this?”;
- Scrolling shopping apps: One hour before bed, seeing “limited-time discounts” and “celebrity styles” leads to orders, waking up wondering, “Why did I buy this?”;
- Paying at gatherings: Friends say, “This restaurant is expensive but delicious,” I grit my teeth and swipe my card, then go home to eat instant noodles to pay off my credit card;
- End of the month struggles: Transferring 3,000 yuan to an investment account on payday, only to rely on credit to make it to the next paycheck.
Consequences: Stagnant savings (annual savings dropped from 30,000 to 0), anxiety and insomnia (fear of maxing out my credit card), self-loathing (“Why do I lack self-control?”).
My best friend, Xiao You, scrolled through the screenshots of my “shopping records” on my phone (spending 180,000 yuan in the past year, with 60% being “impulse purchases”), the “pile of delivery boxes” (20 unopened boxes in the living room), and “credit card bills” (averaging 2 late payments per month), shaking her head: “You’re not a ‘shopaholic’, your ‘consumerism system’ has collapsed—your brain is hijacked by ‘instant gratification’ (the thrill of unboxing) and ‘social anxiety’ (fear of being called ‘not refined enough’), leaving no chance to establish a rational consumption perspective using ‘needs lists’ and ‘budget control.'” It wasn’t until she helped me analyze nearly a year of “spending data” with Python that I realized: my “spending tragedy” was entirely due to “no budget + no records + no delay!”
First Strategy: Use Python to “Uncover” the Spending Black Hole
I used to think “spending money is a joyful thing” until I wrote a set of spending behavior analysis system in Python and discovered: my “monthly spending spree” was all due to “no data tracking + no need filtering + no decision delay.”
In the first step, I had Python act as a “spending detective”—exporting “Alipay/WeChat spending records” (2,300 entries over the past year, with 1,400 marked as “impulse purchases”), “delivery receipt records” (organized for 365 days, averaging 1.2 packages per day), and “emotional diary” (recording my psychology while shopping: 35% impulse buys, 25% following trends, 20% rewarding myself, 20% genuine needs). I used <span>pandas</span> to organize it into a “spending timeline”; used <span>matplotlib</span> to create a “monthly spending distribution pie chart” (x-axis: spending type, y-axis: proportion, with red peaks in “clothing and accessories (45%)”, “beauty and personal care (25%)”, “snacks and beverages (15%)”); and used <span>jieba</span> for word segmentation to generate a “cloud of impulse purchase triggers”—the three largest words were “limited time” (380 occurrences), “cheap” (320 occurrences), and “good-looking” (280 occurrences), accounting for 92% of the trigger content!
Even more heartbreaking, I used <span>seaborn</span> to plot the “relationship between impulse purchases and actual usage”—items marked as “impulse buys” (like the “9.9 yuan hair clip”) were used only once; items marked as “following trends” (like the “celebrity-style sweatshirt”) were worn twice before being stored away; while items from the “needs list” (like the “seasonal coat”) were used over 10 times! Xiao You looked at it and shook her head: “This isn’t ‘shopping’; it’s ‘bleeding your wallet dry’ with the illusion of ‘instant pleasure’—your brain is deceived by the anxiety of ‘missing out’ and has no chance to rebuild a consumption perspective using ‘delayed gratification’ long-term benefits.”
Second Strategy: Use Python to “Create” Spending Tools, Making Impulses “Controllable”
What frustrated me the most was knowing I shouldn’t buy something, yet always being pulled back by “limited-time discounts”—I had previously tried “uninstalling shopping apps”, but ended up reinstalling them out of fear of missing out on deals; I tried “keeping a spending journal”, but found it too cumbersome and gave up; I bought a “spending reminder wristband”, but the vibrations were too weak to notice. Now, I’ve written a set of spending brake execution system in Python, with core functions:
- Based on a “spending needs model” (with a “necessary-want-need” classification template), using
<span>input</span>function +<span>random</span>library to automatically generate a “monthly spending list” (e.g., “Necessary: Rent 3000 + Utilities 1000; Want: New Computer 5000; Need: Seasonal Coat 2000”); - Using
<span>schedule</span>library +<span>plyer</span>to trigger “spending reminders” (e.g., “10:00 before scrolling shopping apps: Today’s budget 200 yuan, already used 50 yuan”; “20:00 before unboxing: Confirm if it’s on the needs list”); - Using
<span>pandas</span>+<span>excelwriter</span>to generate a “daily spending report” in real-time (statistics on “today’s expenditure/category proportion/impulse counts”), using “data visualization” to replace “self-deception”; - Using
<span>random</span>library +<span>matplotlib</span>to generate a “spending achievement blind box”—if there are no impulse purchases for 7 consecutive days, you can draw a “reward blind box” (like “100 yuan shopping voucher/free movie ticket/friend dinner” virtual rewards), using “positive feedback” to reinforce rationality.
The code combines need classification (with a “spending template”), timed reminders (with “trigger logic”), and data feedback (with “analysis charts”):
import schedule
import time
import plyer
from datetime import datetime, timedelta
import pandas as pd
import random
# Custom spending needs template (necessary-want-need classification + monthly budget)
CONSUMPTION_TEMPLATE = {
"Monthly Budget": 8000,
"Category Budget": {
"Necessary": {"Rent": 3000, "Utilities": 1000, "Food": 1500},
"Want": {"New Computer": 5000, "Travel": 2000},
"Need": {"Seasonal Coat": 2000, "Skincare Products": 1000}
},
"Impulse Spending Limit": 500 # Monthly impulse spending should not exceed 500 yuan
}
def calculate_today_budget(today):
"""Calculate today's available budget (example: proportionally allocated)"""
monthly_budget = CONSUMPTION_TEMPLATE["Monthly Budget"]
days_passed = today.day - 1 # Days passed this month
daily_budget = (monthly_budget - CONSUMPTION_TEMPLATE["Impulse Spending Limit"]) / (30 - days_passed)
return round(daily_budget, 2)
def send_consumption_reminder(today, today_spent):
"""Send spending reminder (example: timed trigger)"""
pb = plyer.notification
daily_budget = calculate_today_budget(today)
remaining_budget = daily_budget - today_spent
message = f"🛒 Spending Brake Activated:\n"
message += f"Today's Date: {today.strftime('%Y-%m-%d')}\n"
message += f"Today's Budget: {daily_budget} yuan! Used {today_spent} yuan, Remaining {remaining_budget} yuan\n"
if remaining_budget < 100:
message += f"⚠️ Budget is tight! Only {remaining_budget} yuan left today, consider pausing non-essential spending!\n"
else:
message += f"✅ Spending is normal! Keep being rational!\n"
pb.push_note("💸 Spending Assistant", message)
def track_consumption_progress(today, category, amount, is_impulse):
"""Record spending data (example: manual input/automatic sync)"""
with open("consumption_logs.csv", "a") as f:
f.write(f"{today.strftime('%Y-%m-%d')}, {category}, {amount} yuan, {is_impulse}, {random.choice(['Met Target', 'Did Not Meet Target'])}\n") # Simulate classification status
# Example: Set today's spending reminder (actual can sync from calendar/payment app)
today = datetime.now()
# Step 1: Set spending reminders (example: trigger at 10:00/20:00 daily)
def set_consumption_alarms():
pb.push_note("💸 Spending Assistant", f"⏰ Today's Spending Reminder: Budget {calculate_today_budget(today)} yuan! Be rational, avoid impulse!\n")
# Step 2: Generate daily spending report (example: trigger at 23:00 daily)
def daily_consumption_report():
# Simulate reading today's records (actual can read from CSV file)
logs = [{"Date": "2024-09-19", "Category": "Dining", "Amount": "80 yuan", "Is Impulse": "No", "Status": "Met Target"}]
pb.push_note("📊 Daily Spending Report", f"Today's expenditure 80 yuan (Dining), no impulse purchases! Remaining budget is sufficient, keep it up!\n")
# Step 3: Generate spending achievement blind box (example: every Sunday)
def weekly_consumption_reward():
rewards = ["100 yuan shopping voucher (no threshold)", "Free movie ticket (with friends)", "Friend dinner (split bill)"]
reward = random.choice(rewards)
pb.push_note("🎁 Spending Reward", f"No impulse purchases this week! Your reward is: {reward}～ Send me a screenshot of completion for an extra chicken leg!")
# Run script (keep running in the background)
schedule.every().day.at("10:00").do(set_consumption_alarms)
schedule.every().day.at("20:00").do(set_consumption_alarms)
schedule.every().day.at("23:00").do(daily_consumption_report)
schedule.every().sunday.at("19:00").do(weekly_consumption_reward)
while True:
schedule.run_pending()
time.sleep(60) Third Strategy: Use Python to “Monitor” Spending Effects, Making Savings “Tangible”
What surprised me the most was that using Python not only controlled impulse spending but also allowed me to see the specific changes in “savings growth”—I used to think “saving money = pain”, but after recording with tools, I found I could distinguish “needs” from “wants” more quickly (from “buying when I see a discount” to “listing needs before ordering”), reducing my average impulse spending from 1,500 yuan to 300 yuan, saving 52,000 yuan in six months! Even my mom asked, “How did you suddenly become ‘good at saving money’? Your savings are more than mine as a retired teacher!”
Now, my desktop pops up a “spending health report” every month—from “January spending 12,000 yuan, impulse spending 1,500 yuan, savings 0” to “June spending 8,000 yuan, impulse spending 300 yuan, savings 52,000 yuan”, from “spending = bleeding” to “spending = investment”, from “monthly spending spree” to “savings freedom”, I finally understand:the so-called “self-rescue from consumerism” is merely “using data to dissect needs, using tools to reduce impulses, and using feedback to reinforce rationality”.
What Python Taught Me: “Using Technology to Steer Spending”
From “earning 8,000 yuan but spending it all” to “savings over 50,000 yuan”, what I solved with Python was not just a spending problem, but also cracked the cognitive biases of “instant = happiness” and “following trends = refinement”. Now, before shopping, I check my “needs list” with tools, before payment, I use my budget to “hit the brakes”, and at the end of the month, I celebrate my growth with data—these are all changes brought by the “spending brake system”.
Today’s Interaction
Have you ever had moments of “spending it all every month”? Is it “regretting after unboxing”, “buying useless things just to follow trends”, or “relying on credit to make it to payday”? Share your “spending blood and tears history” in the comments!