My Phone is a ‘Graveyard of Information Fragments’
Last night before bed, I stared at the “Screen Time Statistics” on my phone screen—today’s screen time was 5 hours and 23 minutes, including 2 hours and 15 minutes on short videos, 1 hour and 40 minutes on social apps, and 1 hour and 28 minutes on news reading, while the “Learning/Work” apps were only used for 47 minutes. As I closed my phone, I suddenly remembered the “Today’s Plan” I made in the morning: “Finish the project proposal, read 2 chapters of a professional book, and exercise for 1 hour”—the result was that I only wrote the introduction of the proposal, stopped reading at page 123, and watched a fitness video for 10 minutes before switching to trending topics.
This has been my daily routine recorded in my “Information Diary” for the past six months:
- Morning: I first scroll through my friend circle (15 minutes), then watch 3 short videos to “wake up” (20 minutes), and end up reminiscing about “internet celebrity breakfast” on my way to work;
- At work: My computer has 10 chat windows open, and when WeChat pings, I switch to reply messages, turning a 1-hour proposal writing task into 3 hours;
- During lunch break: I scroll through public accounts and “save” 10 useful articles, browse Xiaohongshu for 5 items, and spend half an hour on Weibo “gossiping”, only to wake up and find my meal unfinished and not having read a single word of the saved articles;
- Before bed: I scroll through Douyin to “help sleep”, but the more I scroll, the more awake I become, and by 1 AM, I’m still watching “celebrity gossip”, waking up with a headache the next day, and the cycle repeats.
Consequences: Distracted attention (frequently losing focus at work, with a 30% increase in error rate), stagnated learning (only attended 2 out of 6 online courses I signed up for in half a year), and anxiety (always feeling like I “missed important information” but unable to remember anything useful).
My colleague Ajie looked through the screenshots of my phone’s “screen usage records” (app usage proportions: entertainment 45%, social 30%, tools 25%), “favorites screenshot” (12 folders, with 90% of articles unopened), and “to-do list” (completion rate below 20% in the past 3 months), shaking his head: “You don’t have a ‘high information demand’, your ‘information processing system’ has crashed—your brain is hijacked by the ‘instant stimuli’ fed by algorithms, leaving no chance to use ‘active filtering’ and ‘deep focus’ to rebuild information immunity.” It wasn’t until he helped me analyze nearly 3 months of “phone behavior data” with Python that I realized: my “information overload” was entirely due to “no filtering + no goals + no moderation”!
First Strategy: Use Python to ‘Disassemble’ the Information Black Hole, Revealing the Problem
I used to think that “scrolling on my phone is relaxing”, but after writing a set of Information Behavior Analysis System in Python, I discovered that my “attention fragments” were all caused by “no data tracking + no content classification + no time control”.
In the first step, I had Python act as an “information detective”—exporting “the built-in screen usage data from my phone” (over the past 3 months, 450 hours of screen time, with 270 hours spent on “passively receiving information”), “WeChat/QQ chat records” (organized over 90 days, with an average of 120 messages per day, 60% of which were “irrelevant chit-chat”), and “favorites/reading history” (captured 180 saved contents, with only 20 opened again). I used <span>pandas</span> to organize it into an “information timeline”; used <span>matplotlib</span> to create a “pie chart of app usage proportions” (x-axis: app type, y-axis: proportion, with red peaks in “short videos (35%)”, “social (30%)”, and “news (25%)”); and used <span>jieba</span> for word segmentation to generate a “high-frequency click word cloud”—the three largest words were “popular” (appeared 420 times), “recommended” (380 times), and “latest” (320 times), accounting for 90% of the triggered content!
Even more heartbreaking was when I used <span>seaborn</span> to draw the “relationship between information consumption and gains”—the content marked as “algorithm-recommended” (like “viral videos” and “trending topics”) had an average focus duration of only 8 seconds; while the content marked as “actively searched” (like “Python tutorials” and “industry reports”) had an average focus duration of over 20 minutes; and the content that was “saved but unread” (like “10 efficient learning methods”) had a subsequent opening rate of less than 5%! Ajie looked at it and shook his head: “What you have is not ‘information acquisition’, but ‘a false busyness created by algorithms’ that fills your brain with ‘mush’—your brain is deceived by the ‘next more exciting’ stimulus, leaving no chance to use ‘active filtering’ for deep thinking to rebuild information processing ability.”
Second Strategy: Use Python to ‘Create’ Information Tools, Making Fragments ‘Controllable’
What frustrated me the most was that “I clearly wanted to focus, but was always pulled back by ‘message notifications'”—I had tried “turning off my phone”, but ended up turning it back on because I was “afraid of missing work messages”; I tried “uninstalling entertainment apps”, but reinstalled them out of “boredom”; I bought a “focus watch”, but it was left unused because “the functions were too complicated”. Now, I wrote a set of Information Filter Execution System in Python, with core functions:
- Based on the “Information Demand Model” (with a “work-learning-life” classification template), using
<span>input</span>function +<span>random</span>library to automatically generate a “daily information whitelist” (e.g., “Work: project group/industry group; Learning: Python tutorials/professional public accounts; Life: family group/weather”); - Using
<span>schedule</span>library +<span>plyer</span>to trigger “information reminders” at set times (e.g., “9:00-11:00 work period: turn off entertainment app notifications”; “12:30-13:30 lunch break: limit short video app usage to 30 minutes”); - Using
<span>pandas</span>+<span>excelwriter</span>to generate a “daily information report” in real-time (statistic on “today’s effective information acquisition/ineffective consumption duration/focus duration”), using “data visualization” to replace “self-deception”; - Using
<span>random</span>library +<span>matplotlib</span>to generate a “focus achievement blind box”—if I focus for more than 2 hours for 3 consecutive days, I can draw a “reward blind box” (like “1-hour free phone scrolling voucher/weekend short trip/new book” virtual rewards), using “positive feedback” to reinforce focus.
The code combines demand classification (with an “information template”), timed control (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 information demand template (work-learning-life classification + whitelist/blacklist)
INFORMATION_TEMPLATE = {
"工作时段": ("09:00-12:00", ["项目群", "行业资讯号", "领导微信"]),
"学习时段": ("14:00-17:00", ["Python教程网", "专业论坛", "电子书APP"]),
"生活时段": ("19:00-21:00", ["家人群", "天气APP", "健身记录"]),
"娱乐黑名单": ["抖音", "快手", "微博热搜"], # 禁用非休息时段
"专注目标": 2 # 每日有效专注时长目标（小时）
}
def get_current_period(now):
"""判断当前时段（工作/学习/生活）"""
hour = now.hour
if 9 <= hour < 12:
return "工作时段"
elif 14 <= hour < 17:
return "学习时段"
elif 19 <= hour < 21:
return "生活时段"
else:
return "休息时段"
def block_distraction_apps(period):
"""根据时段屏蔽娱乐APP（示例：模拟操作，实际需调用手机API）"""
if period != "休息时段":
blocked = INFORMATION_TEMPLATE["娱乐黑名单"]
message = f"⚠️ 信息过滤器启动：\n"
message += f"当前时段：{period}，已屏蔽娱乐APP：{', '.join(blocked)}\n"
message += f"专注目标：今日还需{INFORMATION_TEMPLATE['专注目标']}小时有效专注～"
plyer.notification.push_note("📵 信息小卫士", message)
def track_focus_time(start, end):
"""记录专注时长（示例：手动输入/自动同步）"""
duration = (end - start).seconds // 3600
with open("focus_logs.csv", "a") as f:
f.write(f"{datetime.now().strftime('%Y-%m-%d')}, {start.strftime('%H:%M')}-{end.strftime('%H:%M')}, {duration}小时, {random.choice(['达标', '未达标'])}\n") # 模拟状态
# 示例：设置当日信息管控（实际可从日历/待办APP同步）
today = datetime.now()
# 步骤1：时段信息提醒（每小时触发）
def hourly_period_reminder():
period = get_current_period(today)
if period != "休息时段":
pb = plyer.notification
pb.push_note("⏰ 信息小卫士", f"当前处于{period}，请专注于白名单内容！")
# 步骤2：屏蔽娱乐APP（每时段开始时触发）
def period_block_reminder():
period = get_current_period(today)
block_distraction_apps(period)
# 步骤3：生成信息日报（每天23:00触发）
def daily_information_report():
# 模拟读取当日记录（实际可从CSV文件读取）
logs = [{"日期": "2024-09-20", "时段": "工作时段", "专注时长": "2.5小时", "状态": "达标"}]
pb.push_note("📊 信息日报", f"今日有效专注2.5小时！完成目标125%，无效刷手机仅1小时，进步明显～")
# 步骤4：生成专注成就盲盒（每周日）
def weekly_focus_reward():
rewards = ["1小时自由刷手机券", "周末短途游（和家人/朋友）", "新书（专业/兴趣类）"]
reward = random.choice(rewards)
pb.push_note("🎁 专注奖励", f"本周专注总时长超目标！你的奖励是：{reward}～坚持住，下一个更棒！")
# 运行脚本（后台持续运行）
schedule.every().hour.at(":00").do(hourly_period_reminder) # 每小时提醒
schedule.every().hour.at(":05").do(period_block_reminder) # 每时段开始5分钟屏蔽娱乐APP
schedule.every().day.at("23:00").do(daily_information_report)
schedule.every().sunday.at("19:00").do(weekly_focus_reward)
while True:
schedule.run_pending()
time.sleep(60) Third Strategy: Use Python to ‘Monitor’ Information Effects, Making Focus ‘Tangible’
What surprised me the most was that using Python not only controlled information interference but also allowed me to see the specific changes in my “focus improvement”—I used to think that “focus = pain”, but after recording with tools, I found that I could enter the “flow state” faster (working for 2 hours without touching my phone), and the quality of task completion changed from “barely passing” to “my boss praised me for ‘exceeding expectations'”, with my monthly performance evaluation rising from “qualified” to “excellent”! Even my boss mentioned in the meeting: “Recently, Xiaozhang’s proposals have become more solid, it seems he is spending his time wisely.”
Now, my desktop pops up an “Information Health Report” every month—from “January focus duration 30 hours, ineffective consumption 25 hours, task completion rate 60%” to “June focus duration 120 hours, ineffective consumption 8 hours, task completion rate 100%”, from “information = fragments” to “information = weapons”, from “scrolling anxiety” to “sense of achievement in focus”, I finally understand:What is called ‘self-rescue from information overload’ is simply ‘using data to filter information, using tools to control time, and using feedback to strengthen focus’.
What Python Taught Me is ‘Using Technology to Equip Information with a ‘GPS’
From “spending 5 hours on my phone daily with no gains” to “deeply focusing for 4 hours”, what I solved with Python was not just the information problem, but also cracked the cognitive misconceptions of “algorithm = authority” and “fragments = richness”. Now, before scrolling on my phone, I use tools to check the “whitelist”, filter information according to “needs” when receiving information, and use data to “record growth” after completing tasks—these are all changes brought by the “Information Filter System”.
Today’s Interaction
Have you ever had moments of “scrolling on your phone late into the night with no gains”? Is it “being pushed by algorithms to scroll through viral content”, “constant interruptions from group chat messages”, or “a mountain of saved articles that you haven’t read much of”? Share your “information overload blood and tears history” in the comments section.