What I Automated This Week with Python

Automating tasks with Python can significantly boost productivity, streamline workflows, and reduce manual errors. Here’s a comprehensive breakdown of what I automated this week using Python, illustrating practical applications for both personal and professional efficiency.

1. Automated Daily Report Generation

Every morning, my team requires a status report outlining key performance indicators (KPIs) for our projects. Instead of manually compiling this data from multiple sources, I created a Python script that:

• Connects to our SQL database using SQLAlchemy and pandas.

• Queries relevant metrics, such as open tasks, deadlines, and completed items.

• Formats the data into a clean, readable Excel spreadsheet using openpyxl.

• Emails the report using smtplib and email.mime.

The script runs at 6:00 AM daily via a cron job, ensuring everyone has the latest insights before work starts.

2. Email Parsing and Response Bot

Sorting through dozens of emails to identify important messages used to take up hours weekly. I developed an email parsing bot using imaplib and email libraries, which:

• Logs into a designated email account.

• Scans subject lines and content for specific keywords like “invoice,” “urgent,” or “meeting.”

• Flags priority emails in a Google Sheet using the gspread API.

• Sends automated responses for common inquiries (like payment confirmation or document requests) using templates.

With natural language processing via spaCy, the bot even categorizes emails into types: billing, HR, meetings, or general.

3. File Renaming and Organization Script

Downloads and project files tend to clutter quickly. Using os and shutil, I built a script that:

• Monitors the “Downloads” folder.

• Recognizes file types and renames them with timestamps and context (e.g., “Invoice_2025_05_Week3.pdf”).

• Automatically moves files into categorized folders like “Invoices,” “Screenshots,” or “Documents.”

This script runs every hour and helps maintain a tidy file structure without any manual effort.

4. LinkedIn Scraper and CRM Updater

For sales outreach, keeping LinkedIn profiles in sync with our CRM is essential. Using Selenium, I developed a scraper that:

• Logs into LinkedIn and navigates to saved leads.

• Extracts updated job titles, companies, and profile URLs.

• Updates our CRM system (HubSpot) via its API.

To avoid bans, the bot mimics human interaction with randomized delays and browser fingerprinting using undetected-chromedriver.

5. Social Media Content Scheduler

Manually posting to Twitter, LinkedIn, and Facebook at specific times is inefficient. I automated content scheduling by:

• Storing upcoming posts in a Google Sheet.

• Using tweepy, facebook-sdk, and linkedin-api to post content.

• Scheduling based on engagement analytics using historical data processed with pandas.

This reduced our social media manager’s manual workload by over 70%.

6. Weekly Backup and Archival Automation

Data safety is paramount. I created a Python script using boto3 that:

• Archives essential directories to AWS S3 every Friday night.

• Compresses files into .tar.gz format using tarfile.

• Logs upload statuses to a local text file.

• Deletes files older than 90 days from S3 to manage storage costs.

Automated alerts are sent via Slack API if any upload fails.

7. PDF Text Extraction and Summary Generator

I often receive research papers and contracts in PDF format. To streamline content review, I automated:

• PDF text extraction using PyMuPDF.

• Cleaning and processing the content with re and nltk.

• Generating bullet-point summaries and key takeaways with transformers and a pre-trained BERT model.

This saved hours in reading time and made reviewing contracts much easier.

8. YouTube Transcript Summarizer

For industry webinars, I built a tool that:

• Downloads transcripts from YouTube videos using youtube_transcript_api.

• Parses and segments text into logical sections.

• Generates summaries using GPT-based models from Hugging Face.

• Compiles results into a Markdown file for internal documentation.

The tool was helpful in knowledge sharing and creating training material from webinars.

9. Slack Standup Bot

Instead of manually prompting team members for daily standups, I coded a bot that:

• Sends a “standup” message in a Slack channel at 9:00 AM using slack_sdk.

• Collects replies and stores them in a centralized Google Sheet.

• Sends a summary email to the team lead by 10:00 AM.

It also tracks who hasn’t responded, prompting them with a polite nudge after 30 minutes.

10. News Aggregator with Sentiment Analysis

To stay informed, I created a Python bot that:

• Scrapes top tech news from sites like TechCrunch, The Verge, and Wired using BeautifulSoup.

• Applies sentiment analysis via TextBlob to each article.

• Tags articles as positive, negative, or neutral.

• Sends a daily digest with top 5 headlines in each category via email.

This helped in spotting trends and deciding what’s worth reading.

11. API Monitoring and Health Checks

Our applications rely on third-party APIs for various services. I implemented a monitoring system that:

• Sends requests to API endpoints every 10 minutes.

• Logs response time and status code using requests and time.

• Sends alerts to Slack and email if response time exceeds a threshold or if errors occur.

• Generates weekly uptime and performance reports.

This improved our responsiveness to third-party outages significantly.

12. Resume Screening Tool

As part of an internal hiring initiative, I automated the screening of incoming resumes using:

• PyPDF2 for extracting text from PDF resumes.

• Keyword matching for role-specific skills using re.

• Scoring candidates based on keyword density and recency.

• Exporting qualified candidates to an Airtable base via its API.

This helped reduce initial screening time from hours to minutes.

13. Personal Finance Tracker

For personal budgeting, I created a tool that:

• Connects to bank account statements via .csv exports.

• Categorizes expenses into food, utilities, entertainment, etc.

• Visualizes data using matplotlib and seaborn.

• Sends a weekly summary report and savings rate via Telegram bot.

It’s like having a personal finance dashboard with zero manual entry.

14. Website Uptime Notifier

For a small portfolio of websites I maintain, I built a simple script that:

• Pings each website every 5 minutes.

• Logs HTTP status and downtime duration.

• Sends a push notification to my phone via Pushover if a site is down.

• Logs metrics to a CSV file for later review.

It’s lightweight, simple, and runs as a background daemon using schedule.

15. Voice-to-Text Notes Converter

To quickly convert audio memos into text, I used:

• SpeechRecognition and pydub for processing audio files.

• Google Speech API for transcription.

• Automatically organizing results into Markdown notes.

I use this for transcribing ideas while walking or driving and syncing them to Notion using its API.

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Each of these automations took anywhere from 1 to 6 hours to build, debug, and deploy, but the time savings over the long term are well worth it. Python continues to prove itself as an indispensable tool for automating repetitive tasks, enhancing decision-making with data, and freeing up time for more strategic work.