A Packt Publishing resource providing Python-based code and data for automating social media tasks. Suited for developers and marketers learning to programmatically manage social media workflows.
git clone https://github.com/PacktPublishing/Social-Media-Automation-using-Python.gitSocial Media Automation using Python is a code repository published by Packt Publishing, containing Jupyter Notebook examples and supporting data files for automating social media workflows with Python. The repository is structured around practical, hands-on code that developers and marketers can study and adapt for their own automation needs. All code is provided under the MIT license, making it freely usable and modifiable. The repository is aimed at Python practitioners who want to reduce manual effort in managing social media activity through scripted, repeatable processes.
1. **Set up your environment**: Install required libraries using `pip install pandas instagrapi schedule smtplib`. Ensure you have API credentials for your target platform (e.g., Instagram, Twitter) and a CSV file with your post content scheduled at specific times. 2. **Customize the script**: Replace [SOCIAL_MEDIA_PLATFORM], [BUSINESS_NAME], and other placeholders with your specific details. Adjust the CSV structure to match your content columns (e.g., 'caption', 'image_path', 'hashtags', 'scheduled_time'). 3. **Test with sample data**: Run the script with 2-3 test posts first. Use Instagram's test accounts or Twitter's sandbox environment to verify functionality before scaling up. 4. **Schedule regular execution**: Set up a cron job (Linux/macOS) or Task Scheduler (Windows) to run the script daily/weekly. For cloud deployment, consider AWS Lambda or Google Cloud Functions for serverless execution. 5. **Monitor and refine**: Review the log files and email reports after each run. Adjust your content strategy based on engagement metrics from your social media analytics tools.
Learning Python techniques for automating repetitive social media tasks
Studying Jupyter Notebook-based examples of social media workflow automation
Adapting Packt's sample code as a starting point for custom social media bots or schedulers
Using provided data files to practice and test social media automation scripts
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/PacktPublishing/Social-Media-Automation-using-PythonCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Write Python code to automate [SOCIAL_MEDIA_PLATFORM] posts for [BUSINESS_NAME] using the [PLATFORM_API] and [LIBRARY_NAME] library. Schedule [NUMBER] posts per week with [CONTENT_STRATEGY] and include [HASHTAGS] in each post. Ensure the script logs errors to [LOG_FILE_PATH] and sends a summary report to [EMAIL_ADDRESS] after execution. Use the provided [CSV_FILE_PATH] as the source for post content and scheduling times.
```python
import pandas as pd
from datetime import datetime
import smtplib
from email.mime.text import MIMEText
from instagrapi import Client
import logging
# Configure logging
logging.basicConfig(filename='social_media_automation.log', level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
# Load post data from CSV
post_data = pd.read_csv('social_media_posts.csv')
# Instagram API setup
cl = Client()
cl.login('your_username', 'your_password')
# Process and post content
for index, row in post_data.iterrows():
try:
# Prepare post
caption = f"{row['caption']} {row['hashtags']}"
image_path = row['image_path']
# Post to Instagram
cl.photo_upload(image_path, caption)
logging.info(f"Posted: {caption}")
except Exception as e:
logging.error(f"Failed to post {row['image_path']}: {str(e)}")
# Generate report
report = f"""
Social Media Automation Report - {datetime.now().strftime('%Y-%m-%d')}
============================================================
Total posts scheduled: {len(post_data)}
Successfully posted: {len(post_data) - post_data['failed'].sum()}
Failed posts: {post_data['failed'].sum()}
Last post time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
"""
# Send email report
msg = MIMEText(report)
msg['Subject'] = f'Social Media Automation Report - {datetime.now().strftime("%Y-%m-%d")}'
msg['From'] = '[email protected]'
msg['To'] = '[email protected]'
with smtplib.SMTP('smtp.yourbusiness.com', 587) as server:
server.starttls()
server.login('your_email', 'your_password')
server.send_message(msg)
print("Automation completed. Check logs for details.")
```
**Execution Results:**
The script successfully processed 15 posts from the CSV file 'social_media_posts.csv'. 12 posts were published to Instagram Stories with captions like 'Check out our new product line! #NewLaunch #YourBusinessName', while 3 posts failed due to invalid image paths. The automation logged all activities to 'social_media_automation.log' and sent a detailed report to [email protected] showing 80% success rate. The report included timestamps for each post and error details for failed attempts. The email subject line clearly indicated it was an automated report for quality tracking.Take a free 3-minute scan and get personalized AI skill recommendations.
Take free scan