Podcast Episode CSV Template

CSV File Structure

Main Episode Data (Single Row)

episode_title,episode_subtitle,season_number,episode_number,series_information,publication_datetime,episode_duration,explicit_content,content_format,primary_category,episode_summary,show_notes,primary_cta_text,primary_cta_url,secondary_cta_text,secondary_cta_url,episode_slug,meta_description,publish_apple,publish_spotify,publish_youtube,include_newsletter,internal_status,internal_notes,assigned_editor

Array Fields (Separate Columns or Files)

For these fields, you have multiple options:

Option 1: Semicolon-separated values (simple)

hosts,topics_keywords,related_episodes,merchandise_ideas
john_doe;jane_smith,machine learning;startups;productivity,episode_123;episode_456,T-shirt: Debugging is life;Sticker: Podcast logo

Option 2: JSON strings (structured)

hosts_json,topics_keywords_json,related_episodes_json,merchandise_ideas_json
["john_doe","jane_smith"],["machine learning","startups"],["episode_123","episode_456"],["T-shirt: Debugging is life","Sticker: Podcast logo"]

Complete CSV Template

Version 1: Simple Template (Single Row)

episode_title,episode_subtitle,season_number,episode_number,series_information,publication_datetime,episode_duration,explicit_content,content_format,primary_category,topics_keywords,episode_summary,show_notes,hosts,primary_cta_text,primary_cta_url,secondary_cta_text,secondary_cta_url,episode_slug,meta_description,publish_apple,publish_spotify,publish_youtube,include_newsletter,related_episodes,merchandise_ideas,internal_status,internal_notes,assigned_editor
"The Future of AI in Podcasting","Exploring how AI is transforming content creation",2,15,"Part 3 of 5: AI Tools Series","2025-12-10T10:00:00","01:15:30","no","deep-dive","Technology","AI;machine learning;content creation;automation","In this episode, we explore the latest AI tools that are revolutionizing podcast production...","<p>Timestamps:</p><p>00:00 - Introduction</p><p>10:30 - AI Transcription Tools</p>","john_doe;jane_smith","Get the AI Toolkit","https://example.com/ai-toolkit","Join our Discord","https://example.com/discord","future-of-ai-podcasting","Explore how AI tools are transforming podcast creation from transcription to distribution",TRUE,TRUE,FALSE,TRUE,"episode_14;episode_16","AI Podcast T-shirt;Neural Network Sticker","draft","Need to verify AI tool links before publishing","editor_jane"

Version 2: Multi-Sheet Template (Multiple Files)

episodes.csv (Main Data):

episode_id,episode_title,episode_subtitle,season_number,episode_number,series_information,publication_datetime,episode_duration,explicit_content,content_format,primary_category,episode_summary,show_notes,primary_cta_text,primary_cta_url,secondary_cta_text,secondary_cta_url,episode_slug,meta_description,publish_apple,publish_spotify,publish_youtube,include_newsletter,internal_status,internal_notes,assigned_editor
EP001,"The Future of AI in Podcasting","Exploring how AI is transforming content creation",2,15,"Part 3 of 5: AI Tools Series","2025-12-10T10:00:00","01:15:30","no","deep-dive","Technology","In this episode...","<p>Detailed show notes...</p>","Get the AI Toolkit","https://example.com/ai-toolkit","Join our Discord","https://example.com/discord","future-of-ai-podcasting","Explore how AI tools are transforming...",TRUE,TRUE,FALSE,TRUE,"draft","Need to verify AI tool links","editor_jane"

topics_keywords.csv (Many-to-Many):

episode_id,topic_keyword
EP001,AI
EP001,machine learning
EP001,content creation
EP001,automation

hosts.csv (Many-to-Many):

episode_id,host_id
EP001,john_doe
EP001,jane_smith

guests.csv (Related Data):

episode_id,guest_name,guest_title,guest_bio,guest_website
EP001,"Dr. Alex Chen","AI Research Lead at TechCorp","Dr. Chen specializes in natural language processing...","https://example.com/alex-chen"
EP001,"Sarah Miller","Podcast Producer","Sarah has produced over 500 episodes...","https://example.com/sarah-miller"

chapters.csv (Related Data):

episode_id,chapter_timecode,chapter_title,chapter_description
EP001,"00:00:00","Introduction","Welcome to the episode"
EP001,"10:30:00","AI Transcription Tools","Comparing different AI transcription services"
EP001,"25:45:00","AI Content Generation","Using AI for show notes and summaries"
EP001,"45:20:00","Q&A Session","Answering audience questions"

resources_links.csv (Related Data):

episode_id,link_text,link_url,link_description
EP001,"Otter.ai Transcription","https://otter.ai","AI-powered transcription service"
EP001,"Descript Audio Editing","https://descript.com","AI audio editing tool"
EP001,"ChatGPT for Content","https://chat.openai.com","AI content generation"

Smart CSV Template with Instructions

Create a file named podcast_template.csv with the following content:

# PODCAST EPISODE CSV TEMPLATE
#
# INSTRUCTIONS:
# 1. Fill in one row per episode
# 2. Required fields are marked with [R]
# 3. Use semicolons (;) to separate multiple values in array fields
# 4. Dates must be in ISO format: YYYY-MM-DDTHH:MM:SS
# 5. For complex data (guests, chapters), use the separate CSV files
# 6. Boolean fields: Use TRUE/FALSE or 1/0

episode_title[R],episode_subtitle,season_number,episode_number,series_information,publication_datetime[R],episode_duration,explicit_content[R],content_format[R],primary_category[R],topics_keywords,episode_summary[R],show_notes,hosts[R],primary_cta_text,primary_cta_url,secondary_cta_text,secondary_cta_url,episode_slug,meta_description,publish_apple,publish_spotify,publish_youtube,include_newsletter,related_episodes,merchandise_ideas,internal_status,internal_notes,assigned_editor

# EXAMPLE DATA - Replace with your episode information:
"The Future of AI in Podcasting","Exploring how AI is transforming content creation",2,15,"Part 3 of 5: AI Tools Series","2025-12-10T10:00:00","01:15:30","no","deep-dive","Technology","AI;machine learning;content creation;automation","In this episode, we explore the latest AI tools that are revolutionizing podcast production. We discuss transcription services, content generation, and automated distribution.","<p>Timestamps:</p><p>00:00 - Introduction</p><p>10:30 - AI Transcription Tools</p><p>25:45 - AI Content Generation</p><p>45:20 - Q&A Session</p>","john_doe;jane_smith","Get the AI Toolkit","https://example.com/ai-toolkit","Join our Discord","https://example.com/discord","future-of-ai-podcasting","Explore how AI tools are transforming podcast creation from transcription to distribution",TRUE,TRUE,FALSE,TRUE,"episode_14;episode_16","AI Podcast T-shirt;Neural Network Sticker","draft","Need to verify AI tool links before publishing","editor_jane"

# ADD YOUR EPISODES BELOW:

CSV Import Mapping Script (JavaScript)

// CSV to Form Data Mapper
function mapCSVToFormData(csvRow) {
    const formData = {
        // Direct mappings
        episode_title: csvRow.episode_title,
        episode_subtitle: csvRow.episode_subtitle,
        season_number: parseInt(csvRow.season_number) || null,
        episode_number: parseInt(csvRow.episode_number) || null,
        series_information: csvRow.series_information,
        publication_datetime: csvRow.publication_datetime,
        episode_duration: csvRow.episode_duration,
        explicit_content: csvRow.explicit_content,
        content_format: csvRow.content_format,
        primary_category: csvRow.primary_category,
        episode_summary: csvRow.episode_summary,
        show_notes: csvRow.show_notes,
        primary_cta_text: csvRow.primary_cta_text,
        primary_cta_url: csvRow.primary_cta_url,
        secondary_cta_text: csvRow.secondary_cta_text,
        secondary_cta_url: csvRow.secondary_cta_url,
        episode_slug: csvRow.episode_slug || generateSlug(csvRow.episode_title),
        meta_description: csvRow.meta_description,
        internal_status: csvRow.internal_status || 'draft',
        internal_notes: csvRow.internal_notes,
        assigned_editor: csvRow.assigned_editor,

        // Array fields (semicolon separated)
        topics_keywords: csvRow.topics_keywords ? csvRow.topics_keywords.split(';').map(s => s.trim()) : [],
        hosts: csvRow.hosts ? csvRow.hosts.split(';').map(s => s.trim()) : [],
        related_episodes: csvRow.related_episodes ? csvRow.related_episodes.split(';').map(s => s.trim()) : [],
        merchandise_ideas: csvRow.merchandise_ideas ? csvRow.merchandise_ideas.split(';').map(s => s.trim()) : [],

        // Boolean fields
        publish_apple: parseBoolean(csvRow.publish_apple),
        publish_spotify: parseBoolean(csvRow.publish_spotify),
        publish_youtube: parseBoolean(csvRow.publish_youtube),
        include_newsletter: parseBoolean(csvRow.include_newsletter),

        // Complex structures (will be loaded from separate files)
        guests: [],
        chapters: [],
        resources_links: []
    };

    return formData;
}

// Helper functions
function parseBoolean(value) {
    if (typeof value === 'string') {
        return value.toLowerCase() === 'true' || value === '1';
    }
    return Boolean(value);
}

function generateSlug(title) {
    return title
        .toLowerCase()
        .replace(/[^a-z0-9\s-]/g, '')
        .replace(/\s+/g, '-')
        .replace(/-+/g, '-')
        .trim();
}

// CSV Parser
function parseCSV(csvText) {
    const lines = csvText.split('\n').filter(line => !line.startsWith('#') && line.trim() !== '');
    if (lines.length < 2) return [];

    const headers = lines[0].split(',').map(h => h.trim());
    const episodes = [];

    for (let i = 1; i < lines.length; i++) {
        const values = parseCSVLine(lines[i]);
        const episode = {};

        headers.forEach((header, index) => {
            if (values[index] !== undefined) {
                episode[header] = values[index].trim();
            }
        });

        episodes.push(mapCSVToFormData(episode));
    }

    return episodes;
}

// Parse CSV line with support for quoted values
function parseCSVLine(line) {
    const values = [];
    let currentValue = '';
    let insideQuotes = false;

    for (let i = 0; i < line.length; i++) {
        const char = line[i];

        if (char === '"') {
            insideQuotes = !insideQuotes;
        } else if (char === ',' && !insideQuotes) {
            values.push(currentValue);
            currentValue = '';
        } else {
            currentValue += char;
        }
    }

    values.push(currentValue);
    return values;
}

Python Script for CSV Import

import csv
import json
from datetime import datetime

def import_podcast_csv(csv_file_path):
    episodes = []

    with open(csv_file_path, 'r', encoding='utf-8') as file:
        # Skip comment lines
        lines = [line for line in file if not line.strip().startswith('#')]

        reader = csv.DictReader(lines)

        for row in reader:
            episode = {
                'episode_title': row['episode_title'],
                'episode_subtitle': row.get('episode_subtitle', ''),
                'season_number': int(row['season_number']) if row.get('season_number') else None,
                'episode_number': int(row['episode_number']) if row.get('episode_number') else None,
                'series_information': row.get('series_information', ''),
                'publication_datetime': row['publication_datetime'],
                'episode_duration': row.get('episode_duration', ''),
                'explicit_content': row['explicit_content'],
                'content_format': row['content_format'],
                'primary_category': row['primary_category'],
                'topics_keywords': [keyword.strip() for keyword in row.get('topics_keywords', '').split(';') if keyword.strip()],
                'episode_summary': row['episode_summary'],
                'show_notes': row.get('show_notes', ''),
                'hosts': [host.strip() for host in row['hosts'].split(';') if host.strip()],
                'primary_cta_text': row.get('primary_cta_text', ''),
                'primary_cta_url': row.get('primary_cta_url', ''),
                'secondary_cta_text': row.get('secondary_cta_text', ''),
                'secondary_cta_url': row.get('secondary_cta_url', ''),
                'episode_slug': row.get('episode_slug') or generate_slug(row['episode_title']),
                'meta_description': row.get('meta_description', ''),
                'publish_apple': row.get('publish_apple', 'TRUE').upper() == 'TRUE',
                'publish_spotify': row.get('publish_spotify', 'TRUE').upper() == 'TRUE',
                'publish_youtube': row.get('publish_youtube', 'FALSE').upper() == 'TRUE',
                'include_newsletter': row.get('include_newsletter', 'TRUE').upper() == 'TRUE',
                'related_episodes': [ep.strip() for ep in row.get('related_episodes', '').split(';') if ep.strip()],
                'merchandise_ideas': [idea.strip() for idea in row.get('merchandise_ideas', '').split(';') if idea.strip()],
                'internal_status': row.get('internal_status', 'draft'),
                'internal_notes': row.get('internal_notes', ''),
                'assigned_editor': row.get('assigned_editor', ''),
                'guests': [],
                'chapters': [],
                'resources_links': [],
                'imported_at': datetime.now().isoformat()
            }
            episodes.append(episode)

    return episodes

def generate_slug(title):
    """Generate URL slug from title"""
    import re
    slug = title.lower()
    slug = re.sub(r'[^a-z0-9\s-]', '', slug)
    slug = re.sub(r'\s+', '-', slug)
    slug = re.sub(r'-+', '-', slug)
    return slug.strip('-')

# Export to JSON for API integration
def export_to_json(episodes, output_file):
    with open(output_file, 'w', encoding='utf-8') as f:
        json.dump(episodes, f, indent=2, ensure_ascii=False)

# Example usage
if __name__ == "__main__":
    episodes = import_podcast_csv('podcast_episodes.csv')
    print(f"Imported {len(episodes)} episodes")

    # Export to JSON
    export_to_json(episodes, 'episodes_imported.json')

Usage Instructions:

1. Download the Template

# Save as podcast_episodes.csv

2. Fill in Your Data

• Open in Excel, Google Sheets, or any spreadsheet software
• Follow the example format
• Use semicolons for multiple values
• Ensure dates are in ISO format

3. Import into Your System

// Using the web form
1. Click "Import from CSV"
2. Upload your CSV file
3. Review auto-populated data
4. Add missing complex data (guests, chapters)
5. Upload media files
6. Publish or save as draft

4. Batch Processing

For multiple episodes:

# Create episodes_batch.csv with all episodes
# Run import script
episodes = import_podcast_csv('episodes_batch.csv')
for episode in episodes:
    save_to_database(episode)

Field Validation Rules for CSV:

This CSV template provides a flexible way to import podcast episodes in bulk while maintaining compatibility with the web form structure.