Parse and sort customer testimonials

To parse and sort customer testimonials, you’ll need a structured approach depending on the source and format of the testimonials (e.g., plain text, HTML, CSV, JSON). Here’s a general step-by-step approach:

Step 1: Parse Testimonials

If from Plain Text or HTML

Use regular expressions or a parser to extract:

• Customer Name

• Testimonial Content

• Date

• Rating (if available)

Example (Python snippet using regex):

python
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import re

raw_text = """
Name: John Doe
Date: 2024-11-01
Rating: 5
Testimonial: Great service and fast delivery!

Name: Jane Smith
Date: 2024-10-15
Rating: 4
Testimonial: Product quality was excellent.
"""

testimonials = re.findall(
    r"Name: (.*?)nDate: (.*?)nRating: (d)nTestimonial: (.*?)n",
    raw_text,
    re.DOTALL
)

If from CSV/JSON

Use Python’s csv or json modules:

python
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import json

with open("testimonials.json") as f:
    testimonials = json.load(f)

Step 2: Normalize Data

Ensure each testimonial has the following:

• Name (string)

• Date (datetime)

• Rating (int/float)

• Content (string)

Example:

python
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from datetime import datetime

for t in testimonials:
    t['date'] = datetime.strptime(t['date'], "%Y-%m-%d")
    t['rating'] = int(t['rating'])

Step 3: Sort Testimonials

Sort by Date (Newest First):

python
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sorted_testimonials = sorted(testimonials, key=lambda x: x['date'], reverse=True)

Sort by Rating (Highest First):

python
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sorted_testimonials = sorted(testimonials, key=lambda x: x['rating'], reverse=True)

Sort by Name (Alphabetically):

python
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sorted_testimonials = sorted(testimonials, key=lambda x: x['name'])

Step 4: Output/Use Testimonials

Display Format:

python
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for t in sorted_testimonials:
    print(f"{t['name']} ({t['date'].strftime('%Y-%m-%d')}) - Rating: {t['rating']}/5")
    print(f""{t['testimonial']}"n")

Optional Enhancements

• Sentiment Analysis: Use libraries like TextBlob or VADER to classify testimonials.

• Tag Filtering: Add tags like “delivery”, “quality”, “support” and allow filtering.

• Highlight Keywords: Auto-highlight frequently mentioned positive/negative words.

Let me know the format of your testimonials (plain text, HTML, CSV, JSON), and I can provide you a tailored script.