Have you ever wished you could automatically identify and tag people’s names in a Google Sheet? Maybe you’re managing a list of contacts, analyzing survey responses, or working on a project where extracting this information is key. Well, with a bit of Python magic and the power of SpaCy’s natural language processing capabilities, we can do just that!
The Challenge
The task at hand was to create a Python script that could:
- Connect to Google Sheets: Securely access a specific spreadsheet using Google’s API.
- Extract Data: Read keywords or phrases from a designated column.
- Identify Names: Use SpaCy’s named entity recognition (NER) to determine which of these keywords are people’s names.
- Update the Sheet: Write “Person” into another column, but only if the cell is empty to avoid overwriting existing data.
Solution: Python and SpaCy to the Rescue!
We tackled this challenge by building a custom Python script leveraging the following tools and techniques:
- gspread: A Python library that makes it a breeze to interact with Google Sheets.
- Google Sheets API: This allowed our script to authenticate and access the spreadsheet remotely.
- SpaCy: A powerful NLP library renowned for its named entity recognition capabilities. We chose the “en_core_web_lg” model for greater accuracy.
The Script: A Step-by-Step Breakdown
- Authentication: We started by setting up secure authentication with Google Sheets using a service account and its credentials.
- Opening the Sheet: The script connected to the specific spreadsheet and targeted the desired worksheet (“MASTER” in our case).
- Reading Keywords: We extracted the keywords from the designated column (column C).
- Identifying Names: SpaCy’s NER model worked its magic, analyzing each keyword to determine if it was a person’s name.
- Conditional Update: To prevent data loss, the script carefully checked if the target cell (in column D) was empty before writing “Person.”
- Batch Updates and Error Handling: To ensure efficiency and avoid hitting API limits, we implemented batch updates. We also included error handling to retry if we ran into rate limiting issues.
Code Snippet:
Here’s a glimpse of the core functionality:
# ... (authentication, sheet opening, keyword extraction)
labels = [label_person(keyword) for keyword in keywords]
cells_to_update = []
existing_values = worksheet.col_values(4)
for i, label in enumerate(labels):
while True:
try:
if not existing_values[i + 1] and label:
cells_to_update.append((i + 2, 4, label))
break
except gspread.exceptions.APIError as e:
if e.response.status_code == 429:
time.sleep(60)
else:
raise
if cells_to_update:
worksheet.update_cells(cells_to_update)
Conclusion
With this Python script, you can automate the process of identifying and tagging people’s names in your Google Sheets,saving you valuable time and effort. Feel free to customize the code, experiment with different SpaCy models, or even extend it to identify other types of entities like organizations or locations!