Hey everyone! I’m trying to move some data from a pandas DataFrame to HubSpot CRM. I’ve written a script to do this but I’m running into a problem. Here’s what I’ve got so far:
import pandas as pd
import requests
from io import StringIO
# Create dummy DataFrame
df = pd.DataFrame({'Name': ['John', 'Jane'], 'Email': ['[email protected]', '[email protected]']})
# Convert DataFrame to CSV
csv_buffer = StringIO()
df.to_csv(csv_buffer, index=False)
csv_buffer.seek(0)
# HubSpot API stuff
hubspot_key = 'your_api_key_here'
import_url = 'https://api.hubapi.com/crm/v3/imports'
# Set up the request
data = {
'name': 'My Import',
'files': [
{
'file_name': 'my_data.csv',
'fileData': csv_buffer.getvalue()
}
]
}
headers = {
'Authorization': f'Bearer {hubspot_key}',
'Content-Type': 'application/json'
}
# Send the request
result = requests.post(import_url, json=data, headers=headers)
print(f'Status: {result.status_code}')
print(f'Response: {result.text}')
When I run this, I get a 415 error saying ‘Unsupported Media Type’. I’m not sure what I’m doing wrong. Has anyone successfully imported data to HubSpot from a pandas DataFrame? Any tips would be super helpful!
I encountered a similar issue when integrating with HubSpot’s API. In my experience, the solution was to avoid handling file uploads directly and instead convert the DataFrame into a more manageable format. I recommend transforming your DataFrame into a list of dictionaries and using the HubSpot batch creation endpoint for contacts. This way, you send JSON data rather than a file upload, which bypasses the multipart encoding issues seen with CSV conversion. It also simplifies handling rate limits and ensures that your API key scopes are correctly applied.
yo emma, i’ve been there before. the import api can be a real pain. have u tried using hubspot’s python sdk instead? it’s way easier to handle. just convert ur dataframe to a list of dicts and use the batch endpoint for contacts. trust me, it’ll save u a ton of headaches. good luck with ur project!
hey emma, looks like ur using the wrong content-type header. for file uploads, you need to use ‘multipart/form-data’ instead of ‘application/json’. also, make sure ur sending the actual file data, not just the string representation. might wanna check hubspot’s api docs for the exact format they expect. good luck!
I’ve dealt with this exact problem before, and I can tell you it can be quite challenging. The issue goes beyond the content type; HubSpot’s import API is notoriously finicky. In my experience, switching to their batch API turned out to be far more reliable for smaller datasets. I converted the DataFrame into a list of dictionaries and then used the HubSpot Python SDK to simplify the integration process instead of handling raw requests. Although this method requires a bit more coding, it provides better error handling and easier management of rate limits, with HubSpot capping requests at 100 contacts per call. For larger datasets, implementing pagination is a must. Overall, this approach has saved me countless headaches with HubSpot integrations.
I’ve encountered similar challenges when integrating with HubSpot’s API. From my experience, the most reliable approach is to utilize their batch API for contacts instead of the import endpoint. This method circumvents issues with file uploads and content types.
To implement this, you’ll want to convert your DataFrame to a list of dictionaries. Then, use the HubSpot Python SDK to send the data in batches. This approach not only simplifies the process but also provides better error handling and rate limit management.
Keep in mind that HubSpot limits batch requests to 100 contacts per call, so for larger datasets, you’ll need to implement pagination. While this method requires more initial setup, it’s far more robust and less prone to errors in the long run.
If you’re dealing with a substantial amount of data, consider implementing a queuing system to manage the API calls efficiently and avoid hitting rate limits.