Many have been asking how to connect Facebook Ads API with Python. The need is usually to analyze the facebook ads data, visualize it or simply store it in a database for later use.

Here I will show a very quick way to pull Facebook data with Python.

You can connect directly to the api, here is the documentation: https://developers.facebook.com/docs/marketing-apis/ and use the Python package. However a simpler way is to use Windsor.ai connector service.

Then the steps are as follows:

1. Grant access to Facebook ads in https://onboard.windsor.ai
2. Select the fields and metrics you want to pull
3. Use the built query in python to get your data

Step 1: Grant access to Facebook Ads API to connect with Python

First you have to register, then you select Facebook Ads and grant access.

2. Select the fields and build the query

3. Use the built query in python to get data from Facebook Ads API

Here is a short python snippet that gets the data into a pandas dataframe and prints it:

import requests
import json
import pandas as pd

api_key = 'APIKEY' # your api-key

# URL listing the fields you want to pull
api_url = 'https://connectors.windsor.ai/facebook?date_preset=last_7d&fields=date,campaign,clicks,spend&api_key=' + api_key

res = requests.get(api_url).json()
df = pd.DataFrame.from_dict(res['data'])
print(df)

The output will then look like this:

date campaign clicks spend
0 2021-12-03 retageting APAC 1 2.87
1 2021-12-03 retargeting UK&CO 0 0.03
2 2021-12-04 retageting APAC 0 2.91
3 2021-12-04 retargeting UK&CO 0 0.04

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Importing Facebook Ads Data Into Python

Importing Facebook ads data has never been easier using the Windsor.ai token. With a couple of lines of code, you will be able to fetch the desired data columns into your python project. However, before we start doing that, let’s quickly create a free account on the Windsor website: https://onboard.windsor.ai/. Grab your API key and let’s get started.

Windsor has its own Facebook Ads Python library which makes things simpler. You can install the package by running

pip install FacebookAdsWindsorApi

Next, we need to load the package client

from FacebookAdsWindsorApi.client import Client

Paste your API key into the following code

API_KEY = "YOUR-KEY"
client = Client(API_KEY)

Lastly, you can fetch the columns you want by running

response = client.connectors(
    date_present="last_7d",
    fields=["date", "clicks", "spend"]
)
print(response['data'])

Which returns the following dictionary

>>> [{'date': '2022-10-28', 'clicks': '3', 'spend': '6.27'},
 {'date': '2022-10-29', 'clicks': '5', 'spend': '6.24'},
 {'date': '2022-10-30', 'clicks': '2', 'spend': '4.5'}]

For a full list of possible Facebook Ads library fields you can visit the connector documentation on Windsor’s official website https://windsor.ai/data-field/facebook/. The official python package can be found in the following GitHub repository: https://github.com/windsor-ai/FacebookAdsWindsorApi/

Moreover, for a more general python package, you can check Windsor’s pywindsorai library where you can integrate all of your ad platforms in no time. The full list of the supported platforms can be found here.

For other data Python project, you can visit the how-to website where various data analytics solutions are discussed.

And you can adjust the fields argument for any fields you would like to have.

You might also like to read: 

Connect Facebook Ads to Google Sheets

Connect Facebook Ads to Power BI

Connect Facebook Ads to Excel

Connect Facebook Ads to Snowflake

Connect Facebook Ads to Google BigQuery

Connecting Facebook Ads to Tableau 

Facebook Ads Google Data Studio Connector

Microsoft Power BI Facebook Ads Report Dashboard Template