I often use an API call to pull some customer data. However, whenever I try to pull more than 20 customer ids, the API stops working. When this happens, I run multiple API calls, transform each JSON output into a df and append all the dataframes together.
That is fine when I need just a couple of API calls, but becomes inefficient when I have several customer ids to pull, as sometimes I have to run 5/10 separate API calls.
I thought a loop could help here. Given I have little experience with Python, I had a look at other questions on looping APIs, but I couldn't find a solution.
Below is the code I use. How can I make a single API call that loops through several customer ids (keeping in mind that there's a limit of circa 20 ids per call) and returns a single dataframe?
Thanks!
#list of customer ids
customer_id = [
"1004rca402itas8470der874",
"1004rca402itas8470der875,
"1004rca402itas8470der876",
"1004rca402itas8470der877",
"1004rca402itas8470der878",
"1004rca402itas8470der879"
]
#API call
payload = {'customer':",".join(customer_id), 'countries':'DE, 'granularity':'daily', 'start_date':'2021-01-01', 'end_date':'2022-03-31'}
response = requests.get('https://api.xxxxxxjxjx.com/t3/customers/xxxxxxxxxxxx?auth_token=xxxxxxxxxxxx', params=payload)
response.status_code
#convert to dataframe
api = response.json()
df = pd.DataFrame(api)
df['sales'] = df['domestic_sales'] + df['international_sales']
df = df[['customer_id','country','date','sales']]
df.head()
Here is the general idea:
# List of dataframes
dfs = []
# List of lists of 20 customer ids each
ids = [customer_id[i:i+20] for i in range(0, len(customer_id), 20)]
# Iterate on 'ids' to call api and store new df in list called 'dfs'
for chunk in ids:
payload = {
"customer": ",".join(chunk),
"countries": "DE",
"granularity": "daily",
"start_date": "2021-01-01",
"end_date": "2022-03-31",
}
response = requests.get(
"https://api.xxxxxxjxjx.com/t3/customers/xxxxxxxxxxxx?auth_token=xxxxxxxxxxxx",
params=payload,
)
dfs.append(pd.DataFrame(response.json()))
# Concat all dataframes
df = dfs[0]
for other_df in dfs[1:]:
df = pd.concat([df, other_df])
# Additional work
df['sales'] = df['domestic_sales'] + df['international_sales']
df = df[['customer_id','country','date','sales']]
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