[英]Make multiple API calls - Python
我經常使用 API 調用來拉取一些客戶數據。 但是,每當我嘗試提取超過 20 個客戶 ID 時,API 就會停止工作。 發生這種情況時,我運行多個 API 調用,將每個 JSON output 轉換為 df 和 append 所有數據幀。
當我只需要幾個 API 調用時,這很好,但是當我有多個客戶 ID 需要提取時,效率會變得低下,因為有時我必須運行 5/10 個單獨的 API 調用。
我認為循環可以在這里提供幫助。 鑒於我對 Python 的經驗很少,我查看了有關循環 API 的其他問題,但找不到解決方案。
下面是我使用的代碼。 我怎樣才能進行一個 API 循環調用多個客戶 ID(請記住,每次調用有大約 20 個 ID 的限制)並返回一個 dataframe?
謝謝!
#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()
這是一般的想法:
# 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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