在我的 Google 云函数(Python 3.7 运行时)中,我创建了一个函数,它试图将所有 .csv 文件从谷歌存储桶下载到 pandas 数据框 (df) 中。进入数据帧后,我打算对其进行一些简单的 ETL 工作,然后将其转换回一个大型 .csv 文件以保存到另一个存储桶。
我遇到的问题是当我将对象(使用 file.download_as_string() 转换为字符串)读入 read_csv() 时,我收到与 IO.StringIO 相关的错误(TypeError:initial_value must be str或无,不是字节)
在 read_csv(io.String.IO(file_contents).... 中,这是否与我放置 io.StringIO 方法的位置有关?谁能帮我改正这个错误?
def stage1slemonthly(data, context, source_bucket = 'my_source_bucket',
destination_bucket = 'gs://my destination_bucket'):
from google.cloud import storage
import pandas as pd
import pyspark
from pyspark.sql import SQLContext
import io
storage_client = storage.Client()
# source_bucket = data['bucket']
# source_file = data['name']
source_bucket = storage_client.bucket(source_bucket)
# load in the col names
col_names = ["Customer_Country_Number", "Customer_Name", "Exclude",
"SAP_Product_Name", "CP_Sku_Code", "Exclude", "UPC_Unit",
"UPC_Case", "Colgate_Month_Year", "Total_Cases",
"Promoted_Cases", "Non_Promoted_Cases",
"Planned_Non_Promoted_Cases", "Exclude",
"Lead_Measure", "Tons", "Pieces", "Liters",
"Tons_Conv_Revenue", "Volume_POS_Units", "Scan_Volume",
"WWhdrl_Volume", "Exclude", "Exclude", "Exclude", "Exclude",
"Exclude", "Exclude", "Exclude", "Exclude", "Investment_Buy",
"Exclude", "Exclude", "Gross_Sales", "Claim_Sales",
"Adjusted_Gross_Sales", "Exclude", "Exclude",
"Consumer_Investment", "Consumer_Allowance",
"Special_Pack_FG", "Coupons", "Contests_Offers",
"Consumer_Price_Reduction", "Permanent_Price_Reduction",
"Temporary_Price_Reduction", "TPR_Off_Invoice", "TPR_Scan",
"TPR_WWdrwl_Exfact", "Every_Day_Low_Price", "Closeouts",
"Inventory_Price_Reduction", "Exclude", "Customer_Investment",
"Prompt_Payment", "Efficiency_Drivers", "Efficient_Logistics",
"Efficient_Management", "Business_Builders_Direct", "Assortment",
"Customer_Promotions","Customer_Promotions_Terms",
"Customer_Promotions_Fixed", "Growth_Direct",
"New_Product_Incentives", "Free_Goods_Direct",
"Shopper_Marketing", "Business_Builders_Indirect",
"Middleman_Performance", "Middleman_Infrastructure",
"Growth_Indirect", "Indirect_Retailer_Investments",
"Free_Goods_Indirect", "Other_Customer_Investments",
"Product_Listing_Allowances", "Non_Performance_Trade_Payments",
"Exclude", "Variable_Rebate_Adjustment",
"Overlapping_OI_Adjustment", "Fixed_Accruals",
"Variable_Accruals", "Total_Accruals", "Gross_To_Net",
"Invoiced_Sales", "Exclude", "Exclude", "Net_Sales",
"Exclude", "Exclude", "Exclude", "Exclude", "Exclude",
"Exclude", "Exclude", "Exclude", "Exclude",
"Total_Variable_Cost", "Margin", "Exclude"]
df = pd.DataFrame(columns=[col_names])
for file in list(source_bucket.list_blobs()):
file_contents = file.download_as_string()
df = df.append(pd.read_csv(io.StringIO(file_contents), header=None, names=[col_names]))
df = df.reset_index(drop=True)
# do ETL work here in future
sc = pyspark.SparkContext.getOrCreate()
sqlCtx = SQLContext(sc)
sparkDf = sqlCtx.createDataFrame(df)
sparkDf.coalesce(1).write.option("header", "true").csv(destination_bucket)
当我运行它时,我收到以下错误消息...
Traceback (most recent call last): File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 383, in run_background_function _function_handler.invoke_user_function(event_object) File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 217, in invoke_user_function return call_user_function(request_or_event) File "/env/local/lib/python3.7/site-packages/google/cloud/functions/worker.py", line 214, in call_user_function event_context.Context(**request_or_event.context)) File "/user_code/main.py", line 56, in stage1slemonthly df = df.append(pd.read_csv(io.StringIO(file_contents), header=None, names=[col_names])) TypeError: initial_value must be str or None, not bytes
请您参考如下方法:
您收到此错误是因为 file.download_as_string()
return type是 bytes
而不是 str
,并且您不能将 io.StringIO
与 bytes
参数一起使用(initial_value =file_contents
).
此外,col_names
在这里被定义为一个数组,所以写成pd.DataFrame(columns=[col_names])
和pd.read_csv(... , names=[col_names])
不正确:您应该使用 col_names
而不是 [col_names]
。
无论如何,这似乎不是从 Google Cloud Storage 读取 CSV 文件的正确方法。你宁愿写:
from google.cloud import storage
import pandas as pd
import io
storage_client = storage.Client()
source_bucket = storage_client.bucket(source_bucket)
col_names = ["Customer_Country_Number", "Customer_Name", ...]
df = pd.DataFrame(columns=col_names)
for file in list(source_bucket.list_blobs()):
file_path="gs://{}/{}".format(file.bucket.name, file.name)
df = df.append(pd.read_csv(file_path, header=None, names=col_names))
# the rest of your code
的确,你可以read files directly from GCS用pandas
的read_csv
方法代替下载文件加载,但是需要安装gcsfs
(pip3 install gcsfs
) 首先。