Code snippet that demonstrates how to use Great Expectations to validate Excel files

ge_excel.py

import datetime
import pandas as pd
import great_expectations as ge
import great_expectations.jupyter_ux
from great_expectations.data_context.types.resource_identifiers import (
    ValidationResultIdentifier,
)

# You'll have to run `great_expectations init` to create a context that can be loaded here
# I also had to set up a "dummy" datasource called data__dir pointing at a directory 
# using `great_expectations datasource new`
context = ge.data_context.DataContext()

# Load the data from Excel
excel_df = pd.read_excel("my_excel_file_path", header=1)

# Create a new batch and start adding expectations
batch_kwargs = {
    "dataset": excel_df,
    "datasource": "data__dir"
}
batch = context.get_batch(
    batch_kwargs = batch_kwargs,
    expectation_suite_name = "my_suite"
)
batch.head()
batch.expect_column_values_to_not_be_null("vendor_id")

# Use the standard worfklow to save the suite to file
batch.save_expectation_suite(discard_failed_expectations=False)

results = context.run_validation_operator("action_list_operator", assets_to_validate=[batch])
validation_result_identifier = results.list_validation_result_identifiers()[0]

# This builds and opens data docs
context.build_data_docs()
context.open_data_docs(validation_result_identifier)

How do I generate expectation suite automatically for mulitple csv/excel files?