import logging
import json
import pandas as pandas
import sys

logging_filename = "../logs/ingestion.log"
logging.basicConfig(filename=logging_filename, level=logging.DEBUG)
logging.getLogger().addHandler(logging.StreamHandler())

def make_draft_json(filename, tablename):

    # Creates dataframe variable.
    dataframe_file = pandas.read_csv(filename)

    # Iterate over this.
    dataframe_iterator = dataframe_file.columns

    # JSON structure skeleton based on meta.json.
    output = {
        tablename: {
            "fields": []
        }
    }

    # We get our data here. We'll add additional field info.
    for field in dataframe_iterator:
        data = {
            field: {
                "data_type": str(dataframe_file[field].dtypes),
                "source_name": field,
                "default_text":""
            }
        }
        # Push created data into Output object
        output[tablename]["fields"].append(data)

    # Write to JSON file.
    with open("test_results.json", "w") as results:
        json.dump(output, results, sort_keys=True, indent=4)

if __name__ == '__main__':

    # Since we know that we're inserting our filepath and table_name on the command line as args 1 and 2, do we need a loop like you had in your example??

    csv_filename = sys.argv[1]
    table_name = sys.argv[2]

    make_draft_json(csv_filename, table_name)