It's unclear to me what's wrong, as I've seen os. "FileNotFoundError: The system cannot find the file specified:" "FileNotFoundError Traceback (most recent call last)" We use () method which takes in the path along with the filename where you want to save the CSV as input parameter and saves the generated CSV data in Step 3 as CSV. The error occurs on the os.rename function. Os.rename(os.path.join(root,file),os.path.join(root,newname)) #print(newname, os.path.join(root,newname)) My code (barely modified from an answer to this question How to append the grand-parent folder name to the filename?) import os.path It renames all appropriately in one folder and gets through about half of another folder before I get a FileNotFoundError.
I have code that basically works, but it breaks after successfully naming ~5 files. I really like this visual way to transform (flatten) a sourcing JSON stream into a CSV file.I'm trying to rename a number of csv files I have nested in multiple subfolders with the name of an upper folder as a prefix e.g.įolder1 and Folder 2 both are subfolders to another larger folder as well. All next Flatten transformation tasks' outputs were tripled in their results, and my final Output file contained all 41 expected records! Source file Data Preview correctly showed me 3 rows. Let's use this JSON data file as an example
And when this vertical JSON structural set contains several similar sets (array) then ADF Mapping Data Flows Flatten does a really good job by transforming it into a table with several rows (records). I like the analogy of the Transpose function in Excel that helps to rotate your vertical set of data pairs ( name : value) into a table with the column names and values for corresponding objects. Part 2: Transforming JSON to CSV with the help of Flatten task in Azure Data Factory - Part 2 (Wrangling data flows) What this new task does it helps to transform/transpose/flatten your JSON structure into a denormalized flatten datasets that you can upload into a new or existing flat database table. (2020-Mar- 19) Recently, Microsoft introduced a new Flatten task to the existing set of powerful transformations available in the Azure Data Factory (ADF) Mapping Data Flows.
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