![]() ![]() I can also use Power Automate to convert that Excel file into CSV if needed as explained in this video: Microsoft Power Automate: How to convert Excel. Then press Ctrl+S (or click the save icon) and click 'Yes' at the warning Re-import (you don't even have to click 'Browse' again on Deckbox just click the 'Check file and import' button on the already-selected CSV). Set (The set name) Card (The card name) Regular (Regular non-foil quantity). The first option is to use the Excel connector and save the extracted data in an Excel file like this: Note that you will need to create an Excel file with a table with columns that you define. First of all, you can install the anki Python package using pip, e.g. Use Ctrl+H to Replace All for each affected edition. To build on gavenkoas answer, the Anki API has built-in functionality to import from CSV. coll file in the same directory which you can just open in Decked Builder to get. Once the conversion finishes, click the 'Download CSV' button to save the file. Convert to CSV by clicking the 'Convert' button. ![]() Edit 2: I did get it uploaded via the import CSV option by changing the categories and stuff but would still like to know if there is a way to do it via the Decked Builder upload CSV option so I dont have to change these categories. python convertmtgo.py /path/to/mtgocollection.csv. How to Convert to CSV Click the Choose Files button to select your files. Map(lambda csvFileName: baseDf.filter(col("input_file_name").endsWith(csvFileName)).write.mode('overwrite'). You'll find the Deckbox equivalent on the 'Editions' page. Edit: I am using the Decked Builder Upload CSV option. ![]() # Read csv files into a single data frame and add a column of input file names:īaseDf = ("input_folder/*.csv").withColumn("input_file_name", input_file_name())įilePathInfo = lect("input_file_name").distinct().collect()įilePathInfo_array = list(map(lambda row: row.input_file_name, filePathInfo)) Check out the article on Sealed Deck to learn more. This is a great way to build and play with a wide variety of decks, while still keeping the available resources (number of packs) constant across players. (same_folder/ ).write.parquet(output_folder/)īased on the QuickSilver's answer, here is my PySpark version: spark = ("local").appName("csv_to_parquet").getOrCreate() Sealed play, where each player builds a deck from a distinct set of 6 or more packs, is also supported. Is there any way I can utilize spark to do the batch processing? My current solution is: for each_csv in same_folder:ĭf = (each_csv, header = True) I have a large number of CSV files that need to be converted to parquet files, using pyspark. ![]()
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