Loading CSV seeds in dbt - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the path of the CSV seed file in the dbt project configuration.

dbt

seeds:
  my_project:
    [1]: data/my_seed.csv

Drag options to blanks, or click blank then click option'

Alocation

Bfile

Cpath

Dsource

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'file' or 'location' instead of 'path' causes dbt to not find the seed file.

The path key is used to specify the location of the CSV seed file in the dbt project configuration.

2fill in blank

medium

Complete the command to load seeds into the data warehouse using dbt.

dbt

dbt [1]

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Aseed

Bcompile

Cbuild

Drun

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'dbt run' instead of 'dbt seed' will not load seed files.

The dbt seed command loads CSV seed files into the data warehouse as tables.

3fill in blank

hard

Fix the error in the seed configuration to enable header rows in the CSV file.

dbt

seeds:
  my_project:
    my_seed:
      [1]: true

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Ainclude_header

Bheaders

Chas_header

Dheader

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'headers' or 'has_header' causes dbt to ignore the setting.

The correct key to enable headers in dbt seed configuration is header.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that loads seed data only for CSV files larger than 1MB.

dbt

large_seeds = {name: path for name, path in seeds.items() if [1]([2]) > 1048576 and [2].endswith('.csv')}

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Aos.path.getsize

Bname

Cpath

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'len' instead of 'os.path.getsize' for file size.

Using 'name' instead of 'path' to check file extension.

Use os.path.getsize to get file size and path to check the file extension.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps seed names to their row counts, filtering seeds with more than 100 rows.

dbt

seed_row_counts = { [1]: sum(1 for _ in open([2])) - 1 for [3], _ in seeds.items() if sum(1 for _ in open(_) ) - 1 > 100 }

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Aname

Bpath

Dfile

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'file' instead of 'path' to open the CSV.

Using inconsistent variable names causing errors.

The comprehension uses name as the key, path to open the file, and iterates over name and _ in seeds.items().