MrGiovanni / MrGiovanni/ModelsGenesis

Columns and DataType Not Explicitly Set on line 18 of load_utils.py

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Description

Hello!

I found an AI-Specific Code smell in your project.
The smell is called: Columns and DataType Not Explicitly Set

You can find more information about it in this paper: https://dl.acm.org/doi/abs/10.1145/3522664.3528620.

According to the paper, the smell is described as follows:

Problem If the columns are not selected explicitly, it is not easy for developers to know what to expect in the downstream data schema. If the datatype is not set explicitly, it may silently continue the next step even though the input is unexpected, which may cause errors later. The same applies to other data importing scenarios.
Solution It is recommended to set the columns and DataType explicitly in data processing.
Impact Readability

Example:


### Pandas Column Selection
import pandas as pd
df = pd.read_csv('data.csv')
+ df = df[['col1', 'col2', 'col3']]

### Pandas Set DataType
import pandas as pd
- df = pd.read_csv('data.csv')
+ df = pd.read_csv('data.csv', dtype={'col1': 'str', 'col2': 'int', 'col3': 'float'})

You can find the code related to this smell in this link: https://github.com/MrGiovanni/ModelsGenesis/blob/bea0ec26cccc42b9c408fe02154a88f49ddc1b1d/keras/downstream_tasks/BraTS/load_utils.py#L8-L28.

I also found instances of this smell in other files, such as:

.

I hope this information is helpful!

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading keras/downstream_tasks/BraTS/load_utils.py lines 8-28 and trace how the loaded data is used downstream. Identify the expected columns and data types from the surrounding code, then verify that explicit definitions preserve the existing processing behavior and pass the applicable project checks.

Written by the indexing model from the issue text.

Assessment

Tech stack
pandas, python
Domain
data, machine-learning
Issue type
Refactor
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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