MrGiovanni / MrGiovanni/ModelsGenesis
Columns and DataType Not Explicitly Set on line 18 of load_utils.py
Nobody has claimed this yet.
- Dominant language
- Jupyter Notebook
- Stars
- 791
- Forks
- 141
- PR merge metrics
- No merged PRs in 30d
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
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- 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