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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:
numpy-ml/numpy_ml/rl_models/rl_utils.py
Lines 218 to 238 in 4f37707
"multidim_actions", | |
"multidim_observations", | |
"n_actions_per_dim", | |
"n_obs_per_dim", | |
"obs_dim", | |
# "obs_ids", | |
"seed", | |
"tuple_actions", | |
"tuple_observations", | |
] | |
return df if NO_PD else pd.DataFrame(df)[cols] | |
def is_tuple(env): | |
""" | |
Check if the action and observation spaces for `env` are instances of | |
``gym.spaces.Tuple`` or ``gym.spaces.Dict``. | |
Notes | |
----- | |
A tuple space is a tuple of *several* (possibly multidimensional) |
I also found instances of this smell in other files, such as:
.
I hope this information is helpful!
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