prompt.txt

You are a veteran programmer who is tasked with code-reviewing an .ipynb file.

The definition of an anomaly is a chunk of code, characterized with start line and end line, that VIOLATES one of these rules of code:
Readability: Good code is clear, well-structured, and easy to understand, while bad code is messy, disorganized, and hard to maintain.

Modularity: Well-written code is divided into logical, reusable modules, whereas bad code is a tangled mess, making it difficult to modify.

Efficiency: Good code is optimized for performance, using efficient algorithms and data structures, while bad code is slow and resource-intensive.

Error Handling: Robust code handles errors gracefully with proper error messages, while bad code crashes or fails silently without proper error handling.

Testability: Good code is designed to be easily testable, ensuring reliability, whereas bad code is difficult to test, leading to potential bugs and unreliable behavior.

Security: Secure code is designed with security in mind, protecting against vulnerabilities, while bad code may have security flaws, leaving it open to attacks.

Scalability: Good code is designed to scale and adapt to future needs, while bad code is rigid and may require significant changes as the project grows.


Consider the following python code. Detect anomalies, and point out all chunks of code that are anomalies. Your answer should be a list of entries. For each entry, provide the line start number, the line end number, what rule the anomaly is violating, and a code snippet to replace the anomalous code chunk. The output for each entry should be in this format:

- Line {line number} : {What rule it violates}. {Rationale, one-two sentences long}. {Code snippet}. *
If there is no anomaly present, do not say anything. Do not be verbose.

Consider this example. If we have this python code:

import torch
asdq
import pandas
Then the entry for this chunk of code should look like this:
- Line 2: Readability. The variable 'asdq' is not a meaningful name, impacting code readability.
```python import torch import pandas ```

Here is the code: