preserve helper logs on bounce #87
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Actionable comments posted: 1
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🔇 Files ignored due to path filters (1)
server/package-lock.jsonis excluded by!**/package-lock.json
📒 Files selected for processing (1)
- server/package.json (1 hunks)
| @@ -24,7 +24,7 @@ | |||
| "chartjs-adapter-spacetime": "^1.0.1", | |||
| "clsx": "^2.0.0", | |||
| "haikunator": "^2.1.2", | |||
| "next": "14.2.11", | |||
| "next": "=14.2.11", | |||
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🛠️ Refactor suggestion
Consider the trade-offs of exact version pinning
The change from "next": "^14.2.11" to "next": "=14.2.11" locks the Next.js version to exactly 14.2.11. While this ensures consistency across environments, it may prevent automatic security updates and bug fixes.
Consider these alternatives:
- Use a tilde (
~) instead of an equals sign to allow patch updates:"next": "~14.2.11" - Keep the caret (
^) to allow minor updates, but use a package lock file to ensure consistency. - If exact pinning is necessary, implement a process to regularly check for and manually update to new versions.
Could you explain the reasoning behind this exact version pinning? If it's to address a specific issue, consider documenting it in a comment.
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (1)
sidecar/app/routes/start.py (1)
64-65: Consider a more comprehensive approach to handling complex function signaturesWhile adding pylint disable comments addresses the immediate linter warnings, it doesn't solve the underlying issue of complex function signatures. This approach might lead to decreased code quality and maintainability in the long run.
Suggestions for improvement:
- Conduct a comprehensive review of function signatures across the project to identify patterns of overly complex functions.
- Develop a consistent strategy for handling complex parameter sets, such as using configuration objects or dataclasses.
- Consider creating a custom pylint plugin or configuration that aligns with your project's standards for function complexity.
- Document any decisions made about function complexity and parameter handling in your project's coding guidelines.
By addressing this issue systematically, you can improve overall code quality, maintainability, and consistency across the project.
Also applies to: 157-158
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📒 Files selected for processing (2)
- sidecar/app/routes/start.py (2 hunks)
- sidecar/cli/cli.py (2 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- sidecar/cli/cli.py
| # pylint: disable=too-many-arguments | ||
| # pylint: disable=too-many-positional-arguments |
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🛠️ Refactor suggestion
Consider refactoring to reduce the number of arguments
While adding pylint disable comments addresses the immediate linter warnings, it might be beneficial to consider refactoring the function to reduce the number of arguments. This could improve the function's maintainability and readability.
Potential refactoring options:
- Group related parameters into a configuration object or dataclass.
- Use keyword-only arguments to make the function calls more explicit.
- Consider if some of these parameters could be set as default configurations elsewhere.
Example refactoring:
from dataclasses import dataclass
@dataclass
class IPAHelperConfig:
gate_type: str
stall_detection: bool
multi_threading: bool
disable_metrics: bool
reveal_aggregation: bool
def start_ipa_helper(
query_id: str,
commit_hash: str,
config: IPAHelperConfig,
background_tasks: BackgroundTasks,
request: Request
):
# Function implementationThis approach would reduce the number of direct arguments and make the function signature cleaner.
| # pylint: disable=too-many-arguments | ||
| # pylint: disable=too-many-positional-arguments |
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🛠️ Refactor suggestion
Consider refactoring to reduce the number of arguments
Similar to the start_ipa_helper function, it would be beneficial to refactor this function to reduce the number of arguments. This can improve maintainability and readability of the code.
Suggested refactoring approach:
- Group related parameters into a configuration object or dataclass.
- Use keyword-only arguments for clarity.
Example refactoring:
from dataclasses import dataclass
@dataclass
class IPAQueryConfig:
size: int
max_breakdown_key: int
max_trigger_value: int
per_user_credit_cap: int
malicious_security: bool
def start_ipa_query(
query_id: str,
commit_hash: str,
config: IPAQueryConfig,
background_tasks: BackgroundTasks,
request: Request
):
# Function implementationThis refactoring would simplify the function signature and make it easier to add or modify parameters in the future without changing the function signature.
adds a timestamp to the log file that the draft process writes to, so that it's not overwritten when we restart draft.
Summary by CodeRabbit
nextpackage version specification to an exact version, preventing automatic updates.