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The Dispatch

The Dispatch Demo - openreplay/openreplay

Executive Summary

OpenReplay is a self-hosted session replay and analytics tool designed to help developers troubleshoot issues, co-browse with users, and optimize their web and mobile applications. It captures user interactions, network activity, console logs, JS errors, and various performance metrics to provide a comprehensive view of user sessions. The project is managed by the organization openreplay and has seen significant activity since its creation on April 29, 2021. The repository has 8,913 stars, 477 forks, and 121 open issues. The main programming language used is TypeScript.

Notable Elements

Recent Activity

Team Members & Recent Commits

Patterns and Conclusions

The team shows a collaborative effort in maintaining and improving the project with a clear division of responsibilities. The frequent commits indicate an active development cycle focused on both backend stability and frontend user experience enhancements.

Risks

Notable Issues

Disputes & Anomalies

Plans

Work in Progress

Todos

Conclusion

OpenReplay is actively maintained with regular updates and feature enhancements. However, there are several critical issues related to deployment configurations and build failures that need immediate attention. The team demonstrates strong collaboration and a clear division of responsibilities, ensuring continuous improvement in both backend stability and frontend user experience.

Quantified Commit Activity Over 14 Days

Developer Avatar Branches PRs Commits Files Changes
Delirium 8 2/1/0 12 139 7233
Shekar Siri 4 1/1/0 12 13 1784
dependabot[bot] 5 7/0/3 5 24 889
Alexander 3 2/2/0 5 9 88
Rajesh Rajendran 2 0/0/0 2 25 76
Kraiem Taha Yassine 2 4/4/0 6 8 50
Mehdi Osman 2 11/5/2 7 4 25
GitHub Action 6 0/0/0 6 4 18
Snyk bot 1 0/0/0 1 1 2

PRs: created by that dev and opened/merged/closed-unmerged during the period

Detailed Reports

Report On: Fetch commits



Project Overview

OpenReplay is a self-hosted session replay and analytics tool designed to help developers troubleshoot issues, co-browse with users, and optimize their web and mobile applications. It captures user interactions, network activity, console logs, JS errors, and various performance metrics to provide a comprehensive view of user sessions. OpenReplay supports web applications, iOS, and React Native apps, with plans to support Android and Flutter soon. The project is managed by the organization openreplay and has seen significant activity since its creation on April 29, 2021. The repository has 8,913 stars, 477 forks, and 121 open issues. The main programming language used is TypeScript.

Recent Activities of the Development Team

Reverse Chronological List of Recent Commits

2 days ago

7 days ago

10 days ago

11 days ago

  • Commit: Increment frontend chart version (#2172)

  • Commit: fix ui: fix EFS indexes check for reader (#2171)

  • Commit: chore(helm): Remove hardcoded ingress host

    • Author: Rajesh Rajendran (rjshrjndrn)
    • Files: plaintext scripts/helmcharts/openreplay/charts/alerts/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/alerts/values.yaml, scripts/helmcharts/openreplay/charts/assets/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/assets/values.yaml, scripts/helmcharts/openreplay/charts/canvas-handler/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/canvas-handler/values.yaml, scripts/helmcharts/openreplay/charts/canvas-maker/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/canvas-maker/values.yaml, scripts/helmcharts/openreplay/charts/db/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/db/values.yaml, scripts/helmcharts/openreplay/charts/ender/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/ender/values.yaml, scripts/helmcharts/openreplay/charts/heuristics/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/heuristics/values.yaml, scripts/helmcharts/openreplay/charts/imagestorage/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/imagestorage/values.yaml, scripts/helmcharts/openreplay/charts/integrations/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/integrations/values.yaml, scripts/helmcharts/openreplay/charts/sink/templates/ingress.yaml, scripts/helmcharts/openreplay/charts/sink/values.yaml, scripts/helmcharts/openreplay/charts/storage/templates/ ingress.yaml,scripts/ helm charts/ open replay/ charts/ storage/ values. yaml,scripts/ helm charts/ open replay/ charts/ video storage/ templates/ ingress. yaml,scripts/ helm charts/ open replay/ charts/ video storage/ values. yaml
  • Changes: +24,-48

Patterns and Conclusions

From the recent activities:

  • Mehdi Osman (estradino) frequently increments chart versions and collaborates with GitHub Actions.
  • Kraiem Taha Yassine (tahayk) focuses on fixing issues related to chalice and platform filters.
  • Shekar Siri (shekarsiri) works on UI changes and enhancements.
  • Alexander (zavorotynskiy) contributes to backend improvements and feature additions.
  • Delirium (nick-delirium) is heavily involved in UI fixes and enhancements across multiple files.
  • Rajesh Rajendran (rjshrjndrn) handles helm chart configurations and CI/CD improvements.
  • Dependabot[bot] regularly updates dependencies across various directories.

The team shows a collaborative effort in maintaining and improving the project with a clear division of responsibilities. The frequent commits indicate an active development cycle focused on both backend stability and frontend user experience enhancements.

Report On: Fetch issues



Analysis of Open Issues for openreplay/openreplay

Overview

The repository openreplay/openreplay currently has 121 open issues. This analysis will highlight notable problems, uncertainties, disputes, TODOs, and anomalies among the open issues. Closed issues are mentioned for context but are not the primary focus.

Notable Open Issues

Dependency Updates

  • #2194: build(deps): bump the pip group across 7 directories with 9 updates
    • Details: This issue involves updating multiple dependencies across various directories. The updates include critical packages like fastapi, urllib3, and pydantic.
    • Notable Points:
    • The updates span multiple directories (/api, /ee/api, /ee/connectors/deploy, /ee/intelligent_search, /ee/recommendation).
    • Potential risk of breaking changes or incompatibilities due to the extensive nature of these updates.
    • Auto-review was skipped by coderabbitai[bot].

Feature Requests

  • #2191: Discord integration
    • Details: Suggestion to support Discord integration for automatic error session notifications.
    • Notable Points:
    • Contributor willingness to submit a PR.
    • Potential for enhanced user engagement and real-time error tracking.

Deployment and Configuration Issues

  • #2187: Allow using existing secret in charts

    • Details: Proposal to allow using existing secrets in Helm charts.
    • Notable Points:
    • Enhances flexibility and security in deployment configurations.
    • Specific implementation details provided by the issue creator.

  • #2185: [Snyk] Security upgrade python from 3.11-alpine to 3.13.0b1-alpine

    • Details: Security upgrade recommendation for Docker base image.
    • Notable Points:
    • Addresses known vulnerabilities.
    • Ensures the application benefits from the latest security patches.

Bug Reports

  • #2180: Optional Chaining Breaks Build of NextJS React App Using Latest Tracker v12.0.12

    • Details: Optional chaining in the tracker package causes build failures in a NextJS app using Webpack 4.
    • Notable Points:
    • Significant impact on users with older build systems.
    • Workaround provided by the issue reporter.
    • Discussion on potential solutions and compatibility concerns.

  • #2108: Internal @openreplay/tracker bug: Uncaught (in promise) TypeError: .for is not iterable

    • Details: Error encountered during tracker initialization.
    • Notable Points:
    • Affects multiple frontend stacks (React, SvelteKit).
    • Debugging steps and potential fixes discussed in comments.

Enhancements and Improvements

  • #2186: feat ui/tracker: add compression to assist plugin

    • Details: Adds message compression capabilities to the assist plugin.
    • Notable Points:
    • Improves efficiency in message handling.
    • Detailed walkthrough provided by coderabbitai[bot].

  • #2179: Updated patch build from main 2401449a4ae38ddf1094068de67e84ea45be3834

    • Details: Updates Helm chart version after building a patch.
    • Notable Points:
    • Routine maintenance task with potential impact on deployment stability.

Uncertainties and Disputes

  • #2147: Deploy to K8S ... can't init postgres connection: pgxpool.Connect error

    • Details: Deployment issue on EKS with PostgreSQL connection errors.
    • Notable Points:
    • Unclear cause of connection failure.
    • Requires further investigation and potentially more detailed error logs.

  • #2146: build(deps): bump pydantic[email] from 2.3.0 to 2.7.1

    • Details: Dependency update for pydantic[email].
    • Notable Points:
    • Auto-review skipped by coderabbitai[bot].
    • Potential for breaking changes given the significant version jump.

Anomalies

  • #2145: build(deps): bump redis from 5.0.3 to 5.0.4
    • Details: Minor version bump for Redis dependency.
    • Notable Points:
    • Auto-review skipped by coderabbitai[bot].
    • Typically low-risk but still requires verification.

Recently Closed Issues

Conclusion

The project is actively maintained with regular dependency updates and feature enhancements. However, there are several critical issues related to deployment configurations and build failures that need immediate attention. The community engagement is strong with contributors willing to provide fixes and enhancements. The use of automated tools like coderabbitai[bot] helps streamline reviews but may miss nuanced issues requiring human oversight.

Report On: Fetch pull requests



Analysis of Pull Requests

Notable Open Pull Requests

PR #2194: build(deps): bump the pip group across 7 directories with 9 updates

  • State: Open
  • Created: 1 day ago
  • Details: This PR involves multiple dependency updates across various directories. The packages being updated include fastapi, urllib3, pydantic, gunicorn, and others.
  • Issues:
    • The PR has been auto-generated and skipped review by the bot, which might miss critical issues.
    • The CLA status is pending, which needs to be resolved before merging.
    • Given the wide range of updates, thorough testing is required to ensure no breaking changes are introduced.

PR #2190: build(deps): bump boto3 from 1.34.84 to 1.34.103

  • State: Open
  • Created: 4 days ago
  • Details: Updates boto3 from version 1.34.84 to 1.34.103.
  • Issues:
    • Similar to PR #2194, this PR was also auto-generated and skipped review.
    • The CLA status is pending.
    • Dependency updates should be tested for compatibility with existing code.

PR #2186: feat ui/tracker: add compression to assist plugin

  • State: Open
  • Created: 7 days ago
  • Details: Adds compression capabilities to the assist plugin.
  • Issues:
    • CodeRabbit identified that the version update is not covered by tests, which is a significant issue.
    • Error handling improvements were suggested but not yet implemented.
    • The PR introduces changes that need comprehensive testing to ensure stability.

Notable Recently Closed Pull Requests

PR #2193: Updated patch build from main 5b5df8bf3264e8992184c4c6cd8e10f8744424b7

  • State: Closed (Merged)
  • Created: 2 days ago, Closed: 2 days ago
  • Details: This PR updates the Helm chart version after building the patch from a specific commit.
  • Significance:
    • Routine update but essential for maintaining version consistency.

PR #2192: fix(chalice): fixed funnels

  • State: Closed (Merged)
  • Created: 2 days ago, Closed: 2 days ago
  • Details: Fixes issues related to funnels in the Chalice service.
  • Significance:
    • Important bug fix ensuring the correct functionality of funnels.
    • Addressed permissions issues which could have security implications.

PR #2188: Change UI minor

  • State: Closed (Merged)
  • Created: 7 days ago, Closed: 7 days ago
  • Details: Minor UI changes and improvements.
  • Significance:
    • Enhances user experience with minor tweaks and fixes.

Notable Closed Without Merge

PR #2183: build(deps): bump the pip group across 7 directories with 9 updates

  • State: Closed (Not Merged)
  • Created: 9 days ago, Closed: 1 day ago
  • Details: Similar to PR #2194 but closed without merging.
  • Significance:
    • Superseded by another PR (#2194), indicating ongoing dependency management efforts.

Summary

The project has several open pull requests primarily focused on dependency updates and feature enhancements. However, there are notable issues such as pending CLA statuses and skipped reviews that need attention. Recently closed pull requests indicate active maintenance and bug fixing, which is crucial for project stability. Special attention should be given to open pull requests involving significant changes or multiple dependency updates to ensure they do not introduce new issues.

Report On: Fetch PR 2194 For Assessment



PR #2194

Summary

This pull request involves updating various dependencies across multiple directories within the openreplay/openreplay repository. Specifically, it updates several Python packages in the /api, /ee/api, /ee/connectors/deploy, /ee/intelligent_search, and /ee/recommendation directories. The updates include changes to fastapi, urllib3, pydantic, gunicorn, python-multipart, idna, pycryptodomex, mlflow, and apache-airflow.

Detailed Analysis

Changes

  1. API Directory

    • fastapi: Updated from 0.104.1 to 0.109.1
    • urllib3: Updated from 1.26.16 to 1.26.18
    • pydantic: Updated from 2.3.0 to 2.4.0

  2. EE API Directory

    • fastapi: Updated from 0.104.1 to 0.109.1
    • urllib3: Updated from 1.26.16 to 1.26.18
    • pydantic: Updated from 2.3.0 to 2.4.0
    • gunicorn: Updated from 21.2.0 to 22.0.0
    • python-multipart: Updated from 0.0.6 to 0.0.7

  3. EE Connectors Deploy Directory

    • urllib3: Updated from various versions (1.26.12, etc.) to 1.26.18
    • idna: Updated from 3.4 to 3.7
    • pycryptodomex: Updated from 3.18.0 to 3.19.1

  4. EE Intelligent Search Directory

    • fastapi: Updated from 0.103.1 to 0.109.1
    • pydantic: Updated from 2.3.0 to 2.4.0

  5. EE Recommendation Directory

    • fastapi: Updated from various versions (0.95.2, etc.) to 0.109.1
    • urllib3: Updated from various versions (1.26.x) to 1.26.x
    • pydantic: Updated from various versions (1.x) to latest
    • python-multipart: Updated from various versions (0.x) to latest
    • mlflow: Updated from various versions (2.x) to latest
    • apache-airflow: Updated from various versions (2.x) to latest

Code Quality Assessment

  • The updates are primarily dependency bumps, which do not introduce new functionality but ensure that the project uses the latest versions of its dependencies.
  • The changes are straightforward and involve modifying version numbers in the respective requirement files.
  • It is crucial to test these updates thoroughly in a staging environment before deploying them to production, as dependency updates can sometimes introduce breaking changes or incompatibilities.

Recommendations

  • Ensure that all tests pass successfully after applying these updates.
  • Perform integration testing, especially for critical paths that depend on these libraries.
  • Monitor the application closely after deployment for any unexpected behavior or performance issues.

Conclusion

The dependency updates in PR #2194 are essential for keeping the project up-to-date with the latest versions of its dependencies, which can include important security patches and performance improvements.

PR #2186

Summary

This pull request introduces a new feature related to message compression in the assist plugin within the OpenReplay tracker system.

Detailed Analysis

Changes

  • Adds compression capabilities for messages in the assist plugin.
  • Refactors message processing logic.
  • Updates event handling mechanisms.
  • Minor improvements like removing whitespace contribute to code cleanliness and efficiency.

Code Quality Assessment

  • The code introduces a significant new feature (message compression), which could have a substantial impact on performance and functionality.
  • Error handling has been improved in the message compression method, ensuring robustness during compression.
  • The changes are well-documented, with clear comments explaining the purpose of each modification.

Recommendations

  • Ensure comprehensive testing of the new compression feature, including edge cases where compression might fail.
  • Monitor performance metrics before and after deploying this change to understand its impact on system performance.
  • Consider adding more unit tests specifically for the new compression logic.

Conclusion

The introduction of message compression in PR #2186 is a valuable enhancement that can improve performance by reducing message sizes during transmission, but it requires thorough testing and monitoring.

Overall, both PRs #2194 and #2186 bring important updates and enhancements to the OpenReplay project, focusing on dependency management and performance improvements through message compression, respectively.

Report On: Fetch Files For Assessment



Source Code Assessment

1. api/chalicelib/core/significance.py

URL: significance.py

Structure and Quality Analysis:

  • Imports and Dependencies:

    • The file imports necessary modules and dependencies in a structured manner.
    • It uses both internal (chalicelib, schemas) and external libraries (psycopg2, math, warnings).

  • Constants and Configuration:

    • Constants like SIGNIFICANCE_THRSH and T_VALUES are defined at the top, making them easily configurable.

  • Functions:

    • Functions are well-defined with clear responsibilities.
    • Docstrings are present in some functions, but not all. Adding docstrings for all functions would improve readability.
    • The function get_stages_and_events is quite complex and could benefit from breaking down into smaller helper functions.
    • Use of list comprehensions and dictionary comprehensions is efficient.

  • Error Handling:

    • Error handling is present, especially in database operations, which is crucial for robustness.

  • Logging:

    • Logging is used effectively to trace the execution flow and debug issues.

  • Performance Considerations:

    • The code seems to handle large datasets (e.g., sessions and events) efficiently using SQL queries and Python data structures.
    • There are comments indicating potential performance improvements (e.g., removing LIMIT from queries).

  • Code Style:

    • The code follows PEP8 standards for the most part.
    • Some inline comments could be converted to proper docstrings.

Recommendations:

  1. Add docstrings to all functions for better documentation.
  2. Break down complex functions into smaller, more manageable helper functions.
  3. Ensure consistent use of type hints across all functions.

2. ee/api/schemas/schemas_ee.py

URL: schemas_ee.py

Structure and Quality Analysis:

  • Imports and Dependencies:

    • The file imports necessary modules from Pydantic, a popular data validation library, ensuring robust schema definitions.

  • Class Definitions:

    • Classes are well-defined with clear attributes and validation rules.
    • Use of Pydantic's Field for attribute definitions ensures proper validation and default values.

  • Enums:

    • Enums are used effectively to define constant values, improving code readability and maintainability.

  • Validators:

    • Custom validators are defined using Pydantic's @model_validator, ensuring data integrity.

  • Code Style:

    • Follows PEP8 standards.
    • Consistent use of type hints enhances readability and maintainability.

Recommendations:

  1. Ensure all classes have comprehensive docstrings explaining their purpose and usage.
  2. Consider adding more detailed validation error messages where applicable.

3. backend/internal/assets/cacher/cacher.go

URL: cacher.go

Structure and Quality Analysis:

  • Imports and Dependencies:

    • Imports are organized logically, separating standard library imports from third-party packages.

  • Struct Definitions:

    • Structs like cacher are well-defined with clear fields representing the state of the cacher.

  • Concurrency Handling:

    • Uses concurrency effectively with channels (timeoutMap, workers) to manage tasks.

  • Error Handling:

    • Errors are handled using Go's idiomatic error wrapping, providing context for debugging.

  • Performance Considerations:

    • The code seems optimized for performance, with considerations for caching depth (MAX_CACHE_DEPTH) and timeouts.

  • Code Style:

    • Follows Go's idiomatic practices.
    • Function names are descriptive, indicating their purpose clearly.

Recommendations:

  1. Add comments or docstrings to explain the purpose of each struct and method.
  2. Consider adding more detailed logging for critical operations to aid in debugging.

4. frontend/app/components/UsabilityTesting/TestOverview.tsx

URL: TestOverview.tsx

Structure and Quality Analysis:

  • Imports and Dependencies:

    • Imports are organized logically, separating React imports from other libraries.

  • Component Definition:

    • Functional components are used effectively with hooks (useEffect, useState) to manage state.

  • UI Elements:

    • Uses Ant Design components (Button, Typography, Select) for consistent UI design.

  • State Management:

    • Uses MobX for state management (useStore), ensuring a reactive UI.

  • Code Style:

    • Follows TypeScript best practices with type annotations enhancing readability.

Recommendations:

  1. Break down large components into smaller sub-components to improve readability and maintainability.
  2. Add JSDoc comments to describe the purpose of each component and its props.

5. frontend/app/styles/global.scss

URL: global.scss

Structure and Quality Analysis:

  • Styles Definition:

    • Defines global styles affecting multiple components (form-field, .capitalize-first).

  • Use of SCSS Features:

    • Utilizes SCSS features like nesting (@apply, .lucide) for cleaner style definitions.

Recommendations:

  1. Ensure consistent naming conventions for class names to avoid conflicts.
  2. Consider organizing styles into separate SCSS files if the global styles grow larger.

6. backend/internal/storage/storage.go

URL: storage.go

Structure and Quality Analysis:

  • Imports and Dependencies:

    • Imports are organized logically, separating standard library imports from third-party packages.

  • Struct Definitions:

    • Structs like Storage are well-defined with clear fields representing the state of the storage system.

  • Concurrency Handling:

    • Uses concurrency effectively with channels (compressionTasks, uploadingTasks) to manage tasks.

  • Error Handling:

    • Errors are handled using Go's idiomatic error wrapping, providing context for debugging.

  • Performance Considerations:

    • The code seems optimized for performance, with considerations for compression algorithms (gzip, brotli, zstd) and task management.

  • Code Style:

    • Follows Go's idiomatic practices.

Recommendations:

  1. Add comments or docstrings to explain the purpose of each struct and method.
  2. Consider adding more detailed logging for critical operations to aid in debugging.

7. backend/pkg/objectstorage/s3/s3.go

URL: s3.go

Structure and Quality Analysis:

  • Imports and Dependencies:

    • Imports are organized logically, separating standard library imports from third-party packages.

  • Struct Definitions:

    • Structs like storageImpl are well-defined with clear fields representing the state of the S3 storage implementation.

  • Concurrency Handling:

    • Uses concurrency effectively with AWS SDK clients which are safe for concurrent use.

  • Error Handling:

    • Errors are handled using Go's idiomatic error wrapping, providing context for debugging.

Recommendations:

  1. Add comments or docstrings to explain the purpose of each struct and method.
  2. Consider adding more detailed logging for critical operations to aid in debugging.

8. frontend/app/player/web/MessageLoader.ts

URL: MessageLoader.ts

Structure and Quality Analysis:

  • Imports and Dependencies:

    • Imports are organized logically, separating internal modules from third-party packages.

  • Class Definition:

    • Class-based component is used effectively with methods managing different aspects of message loading (loadFiles, processMessages).

  • State Management:

    • Uses a store pattern to manage state effectively within the class (store.update).

Recommendations:

  1. Add JSDoc comments to describe the purpose of each method within the class.
  2. Break down large methods into smaller helper methods where possible to improve readability.

Conclusion

The source code files provided exhibit good structure and quality overall, adhering to best practices in their respective languages (Python, Go, TypeScript). However, there is room for improvement in terms of documentation (docstrings/comments) across all files to enhance readability and maintainability. Additionally, breaking down complex functions/methods into smaller units can further improve code clarity.