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Add problem statement and ecosystem sections to docs
- Add problem statement before Key Features explaining challenges of tracking experiments with changing parameters, code, dependencies, and environment - Add ecosystem/alternatives section with links to MLflow, Weights & Biases, Neptune.ai, Comet ML - Updated both README.md and docs/user-guide.rst for consistency
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‎.github/ISSUE_TEMPLATE/bug_report.yml‎

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name: Bug Report
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description: File a bug report
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title: "[Bug]: "
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labels: ["bug"]
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body:
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- type: markdown
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attributes:
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value: |
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Thanks for taking the time to fill out this bug report!
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- type: textarea
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id: what-happened
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attributes:
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label: What happened?
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description: A clear description of what the bug is
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placeholder: Tell us what you see!
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validations:
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required: true
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- type: textarea
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id: reproduce
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attributes:
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label: Steps to reproduce
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description: How do we reproduce this?
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placeholder: |
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1.
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2.
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3.
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validations:
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required: true
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- type: textarea
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id: expected
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attributes:
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label: Expected behavior
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description: What did you expect to happen?
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validations:
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required: true
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- type: input
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id: version
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attributes:
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label: Version
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description: What version of Artifacta are you running?
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placeholder: "0.1.1"
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validations:
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required: true
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- type: dropdown
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id: os
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attributes:
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label: Operating System
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options:
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- macOS
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- Linux
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- Windows
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- Other
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validations:
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required: true
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- type: input
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id: python-version
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attributes:
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label: Python Version
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placeholder: "3.11"
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validations:
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required: true
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- type: textarea
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id: logs
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attributes:
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label: Relevant log output
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description: Please copy and paste any relevant log output
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render: shell
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- type: textarea
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id: additional
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attributes:
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label: Additional context
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description: Add any other context about the problem here

‎.github/ISSUE_TEMPLATE/config.yml‎

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blank_issues_enabled: false
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contact_links:
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- name: Ask a Question
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url: https://github.com/walkerbdev/artifacta/discussions
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about: Ask questions and discuss with the community

‎.github/ISSUE_TEMPLATE/feature_request.yml‎

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name: Feature Request
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description: Suggest an idea for this project
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title: "[Feature]: "
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labels: ["enhancement"]
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body:
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- type: markdown
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attributes:
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value: |
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Thanks for suggesting a new feature!
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- type: textarea
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id: problem
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attributes:
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label: Is your feature request related to a problem?
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description: A clear description of what the problem is
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placeholder: I'm always frustrated when...
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- type: textarea
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id: solution
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attributes:
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label: Describe the solution you'd like
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description: A clear description of what you want to happen
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validations:
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required: true
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- type: textarea
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id: alternatives
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attributes:
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label: Describe alternatives you've considered
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description: Any alternative solutions or features you've considered
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- type: textarea
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id: use-case
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attributes:
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label: Use case
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description: Describe your use case and how this feature would help
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validations:
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required: true
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- type: textarea
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id: additional
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attributes:
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label: Additional context
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description: Add any other context or screenshots about the feature request

‎.github/pull_request_template.md‎

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## Description
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Please include a summary of the changes and the related issue.
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Fixes # (issue)
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## Type of change
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- [ ] Bug fix (non-breaking change which fixes an issue)
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- [ ] New feature (non-breaking change which adds functionality)
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- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
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- [ ] Documentation update
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## How Has This Been Tested?
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Please describe the tests that you ran to verify your changes.
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- [ ] Test A
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- [ ] Test B
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## Checklist
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- [ ] My code follows the style guidelines of this project
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- [ ] I have performed a self-review of my own code
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- [ ] I have commented my code, particularly in hard-to-understand areas
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- [ ] I have made corresponding changes to the documentation
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- [ ] My changes generate no new warnings
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- [ ] I have added tests that prove my fix is effective or that my feature works
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- [ ] New and existing unit tests pass locally with my changes
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- [ ] I have run `pre-commit run --all-files` and it passes

‎CODE_OF_CONDUCT.md‎

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# Contributor Covenant Code of Conduct
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## Our Pledge
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We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, or sexual identity and orientation.
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We pledge to act and interact in ways that contribute to an open, welcoming, diverse, inclusive, and healthy community.
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## Our Standards
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Examples of behavior that contributes to a positive environment for our community include:
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* Demonstrating empathy and kindness toward other people
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* Being respectful of differing opinions, viewpoints, and experiences
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* Giving and gracefully accepting constructive feedback
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* Accepting responsibility and apologizing to those affected by our mistakes, and learning from the experience
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* Focusing on what is best not just for us as individuals, but for the overall community
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Examples of unacceptable behavior include:
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* The use of sexualized language or imagery, and sexual attention or advances of any kind
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* Trolling, insulting or derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or email address, without their explicit permission
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* Other conduct which could reasonably be considered inappropriate in a professional setting
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## Enforcement Responsibilities
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Community leaders are responsible for clarifying and enforcing our standards of acceptable behavior and will take appropriate and fair corrective action in response to any behavior that they deem inappropriate, threatening, offensive, or harmful.
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Community leaders have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, and will communicate reasons for moderation decisions when appropriate.
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## Scope
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This Code of Conduct applies within all community spaces, and also applies when an individual is officially representing the community in public spaces. Examples of representing our community include using an official e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at [INSERT CONTACT METHOD]. All complaints will be reviewed and investigated promptly and fairly.
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All community leaders are obligated to respect the privacy and security of the reporter of any incident.
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## Enforcement Guidelines
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Community leaders will follow these Community Impact Guidelines in determining the consequences for any action they deem in violation of this Code of Conduct:
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### 1. Correction
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**Community Impact**: Use of inappropriate language or other behavior deemed unprofessional or unwelcome in the community.
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**Consequence**: A private, written warning from community leaders, providing clarity around the nature of the violation and an explanation of why the behavior was inappropriate. A public apology may be requested.
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### 2. Warning
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**Community Impact**: A violation through a single incident or series of actions.
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**Consequence**: A warning with consequences for continued behavior. No interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, for a specified period of time. This includes avoiding interactions in community spaces as well as external channels like social media. Violating these terms may lead to a temporary or permanent ban.
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### 3. Temporary Ban
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**Community Impact**: A serious violation of community standards, including sustained inappropriate behavior.
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**Consequence**: A temporary ban from any sort of interaction or public communication with the community for a specified period of time. No public or private interaction with the people involved, including unsolicited interaction with those enforcing the Code of Conduct, is allowed during this period. Violating these terms may lead to a permanent ban.
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### 4. Permanent Ban
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**Community Impact**: Demonstrating a pattern of violation of community standards, including sustained inappropriate behavior, harassment of an individual, or aggression toward or disparagement of classes of individuals.
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**Consequence**: A permanent ban from any sort of public interaction within the community.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 2.1, available at [https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
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Community Impact Guidelines were inspired by [Mozilla's code of conduct enforcement ladder][Mozilla CoC].
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For answers to common questions about this code of conduct, see the FAQ at [https://www.contributor-covenant.org/faq][FAQ]. Translations are available at [https://www.contributor-covenant.org/translations][translations].
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[homepage]: https://www.contributor-covenant.org
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[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
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[Mozilla CoC]: https://github.com/mozilla/diversity
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[FAQ]: https://www.contributor-covenant.org/faq
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[translations]: https://www.contributor-covenant.org/translations
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‎README.md‎

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---
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## 🎯 The Problem
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Modern data science and machine learning workflows involve countless experiments—tweaking hyperparameters, adjusting data preprocessing, testing different architectures, updating dependencies, modifying code. **Every change produces different results**, but tracking and comparing these variations manually becomes overwhelming:
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- 📋 Which parameters, environment, or code version led to that breakthrough result last week?
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- 🔍 How does changing the learning rate affect convergence across multiple runs?
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- 📊 What's the actual performance difference between model architectures?
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- 🤔 Which preprocessing steps improved accuracy by 2%?
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- 🔧 Did upgrading that dependency break model performance?
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- 💻 What code changes caused the regression?
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Without systematic tracking of **parameters, metrics, code changes, dependencies, and environment**, you're flying blind—relying on scattered notes, terminal output, and memory. **Artifacta solves this** by automatically capturing experiments, configurations, code versions, and artifacts in one place with intelligent visualization.
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---
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## 🌍 Ecosystem & Alternatives
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Artifacta is part of a growing ecosystem of experiment tracking tools. Popular alternatives include:
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- [**MLflow**](https://mlflow.org/) - Open-source platform from Databricks for ML lifecycle management
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- [**Weights & Biases**](https://wandb.ai/) - Cloud-first experiment tracking with team collaboration features
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- [**Neptune.ai**](https://neptune.ai/) - Metadata store for MLOps with extensive integrations
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- [**Comet ML**](https://www.comet.com/) - ML platform with experiment tracking and model production monitoring
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**Why Artifacta?** We focus on **automatic visualization discovery**, **domain-agnostic tracking** (not just ML), and **simple self-hosting** with a pre-built UI. No heavy dependencies, no mandatory cloud services—just install and start tracking.
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---
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## ✨ Key Features
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- 🌐 **Domain-agnostic** - Track any experiment comparing parameters, data, and outcomes
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### Installation
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#### Standard Installation
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**Prerequisites:** Python 3.9+
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```bash
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# Clone the repository
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git clone https://github.com/walkerbdev/artifacta.git
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cd artifacta
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# Install Python package
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pip install -e .
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pip install artifacta
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```
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**Note:** The UI is pre-built and bundled. No Node.js required.
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That's it! The UI is pre-built and bundled. No Node.js required.
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#### Development Installation
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If you want to contribute or modify the source:
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**Prerequisites:** Python 3.9+, Node.js 16+
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```bash
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# Build UI from source
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# Install Python package
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# Install Python package in editable mode
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pip install -e .
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```
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‎docs/user-guide.rst‎

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Quick Start Guide
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=================
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The Problem
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-----------
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Modern data science and machine learning workflows involve countless experiments—tweaking hyperparameters, adjusting data preprocessing, testing different architectures, updating dependencies, modifying code. **Every change produces different results**, but tracking and comparing these variations manually becomes overwhelming:
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- 📋 Which parameters, environment, or code version led to that breakthrough result last week?
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- 🔍 How does changing the learning rate affect convergence across multiple runs?
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- 📊 What's the actual performance difference between model architectures?
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- 🤔 Which preprocessing steps improved accuracy by 2%?
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- 🔧 Did upgrading that dependency break model performance?
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- 💻 What code changes caused the regression?
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Without systematic tracking of **parameters, metrics, code changes, dependencies, and environment**, you're flying blind—relying on scattered notes, terminal output, and memory. **Artifacta solves this** by automatically capturing experiments, configurations, code versions, and artifacts in one place with intelligent visualization.
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Ecosystem & Alternatives
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------------------------
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Artifacta is part of a growing ecosystem of experiment tracking tools. Popular alternatives include:
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- `MLflow <https://mlflow.org/>`_ - Open-source platform from Databricks for ML lifecycle management
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- `Weights & Biases <https://wandb.ai/>`_ - Cloud-first experiment tracking with team collaboration features
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- `Neptune.ai <https://neptune.ai/>`_ - Metadata store for MLOps with extensive integrations
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- `Comet ML <https://www.comet.com/>`_ - ML platform with experiment tracking and model production monitoring
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**Why Artifacta?** We focus on **automatic visualization discovery**, **domain-agnostic tracking** (not just ML), and **simple self-hosting** with a pre-built UI. No heavy dependencies, no mandatory cloud services—just install and start tracking.
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Installation
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------------
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Standard Installation
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~~~~~~~~~~~~~~~~~~~~~
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For most users, this is the recommended installation method:
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.. code-block:: bash
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# Clone the repository
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git clone https://github.com/walkerbdev/artifacta.git
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cd artifacta
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# Install Python package with bundled UI
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pip install -e .
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pip install artifacta
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For contributors who want to modify the UI:
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For contributors who want to modify the source code or UI:
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# Install Python package
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# Install Python package in editable mode
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To run examples or tests, install with optional dependencies:

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