From 7ebfdf6f43d48916a336c16ea43188f82841b5ae Mon Sep 17 00:00:00 2001
From: Mikhail <mnrozhkov@gmail.com>
Date: Thu, 29 May 2025 18:18:42 +0200
Subject: [PATCH] Add pr template

---
 .github/PULL_REQUEST_TEMPLATE.md | 118 +++++++++++++++++++++++++++++++
 1 file changed, 118 insertions(+)
 create mode 100644 .github/PULL_REQUEST_TEMPLATE.md

diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
new file mode 100644
index 0000000..e509260
--- /dev/null
+++ b/.github/PULL_REQUEST_TEMPLATE.md
@@ -0,0 +1,118 @@
+<!-- .github/PULL_REQUEST_TEMPLATE.md -->
+<!--
+Thank you for submitting your assignment!
+
+Please fill out this template carefully. It helps your peer reviewer and instructor understand your work and provide effective feedback.
+-->
+
+## Assignment: [COURSE_CODE] - Assignment [X]: [Assignment Title]
+
+<!--
+**Instructions for Student:**
+1. Replace `[COURSE_CODE]` with your course code (e.g., DS413BKK).
+2. Replace `[X]` with the assignment number (e.g., 1, 2, 3).
+3. Replace `[Assignment Title]` with the specific title of this assignment (e.g., "Data and Model Versioning with DVC").
+-->
+
+**Student Name:** [Your Full Name]
+
+**GitHub Username:** @[YourGitHubUsername]
+
+---
+
+### 📝 Summary of Changes
+
+<!--
+**Instructions for Student:**
+Briefly (2-3 sentences) describe the main tasks you completed and the key MLOps tools/concepts you applied in this assignment.
+Example: "Initialized DVC for the project, added the Iris dataset and the trained model (model.joblib) to DVC tracking. This allows for versioning of data and model artifacts alongside code."
+-->
+1. ...
+2. ...
+3. ...
+
+---
+
+### ✅ Deliverables Checklist
+
+<!--
+**Instructions for Student:**
+Review the assignment requirements and check off the items you have completed and are included in this Pull Request. Add or remove items if the assignment has specific deliverables not listed here.
+-->
+
+- [ ] **Branching:** Created a new branch for this assignment (e.g., `assignment-X`) and this PR targets my fork's `main` branch.
+- [ ] **Code Implementation:** All required scripts/code changes have been implemented as per the assignment instructions.
+- [ ] **Configuration Files:** `pyproject.toml`, `Makefile` or other configuration files updated if necessary.
+- [ ] **Reflection Questions:** All reflection questions for this assignment are answered in the section below.
+- [ ] **Screenshots:** Relevant screenshots (e.g., MLflow UI, API docs, Grafana dashboard) are included or linked below (if required by the assignment).
+- [ ] **Peer Review:** This PR has been peer-reviewed (if applicable for this assignment).
+
+---
+
+### 🤔 Reflection Questions & Answers
+
+<!--
+**Instructions for Student:**
+Copy the specific reflection questions for THIS assignment from the assignment instructions document.
+Answer each question thoroughly below it.
+-->
+
+Question 1: [Paste Assignment-Specific Question 1 Here]
+
+- [Your Answer Here]
+
+Question 2: [Paste Assignment-Specific Question 2 Here]
+
+- [Your Answer Here]
+
+<!-- Add more questions as needed for the specific assignment -->
+
+---
+
+### 📸 Screenshots / Outputs (if applicable)
+
+<!--
+**Instructions for Student:**
+If the assignment requires visual proof of completion (e.g., MLflow UI, API /docs page, terminal output), embed screenshots here or provide links.
+Make sure images are accessible. You can drag-and-drop images directly into the GitHub PR editor.
+
+Example:
+**MLflow Experiment Run:**
+![MLflow Run Details](link_to_your_screenshot.png)
+
+**API Endpoint Test (curl output):**
+```bash
+# Paste curl command and its output here
+```
+-->
+
+### ❓ Questions / Blockers / Points for Reviewer
+<!--
+**Instructions for Student:**
+Use this space to:
+- Ask any specific questions you have for your peer reviewer or the instructor.
+- Mention any parts of the assignment you found particularly challenging or where you're unsure about your approach.
+- Highlight any specific areas you'd like the reviewer to focus on.
+-->
+
+### 🙋 Self-Review Checklist (Before Submitting for Peer or Instructor Review)
+<!--
+**Instructions for Student:**
+Go through this checklist before requesting a review. This helps catch common issues and improves the quality of your submission.
+-->
+- [ ] Assignment Requirements: I have re-read the assignment requirements and believe my submission meets them.
+- [ ] Code Functionality: I have tested the core functionality of my changes locally.
+- [ ] Code Quality Tools:
+  - [ ] `make format` (or `uv run ruff format .`) run: Code is formatted.
+  - [ ] `make lint` (or `uv run ruff check .`) run: No linting errors reported (or unavoidable ones are justified).
+  - [ ] `make type-check` (or `uv run mypy .`) run: No Mypy errors reported (or unavoidable ones are justified).
+- [ ] Testing: `make test` (or `uv run pytest`) run: All tests pass.
+- [ ] Clarity: My code is reasonably commented, and variable/function names are clear.
+- [ ] PR Description: This PR description is fully filled out, including reflection answers.
+- [ ] Commit History: My commit messages are descriptive and atomic where possible.
+- [ ] No Sensitive Information: I have not committed any API keys, passwords, or other sensitive data.
+
+<!--
+Remember to @mention your peer reviewer in a comment on the PR if this is for peer review!
+Example: "Hi @peer-reviewer-username, this PR is ready for your review. Thanks!"
+-->