Repository: graphistry/pygraphistry

Issue:
[BUG] embed_utils.py breaks StreamHandler terminator for *all* log handlers
**Describe the bug**
The following code in `embed_utils.py` which gets loaded on `import graphistry` 

```python
logging.StreamHandler.terminator = ""
logger = logging.getLogger(__name__)
``` 

Note it is changing the logging StreamHandler class - not an instance.  This is changing every StreamHandler for every library, including every future StreamHandlers, to have a terminator of "" instead of the default "\n".  Took me three hours to track down which import of which import of which import was breaking my logging.

Not exactly sure what this code is intended to do in graphistry, but please don't override the standard python classes.

**To Reproduce**
```
Python 3.11.12 (main, Apr  8 2025, 14:15:29) [Clang 16.0.0 (clang-1600.0.26.6)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import logging
>>> logging.StreamHandler.terminator
'\n'
>>> h1 = logging.StreamHandler()
>>> h1.terminator
'\n'
>>> import graphistry
>>> logging.StreamHandler.terminator
''
>>> h2 = logging.StreamHandler()
>>> h2.terminator
''
>>> h1.terminator
''
```

**Expected behavior**
Namespace unrelated to graphistry should not be modified.

**Actual behavior**
See above. 




Discussion:
Thanks, wip fix @ https://github.com/graphistry/pygraphistry/pull/661 if needed for unblocking

I think it was in there b/c some tqdm support, and you are right that it should have been encapsulated



Patch:
diff --git a/.gitignore b/.gitignore
index 104d69b490..1c7cd046f7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -90,3 +90,7 @@ demos/data/BIOGRID-IDENTIFIERS-3.3.123.tab.txt
 # local jupyter dev
 jupyter_dev/
 docs/source/demos
+
+# AI assistant working directories
+AI_PROGRESS/
+PLAN.md
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9fc3b42daf..7739da8450 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -5,7 +5,28 @@ All notable changes to the PyGraphistry are documented in this file. The PyGraph
 The changelog format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html) and all PyGraphistry-specific breaking changes are explictly noted here.
 
-## [Development]
+## [0.37.0 - 2025-06-05]
+
+### Fixed
+
+* Fix embed_utils.py modifying global logging.StreamHandler.terminator ([#660](https://github.com/graphistry/pygraphistry/issues/660)) ([8480cd06](https://github.com/graphistry/pygraphistry/commit/8480cd06))
+
+### Breaking 🔥
+
+* `FeatureMixin.transform()` now raises `ValueError` for invalid `kind` parameter instead of silently continuing ([25e4bf51](https://github.com/graphistry/pygraphistry/commit/25e4bf51))
+* `FeatureMixin._transform()` now raises `ValueError` when encoder is not initialized instead of returning `None` ([25e4bf51](https://github.com/graphistry/pygraphistry/commit/25e4bf51))
+* `UMAPMixin.transform_umap()` now always returns `pd.DataFrame` (possibly empty) instead of `None` for `y_` in tuple return ([d2941ec4](https://github.com/graphistry/pygraphistry/commit/d2941ec4))
+
+### Chore
+
+* Switch to setup_logger utility in multiple modules ([842fb904](https://github.com/graphistry/pygraphistry/commit/842fb904))
+* Add AI_PROGRESS/ and PLAN.md to .gitignore ([f0c18b3b](https://github.com/graphistry/pygraphistry/commit/f0c18b3b), [ac25a356](https://github.com/graphistry/pygraphistry/commit/ac25a356))
+
+### Docs
+
+* Add AI assistant prompt templates and conventional commits guidance ([a52048a7](https://github.com/graphistry/pygraphistry/commit/a52048a7))
+* Simplify CLAUDE.md to point to ai_code_notes README ([e5393381](https://github.com/graphistry/pygraphistry/commit/e5393381))
+* Update AI assistant documentation with Docker-first testing ([db5496eb](https://github.com/graphistry/pygraphistry/commit/db5496eb))
 
 ## [0.36.2 - 2025-05-16]
 
diff --git a/CLAUDE.md b/CLAUDE.md
index 9a6f982236..26a2e16a0d 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -1,218 +1,1 @@
-# CLAUDE.md
-
-This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
-
-## Project Overview
-
-PyGraphistry is a Python library for graph visualization, analytics, and AI with GPU acceleration capabilities. It's designed to work with graph data by:
-
-1. Loading and transforming data from various sources into graph structures
-2. Providing visualization tools with GPU acceleration
-3. Offering graph analytics and AI capabilities including querying, ML, and clustering
-
-The library follows a client-server model where:
-- The Python client prepares data and handles transformations like loading, wrangling, querying, ML, and AI
-- Visualization happens through Graphistry servers (cloud or self-hosted)
-- Most user interaction follows a functional programming style with immutable state
-
-## Architecture
-
-PyGraphistry has a modular architecture consisting of:
-
-1. Core visualization engine that connects to Graphistry servers
-2. GFQL (Graph Frame Query Language) for dataframe-native graph queries
-3. Integration with many databases and graph systems (Neo4j, Neptune, TigerGraph, etc.)
-4. GPU acceleration through RAPIDS integration
-5. AI/ML capabilities including UMAP embeddings and graph neural networks
-
-Most components follow functional-style programming where methods create new copies of objects with updated bindings rather than modifying state.
-
-## Development Commands
-
-### Containers
-
-PyGraphistry uses Docker for development and testing. The `docker` directory contains Dockerfiles and scripts for building and running tests in isolated environments. The bin/*.sh are unaware of the Docker context, so you should run from the docker folder, which calls the appropriate scripts.
-
-### Environment Setup
-
-```bash
-# Install PyGraphistry with development dependencies
-pip install -e .[dev]
-
-# For GPU-accelerated features
-pip install -e .[rapids]
-
-# For AI capabilities
-pip install -e .[ai]
-
-# For full development setup
-pip install -e .[dev,test,ai]
-```
-
-### Testing Commands
-
-Testing is via containerized pytest, with shell scripts for convenient entry points:
-
-```bash
-# Run all tests
-./bin/test.sh
-
-# Run tests in parallel when many (xdist)
-./bin/test.sh -n auto
-
-# Run minimal tests (no external dependencies)
-./bin/test-minimal.sh
-
-# Run specific test file or test
-python -m pytest -vv graphistry/tests/test_file.py::TestClass::test_function
-
-# Run with Neo4j connectivity tests
-WITH_NEO4J=1 ./bin/test.sh
-
-# Docker-based testing (recommended for full testing)
-cd docker && ./test-cpu-local-minimal.sh
-cd docker && ./test-cpu-local.sh
-# For faster, targeted tests (WITH_BUILD=0 skips slow docs build)
-WITH_LINT=0 WITH_TYPECHECK=0 WITH_BUILD=0 ./test-cpu-local.sh graphistry/tests/test_file.py::TestClass::test_function
-# Ex: GFQL
-WITH_BUILD=0 ./test-cpu-local-minimal.sh graphistry/tests/test_compute_chain.py graphistry/tests/compute
-```
-
-### Linting and Type Checking
-
-Run before testing:
-
-```bash
-# Lint the code
-./bin/lint.sh
-
-# Type check with mypy
-./bin/typecheck.sh
-```
-
-### Building Documentation
-
-Sphinx-based:
-
-```bash
-# Build documentation locally
-cd docs && ./build.sh
-```
-
-### GPU Testing
-
-```bash
-# For GPU functionality (if available)
-cd docker && ./test-gpu-local.sh
-```
-
-## Common Development Workflows
-
-### Adding a New Feature
-
-1. Ensure you understand the functional programming style of PyGraphistry
-2. Create new features as standalone modules or methods where possible
-3. Implement it following the client-server model respecting immutable state
-4. Add appropriate tests in the `graphistry/tests/` directory
-5. Run linting and type checking before submitting changes
-
-### Testing Changes
-
-1. Use the appropriate test script for your feature:
-   - `test-minimal.sh` for core functionality
-   - `test-features.sh` for features functionality
-   - `test-umap-learn-core.sh` for UMAP functionality
-   - `test-dgl.sh` for graph neural network functionality
-   - `test-embed.sh` for embedding functionality
-   - Additional specialized tests exist for specific components
-
-2. For database connectors, ensure you have the relevant database running:
-   - `WITH_NEO4J=1 ./bin/test.sh` for Neo4j tests
-
-### Building and Publishing
-
-1. Update the changelog in CHANGELOG.md
-2. Tag with semantic versioning: `git tag X.Y.Z && git push --tags`
-3. Confirm GitHub Actions publishes to PyPI
-
-### Dependencies
-
-* Dependencies are managed in `setup.py`
-* The `stubs` list in setup.py contains type stubs for development
-* Avoid adding unnecessary dependencies
-* If you encounter type checking errors related to missing imports:
-  - First check if they're already defined in the `stubs` list in setup.py
-  - If not, consider adding them to the ignore list in mypy.ini using format:
-    ```
-    [mypy-package_name.*]
-    ignore_missing_imports = True
-    ```
-
-#### Dependency Structure
-
-```python
-# Core dependencies - always installed
-core_requires = [
-  'numpy', 'pandas', 'pyarrow', 'requests', ...
-]
-
-# Type stubs for development
-stubs = [
-  'pandas-stubs', 'types-requests', 'ipython', 'types-tqdm'
-]
-
-# Optional dependencies by category
-base_extras_light = {...}  # Light integrations (networkx, igraph, etc)
-base_extras_heavy = {...}  # Heavy integrations (GPU, AI, etc)
-dev_extras = {...}         # Development tools (docs, testing, etc)
-```
-
-#### Docker Testing Dependencies
-
-* Docker tests install dependencies via `-e .[test,build]` or `-e .[dev]`
-* The PIP_DEPS environment variable controls which dependencies are installed
-* If adding new stubs, add them to the `stubs` list in setup.py
-
-## Project Dependencies
-
-PyGraphistry has different dependency sets depending on functionality:
-
-- Core: numpy, pandas, pyarrow, requests
-- Optional integrations: networkx, igraph, neo4j, gremlin, etc.
-- GPU acceleration: RAPIDS ecosystem (cudf, cugraph)
-- AI extensions: umap-learn, dgl, torch, sentence-transformers
-
-## Coding tips
-
-* We're version controlled: Avoid unnecessary rewrites to preserve history
-* Occasionally try lint & type checks when editing
-* Post-process: remove Claude's explanatory comments
-
-## Performance Guidelines
-
-### Functional & Immutable
-* Follow functional programming style - return new objects rather than modifying existing ones
-* No explicit `copy()` calls on DataFrames - pandas/cudf operations already return new objects
-* Chain operations to minimize intermediate objects
-
-### DataFrame Efficiency
-* Never call `str()` repeatedly on the same value - compute once and reuse
-* Use `assign()` instead of direct column assignment: `df = df.assign(**{col: val})` not `df[col] = val`
-* Select only needed columns: `df[['col1', 'col2']]` not `df` when processing large DataFrames
-* Use `concat` and `drop_duplicates` with `subset` parameter when combining DataFrames
-* Process collections at once (vectorized) rather than element by element
-* Use `logger.debug('msg %s', var)` not f-strings in loggers to skip interpolation costs when log level disabled
-
-### GFQL & Engine
-* Respect engine abstractions - use `df_concat`, `resolve_engine` etc. to support both pandas/cudf
-* Collection-oriented algorithms: Process entire node/edge collections at once
-* Be mindful of column name conflicts in graph operations
-* Reuse computed temporary columns to avoid unnecessary conversions
-* Consider memory implications during graph traversals
-
-
-## Git tips
-
-* Commits: We use conventional commits for commit messages, where each commit is a semantic change that can be understood in isolation, typically in the form of `type(scope): subject`. For example, `fix(graph): fix a bug in graph loading`. Try to isolate commits to one change at a time, and use the `--amend` flag to modify the last commit if you need to make changes before pushing. Changes should be atomic and self-contained, don't do too many things in one commit.
-
-* CHANGELOG.md: We use a changelog to track changes in the project. We use semvars as git tags, so while deveoping, put in the top (reverse-chronological) section of the changelog `## [Development]`. Organize changes into subsections like `### Feat`,  `### Fixed`, `### Breaking 🔥`, etc.: reuse section names from the rest of the CHANGELOG.md. Be consistent in general.
\ No newline at end of file
+See [ai_code_notes/README.md](ai_code_notes/README.md) for AI assistant development guidance.
\ No newline at end of file
diff --git a/ai_code_notes/README.md b/ai_code_notes/README.md
new file mode 100644
index 0000000000..f327e85d52
--- /dev/null
+++ b/ai_code_notes/README.md
@@ -0,0 +1,242 @@
+# ai_code_notes
+
+Specialized documentation for AI assistants working on PyGraphistry. These guides supplement the main CLAUDE.md with detailed, topic-specific information.
+
+## 🎯 Quick Reference
+
+### Critical Development Rules
+- **Functional Programming**: Always return new objects, never modify in-place
+- **No `copy()` on DataFrames**: Operations already return new objects  
+- **Use `df.assign()`**: Never use `df[col] = val` syntax
+- **Preserve Git History**: Avoid unnecessary rewrites
+- **No Claude Comments**: Remove explanatory comments before committing
+
+### Essential Commands
+```bash
+# Before any work - establish baseline (containerized)
+cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Quick Docker test (from docker/ directory)
+WITH_BUILD=0 ./test-cpu-local-minimal.sh
+
+# Run specific tests fast
+WITH_LINT=0 WITH_TYPECHECK=0 WITH_BUILD=0 ./test-cpu-local.sh graphistry/tests/test_file.py
+
+# Note: Direct script execution requires local environment setup
+# ./bin/lint.sh && ./bin/typecheck.sh
+```
+
+### Performance Must-Haves
+- Never call `str()` repeatedly on same value
+- Use vectorized operations, not loops
+- Select only needed columns: `df[['col1', 'col2']]`
+- Use `logger.debug('msg %s', var)` not f-strings in loggers
+- Respect engine abstractions (`df_concat`, `resolve_engine`)
+
+## 📋 Documentation Hierarchy
+
+```
+CLAUDE.md                    # General guide (< 500 lines)
+├── ai_code_notes/          # Specialized guides
+│   ├── README.md           # This file - overview & quick ref
+│   ├── gfql/              # GFQL patterns & optimization
+│   ├── gpu/               # GPU/RAPIDS best practices  
+│   ├── connectors/        # Database-specific patterns
+│   └── prompt_templates/  # Reusable workflows
+└── AI_PROGRESS/           # Task tracking (gitignored)
+```
+
+### When to Use Each Level
+- **CLAUDE.md**: Start here for general PyGraphistry development
+- **ai_code_notes/**: Load specific guides only when working on that topic
+- **AI_PROGRESS/**: Track multi-session work and complex implementations
+
+## 🚀 Status Tracking Conventions
+
+### Priority System (P0-P5)
+- **P0 🚨**: Critical - Breaking functionality, must fix immediately
+- **P1 🔴**: High - Type safety, imports, security issues  
+- **P2 🟡**: Medium - Code style consistency, best practices
+- **P3 🟢**: Low - Minor improvements, nice-to-haves
+- **P4 ⚪**: Minimal - Cosmetic, already suppressed
+- **P5 ⬜**: Skip - Won't fix, intentional patterns
+
+### Progress Indicators
+- ✅ Complete
+- 🔄 In Progress  
+- 📝 Planned
+- ❌ Blocked
+- ⏭️ Skipped
+
+## 📁 Directory Structure
+
+```
+ai_code_notes/
+├── gfql/                    # GFQL-specific patterns and guidelines
+├── gpu/                     # GPU/CUDA development notes
+├── connectors/              # Database connector patterns
+└── prompt_templates/        # Reusable workflow templates
+    ├── LINT_TYPES_CHECK.md       # Code quality enforcement (with P0-P5)
+    ├── CONVENTIONAL_COMMITS.md   # Git commit workflow with PyGraphistry conventions
+    ├── IMPLEMENTATION_PLAN.md    # [TODO] Feature implementation tracking
+    └── USER_TESTING_PLAYBOOK.md  # [TODO] AI-driven testing workflows
+```
+
+## 📖 Usage Guidelines
+
+### Loading Documentation
+1. **Start with CLAUDE.md** for general PyGraphistry work
+2. **Load specific guides** only when working on that topic
+3. **Don't load everything** - each guide is self-contained
+4. **Check file size** - guides should be < 500 lines
+
+### File Size Guidelines
+- **Documentation**: Max 500 lines per file
+- **Code files**: Max 300 lines ideal, 500 lines acceptable
+- **Functions**: Max 50 lines per function
+- **Classes**: Split large classes into mixins
+
+## ✏️ Creating New Guides
+
+When adding a new guide:
+1. Place in appropriate subdirectory
+2. Use descriptive names (e.g., `neo4j_patterns.md`)
+3. Add header explaining when to use it
+4. Focus on patterns, not API details
+5. Include practical examples
+6. Add to directory structure above
+
+## 📚 Current Guides
+
+### GFQL (Graph Frame Query Language)
+- Query patterns and optimization
+- Column naming conventions  
+- Performance considerations
+- Engine abstraction patterns
+- **Load when**: Working on graph queries, chain/hop operations
+
+### GPU/RAPIDS
+- RAPIDS integration patterns
+- Memory management strategies
+- CPU/GPU fallback handling
+- cuDF vs pandas compatibility
+- **Load when**: Implementing GPU features, optimizing performance
+
+### Connectors
+- Database-specific patterns
+- Connection management
+- Error handling strategies
+- Testing with databases
+- **Load when**: Adding/fixing database integrations
+
+### Prompt Templates
+- **LINT_TYPES_CHECK.md**: Code quality enforcement with P0-P5 priorities
+- **CONVENTIONAL_COMMITS.md**: Git commit workflow following PyGraphistry conventions
+- **IMPLEMENTATION_PLAN.md** [TODO]: Systematic feature implementation
+- **USER_TESTING_PLAYBOOK.md** [TODO]: AI-driven testing workflows
+- **Load when**: Starting new tasks, creating commits, fixing code quality issues
+
+## 🧪 Testing Quick Reference
+
+### Docker Commands (Recommended)
+```bash
+cd docker
+
+# Fast iteration - skip slow parts
+WITH_BUILD=0 ./test-cpu-local-minimal.sh
+
+# Only lint and typecheck (no tests or build)
+WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Full validation before commit
+./test-cpu-local.sh
+
+# GPU functionality
+./test-gpu-local.sh
+
+# Specific features
+./test-umap-learn-core.sh  # UMAP embeddings
+./test-dgl.sh              # Graph neural networks  
+./test-embed.sh            # Embedding features
+```
+
+### Environment Control
+| Variable | Default | Purpose |
+|----------|---------|---------|
+| `WITH_LINT` | 1 | Run flake8 linting |
+| `WITH_TYPECHECK` | 1 | Run mypy type checking |
+| `WITH_BUILD` | 0 | Build documentation |
+| `WITH_NEO4J` | 0 | Run Neo4j integration tests |
+| `PYTHON_VERSION` | - | Override Python version |
+
+## 🔧 Common Patterns
+
+### DataFrame Operations
+```python
+# ✅ Good - Functional style
+df = df.assign(new_col=values)
+df = df[df['col'] > 0]  # Returns new DataFrame
+
+# ❌ Bad - In-place modification  
+df['new_col'] = values
+df.drop('col', inplace=True)
+```
+
+### Engine Abstraction
+```python
+# ✅ Good - Engine agnostic
+from graphistry.compute.typing import DataFrameLike
+engine = resolve_engine(df)
+result = engine.df_concat([df1, df2])
+
+# ❌ Bad - Engine specific
+if isinstance(df, pd.DataFrame):
+    result = pd.concat([df1, df2])
+```
+
+### Type Annotations
+```python
+# ✅ Good - Clear types with imports
+from typing import Optional, Union, TYPE_CHECKING
+if TYPE_CHECKING:
+    import cudf
+
+def process(df: Union[pd.DataFrame, 'cudf.DataFrame']) -> Optional[pd.DataFrame]:
+    return df if len(df) > 0 else None
+```
+
+## 🎯 Development Workflow
+
+### Before Starting
+1. Read CLAUDE.md for general context
+2. Run baseline: `./bin/lint.sh && ./bin/typecheck.sh`
+3. Load specific guide if needed
+
+### During Development  
+1. Follow functional programming patterns
+2. Add type annotations to new code
+3. Use appropriate priority (P0-P5) for issues
+4. Track complex work in AI_PROGRESS/
+
+### Before Committing
+1. Run Docker tests: `cd docker && WITH_BUILD=0 ./test-cpu-local.sh`
+2. Update CHANGELOG.md under `## [Development]`
+3. Use conventional commit: `fix(scope): description` (see `prompt_templates/CONVENTIONAL_COMMITS.md`)
+4. Remove debug code and Claude comments
+
+## 📝 AI_PROGRESS Tracking
+
+For multi-session or complex work:
+```
+AI_PROGRESS/task_name/
+├── implementation_plan.md  # Phases and approach
+├── progress.md            # Current status (update each session)
+├── insights.md            # Learnings and recommendations
+└── [task-specific files]  # Test results, benchmarks, etc.
+```
+
+### Example Task Names
+- `add_gfql_caching`
+- `fix_gpu_memory_leak`  
+- `implement_new_layout`
+- `optimize_umap_performance`
\ No newline at end of file
diff --git a/ai_code_notes/prompt_templates/CONVENTIONAL_COMMITS.md b/ai_code_notes/prompt_templates/CONVENTIONAL_COMMITS.md
new file mode 100644
index 0000000000..edaf831264
--- /dev/null
+++ b/ai_code_notes/prompt_templates/CONVENTIONAL_COMMITS.md
@@ -0,0 +1,495 @@
+# Conventional Commits Template for PyGraphistry
+
+<!-- FILE TRACKING HEADER - FILL IN WHEN FILE CREATED -->
+```
+File: AI_PROGRESS/commits_[YYYY_MM_DD_HHMMSS]/progress.md
+Run Name: commits_[YYYY_MM_DD_HHMMSS]
+Created: [YYYY-MM-DD HH:MM:SS]
+Status: [IN_PROGRESS/COMPLETE/BLOCKED]
+Total Commits: [number]
+```
+
+## Instructions for AI Assistant
+
+This template provides a systematic approach for creating well-organized conventional commits in PyGraphistry. When asked to create commits:
+
+1. **Analyze changes first** - Run Steps 1-2 to understand the full scope
+2. **Get user feedback** - Present analysis and proposed batching strategy
+3. **Create topical commits** - Group related changes by feature/scope
+4. **Use line-level precision** - Don't commit entire files if only parts changed
+5. **Follow conventional format** - type(scope): clear, concise subject
+6. **Update CHANGELOG after each commit** - Add entry once hash is available
+
+### File Structure
+- **Main tracking file**: `progress.md` - persists across all commit operations
+- **Optional scratchpads**: Create additional files only for complex analysis
+- **CHANGELOG section**: At end of progress.md, updated after each commit
+
+### Progress Update Format
+When returning with updates, ALWAYS start with:
+```
+Continuing run: commits_[YYYY_MM_DD_HHMMSS]
+Iteration: [number]
+Status: Creating commit [X] of [Y]
+```
+
+### Conventional Commit Format
+```
+type(scope): subject
+
+[optional body]
+
+[optional footer(s)]
+```
+
+**Types**:
+- `feat`: New feature
+- `fix`: Bug fix
+- `docs`: Documentation only
+- `style`: Formatting, missing semicolons, etc
+- `refactor`: Code restructuring without feature/fix
+- `perf`: Performance improvements
+- `test`/`tests`: Adding/updating tests
+- `chore`: Build process, auxiliary tools
+- `ci`: CI configuration files and scripts
+- `build`/`infra`: Build system or dependencies
+
+**PyGraphistry-Specific Scopes**:
+- `plottable`: Plotting functionality
+- `umap`: UMAP embeddings
+- `gfql`: Graph Frame Query Language
+- `gpu`/`gpu ci`: GPU-related functionality
+- `cugraph`/`cudf`: RAPIDS integration
+- `dbscan`: Clustering functionality
+- `featurize`: Feature engineering
+- `transform`: Data transformation
+- `dgl`: Deep Graph Library integration
+- `layout`: Layout algorithms (ring, tree, fa2, gib)
+- `compute`: Compute chain/hop operations
+- `api`: API changes
+- `hyper`: Hypergraph functionality
+
+## Execution Protocol
+
+### Step 1: Initial Status Analysis
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Commands**: 
+- `git status`
+- `git diff --stat`
+**Purpose**: Get overview of all changes
+**Action**: Identify modified, new, and deleted files
+
+<!-- FILL IN: Status analysis -->
+**Repository State**:
+- **Current branch**: [branch name]
+- **Files modified**: [count]
+- **Files added**: [count]
+- **Files deleted**: [count]
+- **Total changes**: [lines added/deleted]
+
+**Change Categories**:
+- [ ] Infrastructure/config files
+- [ ] Documentation updates
+- [ ] Source code changes
+- [ ] Test modifications
+- [ ] Dependencies/build files
+
+### Step 2: Detailed Change Analysis
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Analyze changes by logical grouping
+**Action**: Review diffs to understand change context
+
+<!-- FILL IN: For each significant file/area -->
+**Change Analysis**:
+
+#### Group 1: [Descriptive Name]
+**Files**: 
+- `path/to/file1.py` - [brief description of changes]
+- `path/to/file2.py` - [brief description of changes]
+
+**Change Summary**: [What feature/fix/improvement this represents]
+**Diff Preview**:
+```bash
+git diff --cached path/to/file1.py | head -20
+```
+**Key Changes**:
+- [ ] Added functionality: [describe]
+- [ ] Modified behavior: [describe]
+- [ ] Removed code: [describe]
+
+#### Group 2: [Descriptive Name]
+[Repeat structure for each logical group]
+
+### Step 3: Commit Strategy Proposal
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Present batching strategy for user approval
+**Action**: Propose logical commit groupings
+
+<!-- FILL IN: Proposed commit strategy -->
+**Proposed Commit Order**:
+
+1. **Infrastructure/Supporting Changes** (if any)
+   - Commit 1: `chore(build): [description]`
+     - Files: [list files]
+   - Commit 2: `chore(config): [description]`
+     - Files: [list files]
+
+2. **Core Feature Changes**
+   - Commit 3: `feat(scope): [description]`
+     - Files: [list files]
+   - Commit 4: `fix(scope): [description]`
+     - Files: [list files]
+
+3. **Documentation/Tests**
+   - Commit 5: `docs(scope): [description]`
+     - Files: [list files]
+   - Commit 6: `test(scope): [description]`
+     - Files: [list files]
+
+**User Decision Point**:
+```
+Please review the proposed commit strategy:
+- Approve as-is? (y)
+- Modify grouping? (m)
+- Different order? (o)
+- Skip some commits? (s)
+```
+
+### Step 4: Pre-commit Preparation
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Ensure clean working state
+**Action**: Verify no unintended changes
+
+<!-- FILL IN: Pre-commit checks -->
+**Pre-commit Checklist**:
+- [ ] Run linting: `./bin/lint.sh`
+- [ ] Run type checking: `./bin/typecheck.sh`
+- [ ] Verify tests pass: `python -m pytest -xvs` (if test changes)
+- [ ] Check for secrets: Review diffs for sensitive data
+- [ ] Unstage unrelated changes: `git reset HEAD <file>`
+- [ ] Remove Claude comments: No explanatory comments in code
+- [ ] Verify functional style: No `df[col] = val`, use `df.assign()`
+- [ ] Check for unnecessary `copy()`: DataFrames already return new objects
+
+### Step 5: Execute Commits
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Create commits according to approved strategy
+**Action**: Stage and commit changes in batches
+
+<!-- FILL IN: For each commit -->
+#### Commit [number]: [type(scope): subject]
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**CHANGELOG Entry** (to add after commit):
+```
+### [Section based on type]
+- scope: concise description (#hash_here)
+```
+
+**Staging Commands**:
+```bash
+# Check current staging status
+git status
+
+# Stage specific changes (from unstaged state)
+git add -p path/to/file1.py  # Interactive staging for partial changes
+git add path/to/file2.py      # Full file staging
+
+# Or if files are already staged and you need to unstage specific ones:
+git reset HEAD path/to/unwanted.py  # Unstage specific file
+```
+
+**Staged Files**:
+- [ ] `path/to/file1.py` - [portions staged]
+- [ ] `path/to/file2.py` - [full file]
+
+**Commit Message**:
+```
+[type]([scope]): [subject]
+
+[Detailed explanation of what changed and why]
+[Impact of the changes]
+[Any breaking changes or migration notes]
+
+[Footer if needed - e.g., Fixes #123]
+```
+
+**Execution**:
+```bash
+git commit -m "$(cat <<'EOF'
+[Insert actual commit message here]
+EOF
+)"
+```
+
+**Verification**:
+- [ ] Commit created successfully
+- [ ] `git show HEAD` displays expected changes
+- [ ] No unintended files included
+
+**Post-commit Actions**:
+1. Get commit hash: `git rev-parse --short HEAD`
+2. Add entry to appropriate CHANGELOG section (Features/Fixes/etc)
+3. Format: `- scope: description (hash)`
+
+### Step 6: Post-commit Review
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Verify all commits and final state
+**Action**: Review commit history and remaining changes
+
+<!-- FILL IN: Post-commit verification -->
+**Commit Summary**:
+```bash
+git log --oneline -[number of commits]
+```
+
+**Created Commits**:
+1. [hash] [type(scope): subject]
+2. [hash] [type(scope): subject]
+3. [hash] [type(scope): subject]
+
+**CHANGELOG Status**:
+- [ ] All commits added to CHANGELOG section
+- [ ] Commit hashes are short format (7 chars)
+- [ ] Links will work on GitHub after push
+
+**Remaining Changes**:
+- [ ] All planned changes committed
+- [ ] Unstaged changes: [list if any]
+- [ ] Untracked files: [list if any]
+
+### Step 7: Final Report
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Generate comprehensive summary
+**Action**: Document what was accomplished
+
+<!-- FILL IN: Final report -->
+```
+=== CONVENTIONAL COMMITS FINAL REPORT ===
+Started: [YYYY-MM-DD HH:MM:SS]
+Completed: [YYYY-MM-DD HH:MM:SS]
+Run Name: commits_[YYYY_MM_DD_HHMMSS]
+Total Commits Created: [number]
+Files Modified: [count]
+Lines Added: [count]
+Lines Deleted: [count]
+
+Commits by Type:
+- feat: [count]
+- fix: [count]
+- docs: [count]
+- chore: [count]
+- test: [count]
+- other: [count]
+
+Key Accomplishments:
+1. [Major feature/fix implemented]
+2. [Infrastructure improvement]
+3. [Documentation updated]
+
+Next Steps:
+- [ ] Push to remote: git push origin [branch]
+- [ ] Create PR if needed
+- [ ] Update issue tracker
+
+Result: ✅ COMPLETE / 🛑 BLOCKED
+```
+
+## Commit Message Best Practices
+
+### Subject Line Rules
+- **Limit to 50 characters** (hard limit 72)
+- **Use imperative mood**: "Add feature" not "Added feature"
+- **Don't end with period**
+- **Capitalize first letter**
+
+### Body Guidelines
+- **Wrap at 72 characters**
+- **Explain what and why**, not how
+- **Reference issues and PRs**
+- **Note breaking changes**
+
+### Good PyGraphistry Examples
+```
+feat(gfql): add multi-hop traversal support
+
+Implement efficient multi-hop graph traversals with column
+conflict resolution. Uses temporary column prefixing to avoid
+namespace collisions during chain operations.
+
+* Supports up to 10 hops with automatic memoization
+* Handles both pandas and cudf DataFrames
+* Preserves original column names in final output
+```
+
+```
+fix(umap): handle timeout in GPU embedding computation
+
+Previous implementation could hang on large graphs when GPU
+memory was insufficient. Now implements fallback to CPU with
+proper memory estimation and chunking.
+
+Fixes #660
+```
+
+```
+breaking fix(api): change from_cugraph return type
+
+BREAKING CHANGE: from_cugraph now returns PlotterBase instead
+of tuple when return_graph=True. This aligns with other
+from_* methods.
+
+Migration: Change `g, _ = from_cugraph(G)` to `g = from_cugraph(G)`
+```
+
+### Atomic Commits
+Each commit should:
+- **Focus on one logical change**
+- **Be revertable independently**
+- **Tell a clear story in history**
+- **Include related test updates**
+
+## Interactive Staging Tips
+
+### Using `git add -p`
+When files have multiple unrelated changes:
+
+```bash
+git add -p path/to/file.py
+```
+
+Options:
+- `y` - stage this hunk
+- `n` - skip this hunk
+- `s` - split into smaller hunks
+- `e` - manually edit hunk
+- `?` - help
+
+### Staging Strategies
+1. **New features first** - Infrastructure before implementation
+2. **Bug fixes separate** - Don't mix fixes with features
+3. **Refactoring alone** - Keep behavior changes separate
+4. **Tests with implementation** - Include in same commit
+5. **Docs can be separate** - Unless integral to feature
+
+## Common PyGraphistry Patterns
+
+### GFQL Feature Implementation
+```
+1. feat(gfql): add base predicate AST structure
+2. feat(gfql): implement numeric predicate operators
+3. feat(compute): integrate predicates into hop operations
+4. test(gfql): add predicate evaluation tests
+5. docs(gfql): update query language reference
+```
+
+### GPU/CPU Fallback Pattern
+```
+1. feat(umap): add GPU memory estimation
+2. feat(umap): implement CPU fallback mechanism
+3. perf(umap): optimize chunking for large graphs
+4. test(umap): add GPU OOM handling tests
+```
+
+### Breaking API Change
+```
+1. test(api): add tests for new return type behavior
+2. breaking fix(api): change from_cugraph return signature
+3. docs(api): update migration guide for v2.x
+4. chore(changelog): mark breaking change with 🔥
+```
+
+### Layout Algorithm Addition
+```
+1. feat(layout): add tree layout algorithm base
+2. feat(layout/tree): implement Sugiyama method
+3. feat(plottable): expose tree layout in plot API
+4. test(layout): add tree layout test cases
+5. docs(layout): add tree layout examples
+```
+
+## Troubleshooting
+
+### When Commits Get Messy
+- **Too many changes staged**: Use `git reset HEAD` and re-stage selectively
+- **Wrong commit message**: `git commit --amend` (before push only)
+- **Need to split commit**: `git reset HEAD~1` and recommit in parts
+- **Accidentally committed file**: `git rm --cached <file>` in new commit
+
+### Pre-commit Hooks
+If commits fail due to hooks:
+1. Fix the issues (formatting, linting)
+2. Re-stage fixed files
+3. Retry commit
+4. If hooks modified files, amend commit to include changes
+
+## Decision Points Summary
+
+1. **After Step 2**: Review analysis, decide on grouping strategy
+2. **After Step 3**: Approve/modify commit batching plan
+3. **During Step 5**: Decide on exact staging for each commit
+4. **After Step 6**: Verify satisfaction with commits created
+
+## File Cleanup
+
+**Cleanup Decision**:
+- [ ] **Keep progress.md** - Contains useful commit history
+- [ ] **Delete progress.md** - No longer needed
+- [ ] **Archive to project notes** - Move to documentation
+
+---
+
+**Remember**:
+- Always analyze before committing
+- Group related changes logically
+- Use precise staging for clean history
+- Follow conventional format strictly
+- Document the why, not just the what
+- **Update CHANGELOG after each commit**
+
+## CHANGELOG Updates
+
+<!-- 
+This section tracks changes to be added to CHANGELOG.md
+Update AFTER each commit when hash is available.
+PyGraphistry format: - description (#commit_hash)
+-->
+
+**Run**: commits_[YYYY_MM_DD_HHMMSS]  
+**Date**: [YYYY-MM-DD]
+
+### To add to CHANGELOG.md under `## [Development]`:
+
+#### Breaking 🔥
+<!-- Add breaking changes here as they're committed -->
+- Change from_cugraph return type to PlotterBase (#xxxxxxx)
+
+#### Feat
+<!-- Add new features here as they're committed -->
+- Add multi-hop graph traversal with memoization (#xxxxxxx)
+- Support GPU fallback for UMAP embeddings (#xxxxxxx)
+
+#### Fixed
+<!-- Add bug fixes here as they're committed -->
+- Handle GPU memory exhaustion in embeddings (#xxxxxxx)
+- Resolve column conflicts in chain operations (#xxxxxxx)
+
+#### Docs
+<!-- Add documentation updates here as they're committed -->
+- Update GFQL query examples (#xxxxxxx)
+- Add GPU memory management guide (#xxxxxxx)
+
+#### Infra
+<!-- Add infrastructure/build changes here as they're committed -->
+- Upgrade to cudf 23.x compatibility (#xxxxxxx)
+- Add type stubs for pandas 2.0 (#xxxxxxx)
+
+#### Tests
+<!-- Add test additions/updates here as they're committed -->
+- Add GPU fallback integration tests (#xxxxxxx)
+- Improve GFQL chain coverage (#xxxxxxx)
+
+### Session Summary
+- Total commits: [number]
+- Breaking changes: [list if any]
+- Related issues: [#660, #657]
+- Remember to update CHANGELOG.md in Development section!
\ No newline at end of file
diff --git a/ai_code_notes/prompt_templates/LINT_TYPES_CHECK.md b/ai_code_notes/prompt_templates/LINT_TYPES_CHECK.md
new file mode 100644
index 0000000000..df85de4a7a
--- /dev/null
+++ b/ai_code_notes/prompt_templates/LINT_TYPES_CHECK.md
@@ -0,0 +1,492 @@
+# Lint and Type Check Template for PyGraphistry
+
+<!-- FILE TRACKING HEADER - FILL IN WHEN FILE CREATED -->
+```
+Run Name: lint_check_[YYYY_MM_DD_HHMMSS]
+Main File: AI_PROGRESS/lint_check_[YYYY_MM_DD_HHMMSS]/progress.md
+Created: [YYYY-MM-DD HH:MM:SS]
+Status: [IN_PROGRESS/COMPLETE/BLOCKED]
+```
+
+## Instructions for AI Assistant
+
+This template guides systematic code quality checks using flake8 (linting) and mypy (type checking) for PyGraphistry.
+
+### Quick Start - Docker Commands
+```bash
+# Run lint and typecheck only (recommended approach)
+cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Skip lint check
+cd docker && WITH_LINT=0 WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Skip typecheck
+cd docker && WITH_TYPECHECK=0 WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+```
+
+1. **Start without creating files** - Run Steps 1-2 first
+2. **MANDATORY: FIX ALL FIXABLE ISSUES** - You MUST attempt to fix every error found
+3. **Create AI_PROGRESS file only if needed**:
+   - When manual fixes are required
+   - When Step 3 indicates iteration needed
+   - When complex issues found
+4. **Follow the iterative process** - Steps 1-3 repeat until clean
+5. **Always complete with Step 4** - Print report and handle cleanup
+6. **Ask about file deletion** in interactive mode (after showing report)
+
+### File Structure
+- **Main tracking file**: `AI_PROGRESS/lint_check_[YYYY_MM_DD_HHMMSS]/progress.md`
+  - This is the ONLY file that tracks overall progress across all iterations
+  - Always update this file when iterating back with progress updates
+  - Include the run name at the top of each update for easy tracking
+- **Additional files allowed**: Task-specific scratchpads for complex issues
+  - `issues_catalog.md` - Detailed issue breakdown if needed
+  - `implementation_plan.md` - For complex refactoring plans
+
+### ⚠️ CRITICAL: You MUST Fix Issues, Not Just Report Them ⚠️
+**NEVER** skip to "BLOCKED" status without attempting fixes. The process is:
+1. Find issues → 2. FIX THEM → 3. Verify → 4. Repeat until clean
+
+**BLOCKED means**: "I tried to fix these but cannot due to [specific technical reason]"
+**BLOCKED does NOT mean**: "I found many issues" or "Issues look complex"
+
+### Iterative Process Overview
+The lint/type check process is **iterative by design**:
+- **Steps 1-2**: Identify issues AND FIX THEM IMMEDIATELY
+- **Step 3**: Verify and decide to iterate or finish
+- **Repeat**: Continue until clean (0 flake8, 0 mypy)
+- **Step 4**: Generate final report and cleanup
+- **Exit**: When clean OR blocked AFTER ATTEMPTING FIXES
+
+**When returning with progress updates**:
+- Always start with: "Continuing run: lint_check_[YYYY_MM_DD_HHMMSS]"
+- Update the main progress.md file with current iteration status
+- Include iteration number and timestamp for each update
+
+### When to Create progress.md File
+- **NO FILE NEEDED**: Clean in first pass (no issues found)
+- **CREATE progress.md**: Any of these conditions:
+  - Multiple iterations needed (Step 3 → Iterate)
+  - Manual fixes required in Steps 1-2
+  - Complex issues found requiring documentation
+  - More than 5 total issues across all tools
+
+**Remember**: progress.md is the main tracking file that persists across all iterations
+
+## Execution Protocol
+
+### Step 1: Check Lint Issues with flake8
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Command (containerized)**: `cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh`
+**Command (direct)**: `./bin/lint.sh` (requires local environment)
+**Purpose**: Identify all linting issues
+**Action**: Run and categorize issues by type
+
+<!-- FILL IN: Lint check results -->
+**Quick syntax check (Critical errors only)**:
+```bash
+# First run - critical errors only
+./bin/lint.sh 2>&1 | grep -E "E9|F63|F7|F82" | head -20
+```
+
+**Full lint check results**:
+- **Total issues found**: [count]
+- **Critical errors** (E9, F63, F7, F82): [count]
+- **Import issues** (F401): [count]
+- **Other issues**: [count]
+
+**Issues by Priority**:
+- **P0 - Critical** (breaking functionality):
+  - [ ] Issue: [file:line] - [error code] - [description]
+  
+- **P1 - High** (type safety violations, imports):
+  - [ ] Issue: [file:line] - [error code] - [description]
+  
+- **P2 - Medium** (code style consistency):
+  - [ ] Issue: [file:line] - [error code] - [description]
+  
+- **P3 - Low** (minor improvements):
+  - [ ] Issue: [file:line] - [error code] - [description]
+  
+- **P4 - Nice to Have** (cosmetic, minimal impact, already suppressed):
+  - [ ] Issue: [file:line] - [error code] - [description]
+  
+- **P5 - Unimportant** (won't fix, intentional, or too minor to matter):
+  - [ ] Issue: [file:line] - [error code] - [description]
+
+**Quick fixes** (< 5 min each): [count]
+**Complex fixes** (require analysis): [count]
+**Can ignore** (P4/P5): [count]
+
+### Step 2: Type Check with MyPy
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Command (containerized)**: `cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh`
+**Command (direct)**: `./bin/typecheck.sh` (requires local environment)
+**Purpose**: Verify type safety across the codebase
+**Action**: Run and filter results
+
+<!-- FILL IN: Type check results -->
+**Type check results**:
+- **Total errors**: [count]
+- **Excluded files** (from mypy.ini): tests/, _version.py, graph_vector_pb2.py
+- **Ignored imports**: [count from ignore_missing_imports]
+
+**Issues by Priority**:
+- **P0 - Critical** (breaking functionality):
+  - [ ] Issue: [file:line] - [description]
+  
+- **P1 - High** (type safety violations):
+  - [ ] Issue: [file:line] - [description]
+  
+- **P2 - Medium** (missing annotations):
+  - [ ] Issue: [file:line] - [description]
+  
+- **P3 - Low** (optional improvements):
+  - [ ] Issue: [file:line] - [description]
+  
+- **P4 - Nice to Have** (third-party stubs, test files, minimal benefit):
+  - [ ] Issue: [file:line] - [description]
+  
+- **P5 - Unimportant** (dynamic typing required, legacy patterns, not worth fixing):
+  - [ ] Issue: [file:line] - [description]
+
+**Quick fixes** (obvious annotations): [count]
+**Complex fixes** (require refactoring): [count]
+**Can ignore** (P4/P5): [count]
+
+**⚠️ MANDATORY FIXING PHASE ⚠️**
+If ANY errors found above, you MUST:
+1. Start fixing immediately (begin with quick fixes)
+2. Use Edit/MultiEdit tools to fix the issues
+3. Document each fix in the iteration tracking
+4. Continue to Step 3 ONLY after attempting fixes
+
+### Step 3: Repeat-or-Finish
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Verify all fixes and determine if another iteration is needed
+**Action**: Re-run both tools to check for clean state
+
+<!-- FILL IN: Verification results -->
+**Verification Commands**:
+```bash
+# Containerized approach (recommended)
+cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Or run directly if you have local environment
+# ./bin/lint.sh
+# ./bin/typecheck.sh
+```
+
+**Results**:
+- **Flake8 issues remaining**: [count]
+- **MyPy issues remaining**: [count]
+
+**Decision**:
+- [ ] ✅ **CLEAN** - 0 flake8 issues AND 0 mypy issues (excluding P4/P5) → Go to Step 4
+- [ ] 🔄 **ITERATE** - P0-P3 issues remain → REPEAT Steps 1-3
+- [ ] 🛑 **BLOCKED** - Cannot fix remaining P0-P3 issues → Document blockers → Go to Step 4
+
+**Note**: P4/P5 issues don't require iteration - document them but consider the check "clean" if only these remain.
+
+**⚠️ BLOCKED CRITERIA ⚠️**
+You can ONLY choose BLOCKED if ALL of these are true:
+1. You have attempted to fix at least 5-10 issues
+2. You encountered a specific technical blocker (document it)
+3. The blocker prevents further progress
+
+Examples of valid blockers:
+- "Circular import that breaks when fixed"
+- "Third-party library missing type stubs configured in mypy.ini"
+- "Type system limitation requiring major refactor"
+- "Flake8 rule conflicts with project style guide"
+
+NOT valid reasons for BLOCKED:
+- "Too many errors" 
+- "Errors look complex"
+- "Would take too long"
+- "Not sure how to fix"
+
+### Step 4: Final Report and Cleanup
+**Started**: [YYYY-MM-DD HH:MM:SS]
+**Purpose**: Generate comprehensive report and handle file cleanup
+**Action**: Print final summary and manage AI_PROGRESS file
+
+<!-- FILL IN: Final report -->
+```
+=== LINT & TYPE CHECK FINAL REPORT ===
+Started: [YYYY-MM-DD HH:MM:SS]
+Completed: [YYYY-MM-DD HH:MM:SS]
+Total Iterations: [number]
+Starting Issues: [count]
+Issues Fixed: [count] ([percentage]%)
+Time Elapsed: [duration]
+
+Summary by Tool:
+- Flake8 issues fixed: [count]
+- MyPy issues fixed: [count]
+- Remaining issues: [count]
+
+Docker testing command:
+cd docker && WITH_BUILD=0 ./test-cpu-local.sh
+
+File Status:
+- progress.md created: Yes/No
+- Location: AI_PROGRESS/lint_check_[date]/progress.md
+
+Result: ✅ CLEAN / 🔧 IMPROVED / 🛑 BLOCKED
+```
+
+**Cleanup Decision**:
+- [ ] **Interactive Mode** - Ask user: "Delete progress.md file? (y/n)"
+- [ ] **Non-interactive Mode** - Keep file, note location in output
+- [ ] **No File Created** - Nothing to clean up
+
+## Issue Summary
+
+<!-- FILL IN: After running all tools -->
+**Iteration Tracking**:
+- **Current Iteration**: [number]
+- **Starting Issues**: [initial count]
+- **Current Status**: [count remaining]
+
+**Per-Iteration Progress**:
+| Iteration | Started | Flake8 Fixed | Flake8 Remaining | MyPy Fixed | MyPy Remaining | P4/P5 | Status |
+|-----------|---------|--------------|------------------|------------|----------------|-------|--------|
+| 1         | [time]  | [count]      | [count]          | [count]    | [count]        | [count]| 🔄     |
+| 2         | [time]  | [count]      | [count]          | [count]    | [count]        | [count]| ✅     |
+
+**Total Issues Fixed**:
+- Flake8 issues fixed: [count]
+- MyPy errors fixed: [count]
+- **P0-P3 remaining**: [count]
+- **P4/P5 ignored**: [count]
+
+## PyGraphistry-Specific Patterns
+
+### Common Flake8 Fixes
+```python
+# E501: Line too long (max 127)
+# Break long lines
+result = very_long_function_call(
+    parameter1, parameter2, 
+    parameter3, parameter4
+)
+
+# F401: Unused import
+# Remove the import or add to __all__
+
+# E722: Bare except
+# Replace: except:
+# With: except Exception:
+
+# W291/W293: Trailing whitespace
+# Remove whitespace at end of lines
+```
+
+### Common MyPy Fixes
+```python
+# Missing return type
+def process_data(df: pd.DataFrame) -> pd.DataFrame:
+    return df
+
+# Optional types
+from typing import Optional, Union
+def get_value(key: str) -> Optional[str]:
+    return None
+
+# DataFrame types
+from typing import TYPE_CHECKING
+if TYPE_CHECKING:
+    import cudf
+    
+def process(df: Union[pd.DataFrame, 'cudf.DataFrame']) -> Union[pd.DataFrame, 'cudf.DataFrame']:
+    return df
+
+# Functional style (PyGraphistry pattern)
+# Good: Return new objects
+df = df.assign(new_col=values)
+# Bad: Mutate in place
+df['new_col'] = values  # Avoid
+```
+
+### Configuration Reference
+
+**Flake8 Ignored Rules (from bin/lint.sh)**:
+- C901: Function complexity
+- E121-E128: Indentation rules
+- E201-E203: Whitespace around brackets
+- E501: Line length (but still check at 127 chars)
+- F401: Unused imports (but still fix obvious ones)
+- W291, W293: Trailing whitespace
+
+**MyPy Configuration (from mypy.ini)**:
+- Python version: 3.8
+- Excluded: tests/, _version.py, graph_vector_pb2.py
+- Many imports ignored due to missing stubs
+
+### P4/P5 Issue Examples (Following Product Management Priority Conventions)
+
+**P4 - Nice to Have (low impact)**:
+- Minor style inconsistencies that don't affect readability
+- Flake8 rules explicitly ignored in bin/lint.sh (E121-E128, etc.)
+- MyPy errors in excluded files (tests/, _version.py)
+- Import errors for packages with `ignore_missing_imports = True`
+- Optional type annotations that would add minimal safety benefit
+
+**P5 - Unimportant (not worth fixing)**:
+- Style violations in generated code (graph_vector_pb2.py)
+- Complex type annotations that would hurt readability
+- Dynamic attribute access required by the functional API
+- Legacy patterns that work but don't follow modern conventions
+- Third-party library limitations requiring # type: ignore
+- Cosmetic issues with no functional impact
+
+## Docker Commands Reference
+
+### Prerequisites
+The Docker test scripts require a pre-built test-cpu image. If not available:
+```bash
+cd docker
+# Build the test image first (one-time setup)
+COMPOSE_DOCKER_CLI_BUILD=1 DOCKER_BUILDKIT=1 \
+  docker compose build \
+  --build-arg PYTHON_VERSION=3.10 \
+  --build-arg PIP_DEPS="-e .[test,build]" \
+  test-cpu
+```
+
+### Running Lint/Type Checks (Containerized)
+```bash
+# RECOMMENDED: Run both lint and typecheck only
+cd docker && WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Full test suite including lint/typecheck/tests/build
+cd docker && ./test-cpu-local.sh
+
+# Fast iteration (skip build)
+WITH_BUILD=0 ./test-cpu-local.sh
+
+# Only run lint check
+WITH_TYPECHECK=0 WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Only run type check  
+WITH_LINT=0 WITH_BUILD=0 WITH_TEST=0 ./test-cpu-local.sh
+
+# Skip lint/typecheck for focused testing
+WITH_LINT=0 WITH_TYPECHECK=0 WITH_BUILD=0 ./test-cpu-local.sh
+
+# Specific test file
+WITH_BUILD=0 ./test-cpu-local.sh graphistry/tests/test_compute.py
+```
+
+### Direct Script Execution (requires local environment)
+If you have the dependencies installed locally:
+```bash
+# From project root
+./bin/lint.sh
+./bin/typecheck.sh
+
+# For specific files
+flake8 graphistry/embed_utils.py --max-line-length=127
+mypy graphistry/embed_utils.py
+```
+
+### Understanding Output
+- The docker scripts mount the code as read-only and run the bin scripts inside the container
+- Lint errors show file:line:column followed by error code and description
+- Type errors show file:line followed by error description
+- Exit code 0 means all checks passed
+
+## Decision Point
+
+<!-- FILL IN: Based on issue count and complexity -->
+**File Creation Decision**:
+- [ ] **No File Mode** - Clean or simple fixes in first pass
+- [ ] **Create File** - Multiple iterations or complex fixes needed
+
+**Execution Mode**: 
+- [ ] **Direct Fix** - Simple issues, fix immediately
+- [ ] **Tracked Fix** - Create AI_PROGRESS file to track iterations
+- [ ] **Task Mode** - Complex issues need full implementation plan
+
+## Task Mode Actions
+
+<!-- Use this section if progress.md needed -->
+### ⚠️ REMINDER: You MUST Actually Fix Issues Here ⚠️
+This section is for DOCUMENTING fixes you've already made, not planning future fixes.
+If you haven't fixed anything yet, GO BACK and start fixing!
+
+### Task Created:
+**Task Name**: `AI_PROGRESS/lint_check_[YYYY_MM_DD_HHMMSS]/`
+
+**Files Created**:
+- [ ] `progress.md` - Main tracking file (ALWAYS created, tracks all iterations)
+- [ ] `implementation_plan.md` - Systematic fix plan (optional, for complex issues)
+- [ ] `issues_catalog.md` - Detailed issue list (optional, for many issues)
+
+**Priority Order for Fixes**:
+1. **P0**: Fix immediately - breaking functionality
+2. **P1**: Fix next - type safety and imports
+3. **P2**: Fix if time - style consistency
+4. **P3**: Fix if easy - minor improvements
+5. **P4**: Skip - nice to have but not important
+6. **P5**: Skip - unimportant or not worth the effort
+
+### Progress Update Format (for progress.md):
+```
+=== ITERATION [number] UPDATE ===
+Run Name: lint_check_[YYYY_MM_DD_HHMMSS]
+Started: [YYYY-MM-DD HH:MM:SS]
+
+Fixes Applied:
+1. File: [path]
+   - Issue: [flake8/mypy code] - [description]
+   - Fix: [what was changed]
+   - Status: ✅ Fixed
+
+2. File: [path]
+   - Issue: [flake8/mypy code] - [description]
+   - Fix: [what was changed]
+   - Status: ❌ Failed - [reason]
+
+Verification:
+- Flake8: [count] remaining
+- MyPy: [count] remaining
+- Next: [ITERATE/COMPLETE/BLOCKED]
+```
+
+## Example Step 4 Output
+
+```
+=== LINT & TYPE CHECK FINAL REPORT ===
+Started: 2024-01-15 14:30:00
+Completed: 2024-01-15 14:35:15
+Total Iterations: 2
+Starting Issues: 23
+Issues Fixed: 23 (100%)
+Time Elapsed: 5 minutes 15 seconds
+
+Summary by Tool:
+- Flake8 issues fixed: 21
+- MyPy issues fixed: 2
+- Remaining issues: 0
+
+Docker testing command:
+cd docker && WITH_BUILD=0 ./test-cpu-local.sh
+
+File Status:
+- progress.md created: Yes
+- Location: AI_PROGRESS/lint_check_2024_01_15_143000/progress.md
+
+Result: ✅ CLEAN
+
+Would you like to delete the progress.md tracking file? (y/n): _
+```
+
+## ⚠️ FINAL REMINDER: The Goal is FIXING, Not Just Finding ⚠️
+
+When you run this template:
+1. **DO**: Find issues → Fix them → Verify → Repeat
+2. **DON'T**: Find issues → Report them → Give up
+
+Remember: Users want clean code, not detailed reports about dirty code!
\ No newline at end of file
diff --git a/graphistry/ai_utils.py b/graphistry/ai_utils.py
index 9b74d086ba..e14244e8cf 100644
--- a/graphistry/ai_utils.py
+++ b/graphistry/ai_utils.py
@@ -374,7 +374,7 @@ def infer_graph(
     logger.debug(" - Batch has", len(df), "nodes") if verbose else None
     logger.debug(" - Brought in", len(old_nodes), "nodes") if verbose else None
 
-    new_targets = pd.concat([y, Y.loc[old_nodes.index]]) if y is not None else Y
+    new_targets = pd.concat([y, Y.loc[old_nodes.index]]) if y is not None and not y.empty else Y
 
     return hydrate_graph(res, new_nodes, new_edges, node, src, dst, new_emb, new_features, new_targets)
 
diff --git a/graphistry/compute/cluster.py b/graphistry/compute/cluster.py
index 8d2c65d8c9..de49223ed1 100644
--- a/graphistry/compute/cluster.py
+++ b/graphistry/compute/cluster.py
@@ -18,8 +18,9 @@
 from graphistry.models.ModelDict import ModelDict
 from graphistry.feature_utils import get_matrix_by_column_parts
 from graphistry.utils.lazy_import import lazy_dbscan_import
+from graphistry.util import setup_logger
 
-logger = logging.getLogger("compute.cluster")
+logger = setup_logger("compute.cluster")
 
 if TYPE_CHECKING:
     MIXIN_BASE = Plottable
diff --git a/graphistry/compute/collapse.py b/graphistry/compute/collapse.py
index 622ca99a49..c41a88c631 100644
--- a/graphistry/compute/collapse.py
+++ b/graphistry/compute/collapse.py
@@ -3,22 +3,9 @@
 
 from graphistry.PlotterBase import Plottable
 
-logger = logging.getLogger("collapse")
-#logger.setLevel(logging.DEBUG)
-
-# create console handler and set level to debug
-# best for development or debugging
-consoleHandler = logging.StreamHandler()
-#consoleHandler.setLevel(logging.DEBUG)
-
-# create formatter
-formatter = logging.Formatter(': %(message)s')
-
-# add formatter to ch
-consoleHandler.setFormatter(formatter)
-
-# add ch to logger
-logger.addHandler(consoleHandler)
+logger = logging.getLogger(__name__)
+# Handler configuration removed - let users control their own logging setup
+# Use graphistry.util.setup_logger() if needed for consistent configuration
 
 COLLAPSE_NODE = "node_collapse"
 COLLAPSE_SRC = "src_collapse"
diff --git a/graphistry/compute/conditional.py b/graphistry/compute/conditional.py
index b74d0f9d48..413e8d8724 100644
--- a/graphistry/compute/conditional.py
+++ b/graphistry/compute/conditional.py
@@ -5,8 +5,9 @@
 
 from graphistry.Engine import Engine
 from graphistry.Plottable import Plottable
+from graphistry.util import setup_logger
 
-logger = logging.getLogger("compute.conditional")
+logger = setup_logger("compute.conditional")
 
 if TYPE_CHECKING:
     MIXIN_BASE = Plottable
diff --git a/graphistry/embed_utils.py b/graphistry/embed_utils.py
index 7f68faa2c9..73e70c371e 100644
--- a/graphistry/embed_utils.py
+++ b/graphistry/embed_utils.py
@@ -30,8 +30,27 @@ def check_cudf():
 XSymbolic = Optional[Union[List[str], str, pd.DataFrame]]
 ProtoSymbolic = Optional[Union[str, Callable[[TT, TT, TT], TT]]]  # type: ignore
 
-logging.StreamHandler.terminator = ""
+
+# Custom handler that doesn't add newlines (for tqdm compatibility)
+# This fixes issue #660 where we were globally modifying logging.StreamHandler.terminator
+# Now we only affect our own logger without breaking other libraries' logging
+class _NoTerminatorHandler(logging.StreamHandler):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.terminator = ""
+
+
+# Set up logger with custom handler that won't affect global logging
 logger = logging.getLogger(__name__)
+# Clear handlers to ensure we only have our custom no-terminator handler
+logger.handlers.clear()
+_handler = _NoTerminatorHandler()
+_handler.setFormatter(logging.Formatter('%(message)s'))
+_handler.setLevel(logging.WARNING)  # Set level on handler
+logger.addHandler(_handler)
+logger.setLevel(logging.WARNING)
+# Propagate=False ensures our special formatting isn't overridden by parent loggers
+logger.propagate = False
 
 
 def log(msg:str) -> None:
diff --git a/graphistry/feature_utils.py b/graphistry/feature_utils.py
index 66fad7a95f..9bfe191d64 100644
--- a/graphistry/feature_utils.py
+++ b/graphistry/feature_utils.py
@@ -239,10 +239,14 @@ def features_without_target(
         return df
     remove_cols = []
     if isinstance(y, pd.DataFrame):
+        if y.empty:
+            return df
         remove_cols = list(df.columns.intersection(y.columns))
     elif is_cudf_df(y):
         import cudf
         assert isinstance(y, cudf.DataFrame)
+        if y.empty:
+            return df
         remove_cols = list(df.columns.intersection(y.columns))
     elif isinstance(y, pd.Series):
         if y.name and (y.name in df.columns):
@@ -887,7 +891,7 @@ def get_numeric_transformers(ndf, y=None):
     label_encoder = False
     data_encoder = False
     y_ = y
-    if y is not None:
+    if y is not None and not y.empty:
         y_ = y.select_dtypes(include=[np.number])
         label_encoder = FunctionTransformer(
             partial(passthrough_df_cols, columns=y_.columns)
@@ -1017,7 +1021,7 @@ def process_dirty_dataframes(
         X_enc, _, data_encoder, _ = get_numeric_transformers(ndf, None)
 
 
-    if multilabel and y is not None:
+    if multilabel and y is not None and not y.empty:
         y_enc, label_encoder = encode_multi_target(y, mlb=None)
     elif (
         y is not None
@@ -2340,6 +2344,7 @@ def _transform(self, encoder: str, df: pd.DataFrame, ydf: Optional[pd.DataFrame]
                 "Fit on data (g.featurize(kind='..', ...))"
                 "before being able to transform data"
             )
+            raise ValueError(f"Encoder {encoder} not initialized. Call featurize() first.")
 
     def transform(self, df: pd.DataFrame, 
                   y: Optional[pd.DataFrame] = None, 
@@ -2350,7 +2355,7 @@ def transform(self, df: pd.DataFrame,
                   sample: Optional[int] = None, 
                   return_graph: bool = True,
                   scaled: bool = True,
-                  verbose: bool = False):
+                  verbose: bool = False) -> Union[Tuple[pd.DataFrame, pd.DataFrame], 'Plottable']:
         """Transform new data and append to existing graph, or return dataframes
         
             **args:**
@@ -2375,7 +2380,7 @@ def transform(self, df: pd.DataFrame,
         # This is temporary until cucat release 
         if 'cudf' in str(getmodule(df)):
             df = df.to_pandas()  # type: ignore
-        if (y is not None) and ('cudf' in str(getmodule(y))):
+        if (y is not None) and not y.empty and ('cudf' in str(getmodule(y))):
             y = y.to_pandas()  # type: ignore
 
         if kind == "nodes":
@@ -2383,8 +2388,7 @@ def transform(self, df: pd.DataFrame,
         elif kind == "edges":
             X, y_ = self._transform("_edge_encoder", df, y, scaled=scaled)
         else:
-            logger.debug("kind must be one of `nodes`,"
-                         f"`edges`, found {kind}")
+            raise ValueError(f"kind must be one of 'nodes' or 'edges', found {kind}")
             
         if return_graph and kind not in ["edges"]:
             emb = None  # will not be able to infer graph from umap coordinates, 
@@ -2456,7 +2460,9 @@ def scale(
         if df is None:  # use the original data
             X, y = (self._node_features_raw, self._node_target_raw) if kind == "nodes" else (self._edge_features_raw, self._edge_target_raw)  # type: ignore
         else:
-            X, y = self.transform(df, y, kind=kind, return_graph=False, scaled=False)
+            result = self.transform(df, y, kind=kind, return_graph=False, scaled=False)
+            assert isinstance(result, tuple), "transform with return_graph=False should return tuple"
+            X, y = result
 
         if kind == "nodes" and hasattr(self, "_node_encoder"):  # type: ignore
             if self._node_encoder is not None:  # type: ignore
diff --git a/graphistry/models/ModelDict.py b/graphistry/models/ModelDict.py
index 74128c3d76..a82194dfd1 100644
--- a/graphistry/models/ModelDict.py
+++ b/graphistry/models/ModelDict.py
@@ -2,7 +2,6 @@
 from collections import UserDict
 import logging
 
-
 logger = logging.getLogger(__name__)
 
 
diff --git a/graphistry/networks.py b/graphistry/networks.py
index b5fb04b438..ce7193a2fa 100644
--- a/graphistry/networks.py
+++ b/graphistry/networks.py
@@ -2,10 +2,9 @@
 from graphistry.utils.lazy_import import lazy_networks_import
 
 from . import constants as config
+from .util import setup_logger
 
-import logging
-
-logger = logging.getLogger(__name__)
+logger = setup_logger(__name__)
 
 
 if TYPE_CHECKING:  # noqa
diff --git a/graphistry/outliers.py b/graphistry/outliers.py
index 283cd7848d..e19424e577 100644
--- a/graphistry/outliers.py
+++ b/graphistry/outliers.py
@@ -3,6 +3,8 @@
 import pandas as pd
 import logging
 
+from .util import setup_logger
+
 try: 
     import matplotlib.font_manager
     import matplotlib.pyplot as plt
@@ -18,7 +20,7 @@
     OneClassSVM = None  # type: ignore
 
 
-logger = logging.getLogger(__name__)
+logger = setup_logger(__name__)
 
 
 # #####################################################################################################################
diff --git a/graphistry/plugins/graphviz.py b/graphistry/plugins/graphviz.py
index 251f6d4757..5ada9772d4 100644
--- a/graphistry/plugins/graphviz.py
+++ b/graphistry/plugins/graphviz.py
@@ -8,9 +8,10 @@
     EDGE_ATTRS, FORMATS, GRAPH_ATTRS, NODE_ATTRS, PROGS, UNSANITARY_ATTRS,
     EdgeAttr, Format, GraphAttr, NodeAttr, Prog
 )
+from graphistry.util import setup_logger
 
 
-logger = logging.getLogger(__name__)
+logger = setup_logger(__name__)
 
 
 ############################################
diff --git a/graphistry/text_utils.py b/graphistry/text_utils.py
index 0a786fe011..5915a53014 100644
--- a/graphistry/text_utils.py
+++ b/graphistry/text_utils.py
@@ -49,7 +49,9 @@ def build_index(self, angular=False, n_trees=None):
 
     def _query_from_dataframe(self, qdf: pd.DataFrame, top_n: int, thresh: float):
         # Use the loaded featurizers to transform the dataframe
-        vect, _ = self.transform(qdf, None, kind="nodes", return_graph=False)
+        result = self.transform(qdf, None, kind="nodes", return_graph=False)
+        assert isinstance(result, tuple), "transform with return_graph=False should return tuple"
+        vect, _ = result
 
         nodes = self._nodes
         if 'cudf' in str(getmodule(nodes)):
diff --git a/graphistry/umap_utils.py b/graphistry/umap_utils.py
index 6c14de5e32..5420b5d421 100644
--- a/graphistry/umap_utils.py
+++ b/graphistry/umap_utils.py
@@ -130,7 +130,7 @@ def safe_cudf(X, y):
                 new_kwargs[key] = df_to_engine(value, Engine.CUDF)
         return new_kwargs['X'], new_kwargs['y']
 
-    if 'cudf' in str(getmodule(X)) or (y is not None and 'cudf' in str(getmodule(y))) or engine == "cuml":
+    if 'cudf' in str(getmodule(X)) or (y is not None and not y.empty and 'cudf' in str(getmodule(y))) or engine == "cuml":
         return safe_cudf(X, y)
     
     return X, y
@@ -373,7 +373,7 @@ def _umap_fit_transform(
         if self._umap is None:
             raise ValueError("UMAP is not initialized")
         self.umap_fit(X, y, umap_fit_kwargs)
-        logger.debug('_umap_fit_transform:\nX::%s\n%s\nkwargs:\n%s\ny:\n%s', type(X), X.dtypes, umap_transform_kwargs, y.dtypes if y is not None else None)
+        logger.debug('_umap_fit_transform:\nX::%s\n%s\nkwargs:\n%s\ny:\n%s', type(X), X.dtypes, umap_transform_kwargs, y.dtypes if y is not None and not y.empty else None)
         emb = self._umap.transform(X, **umap_transform_kwargs)
 
         engine = umap_model_to_engine(self._umap)
@@ -418,18 +418,33 @@ def transform_umap(self, df: pd.DataFrame,
         assert engine is not None, f'Expected self._umap_engine to be resolved, got {engine}'
 
         df, y = make_safe_umap_gpu_dataframes(df, y, engine)
-        X, y_ = self.transform(df, y, kind=kind, return_graph=False)
+        result = self.transform(df, y, kind=kind, return_graph=False)
+        # When return_graph=False, transform returns a tuple (X, y_)
+        if not isinstance(result, tuple):
+            raise ValueError(f"Expected transform with return_graph=False to return tuple, got {type(result)}")
+        X, y_ = result
+        # transform should always return a tuple, even if y_ is empty/None
+        assert isinstance(X, pd.DataFrame), f"Expected X to be DataFrame, got {type(X)}"
+        if y_ is None:
+            # Create empty DataFrame to maintain consistent return type
+            y_ = pd.DataFrame(index=X.index)
         X, y_ = make_safe_umap_gpu_dataframes(X, y_, engine)  # type: ignore
         assert self._umap is not None, 'Expected self._umap to be initialized'
         emb = self._umap.transform(X, **umap_transform_kwargs)  # type: ignore
         emb = self._bundle_embedding(emb, index=df.index)
         if return_graph and kind == 'nodes':
             emb, _ = make_safe_umap_gpu_dataframes(emb, None, engine)  # for now so we don't have to touch infer_edges, force to pandas
-            X, y_ = make_safe_umap_gpu_dataframes(X, y_, engine)
-            g = self._infer_edges(emb, X, y_, df, 
+            X_safe, y_safe = make_safe_umap_gpu_dataframes(X, y_, engine)
+            # Ensure y_safe is never None when passed to _infer_edges
+            if y_safe is None:
+                y_safe = pd.DataFrame(index=X_safe.index)
+            g = self._infer_edges(emb, X_safe, y_safe, df, 
                                   infer_on_umap_embedding=fit_umap_embedding, merge_policy=merge_policy,
                                   eps=min_dist, sample=sample, n_neighbors=n_neighbors) 
             return g
+        # Ensure y_ is never None when returning the tuple
+        if y_ is None:
+            y_ = pd.DataFrame(index=X.index)
         return emb, X, y_
 
     def _bundle_embedding(self, emb, index):


Test patch:
diff --git a/graphistry/tests/test_logging.py b/graphistry/tests/test_logging.py
new file mode 100644
index 0000000000..873d1055e4
--- /dev/null
+++ b/graphistry/tests/test_logging.py
@@ -0,0 +1,46 @@
+"""Tests for logging behavior across the graphistry package"""
+import unittest
+import logging
+import sys
+from io import StringIO
+
+
+class TestLogging(unittest.TestCase):
+    """Test that graphistry's logging doesn't interfere with user logging configurations"""
+    
+    def test_external_logger_configuration_preserved(self):
+        """Regression test for issue #660: graphistry should not modify external loggers"""
+        # Set up a logger with custom configuration before importing graphistry
+        external_logger = logging.getLogger("user_application")
+        handler = logging.StreamHandler()
+        original_terminator = handler.terminator
+        formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+        handler.setFormatter(formatter)
+        external_logger.addHandler(handler)
+        
+        # Import graphistry (which loads various modules with custom logging)
+        import graphistry
+        
+        # Verify the external logger configuration is unchanged
+        self.assertEqual(handler.terminator, original_terminator,
+                        "graphistry import modified external handler terminator")
+        self.assertEqual(logging.StreamHandler.terminator, '\n',
+                        "graphistry import modified global StreamHandler default")
+        
+        # Verify external logger still works as expected
+        capture = StringIO()
+        test_handler = logging.StreamHandler(capture)
+        test_logger = logging.getLogger("test_logger")
+        test_logger.addHandler(test_handler)
+        test_logger.setLevel(logging.INFO)
+        
+        test_logger.info("Line 1")
+        test_logger.info("Line 2")
+        
+        output = capture.getvalue()
+        self.assertEqual(output, "Line 1\nLine 2\n",
+                        "Logger output should have newlines between messages")
+
+
+if __name__ == "__main__":
+    unittest.main()