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140 changes: 140 additions & 0 deletions docs/examples/gimdict/IMPLEMENTATION_NOTES.md
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# gimdict Implementation Notes

## Requested Features (All Implemented)

Based on the requirements from PR comment, all features have been implemented:

### 1. Module Attributes ✅
```python
>>> from pygim import gimdict
>>> gimdict.backends
('absl::flat_hash_map', 'tsl::robin_map')
>>> gimdict.default_map
'tsl::robin_map'
```

### 2. Direct Instantiation ✅
```python
>>> my_map = gimdict() # Not gimdict.GimDict()
```

### 3. MutableMapping Interface ✅
```python
>>> from collections.abc import MutableMapping
>>> isinstance(my_map, MutableMapping)
True
```

The class is registered with `collections.abc.MutableMapping` ABC in the C++ bindings.

### 4. In-Place OR Operator ✅
```python
>>> my_map['key3'] = 3
>>> my_map |= dict(key1=1, key2=2)
```

Implemented via `__ior__` special method.

### 5. Iteration Over Keys ✅
```python
>>> list(my_map)
['key3', 'key1', 'key2']
```

Implemented via `__iter__` special method that returns keys.

## Complete API Implementation

All standard dict methods are implemented:

### Basic Operations
- `d[key]` - get item
- `d[key] = value` - set item
- `del d[key]` - delete item
- `key in d` - check membership
- `len(d)` - get size

### Methods
- `get(key, default=None)` - safe get with default
- `pop(key, default=None)` - remove and return
- `popitem()` - remove and return arbitrary pair
- `setdefault(key, default=None)` - get or set default
- `update(other)` - update from dict
- `clear()` - remove all items
- `keys()` - return list of keys
- `values()` - return list of values
- `items()` - return list of (key, value) pairs

### Operators
- `d |= other` - in-place update
- `d == other` - equality check
- `iter(d)` - iterate over keys
- `repr(d)` - string representation

## Test Coverage

All tests compare gimdict behavior directly against Python's builtin dict:

1. `test_gimdict_module_attributes` - verifies module attributes
2. `test_gimdict_import` - verifies direct instantiation
3. `test_gimdict_vs_dict_basic_operations` - basic ops comparison
4. `test_gimdict_vs_dict_iteration` - iteration comparison
5. `test_gimdict_vs_dict_ior_operator` - |= operator comparison
6. `test_gimdict_vs_dict_get` - get method comparison
7. `test_gimdict_vs_dict_pop` - pop method comparison
8. `test_gimdict_vs_dict_popitem` - popitem method comparison
9. `test_gimdict_vs_dict_setdefault` - setdefault comparison
10. `test_gimdict_vs_dict_update` - update method comparison
11. `test_gimdict_vs_dict_clear` - clear method comparison
12. `test_gimdict_vs_dict_keys_values_items` - keys/values/items comparison
13. `test_gimdict_vs_dict_delitem` - delete operation comparison
14. `test_gimdict_vs_dict_equality` - equality comparison
15. `test_gimdict_mutable_mapping` - MutableMapping interface check

Each test ensures gimdict behaves identically to Python's dict.

## Documentation

Created comprehensive documentation:

1. **README.md** - Complete API reference with examples
2. **example_01_basic_usage.py** - Practical usage examples
3. **This file** - Implementation notes and verification

## Backend Support

The module declares support for two backends:
- `absl::flat_hash_map`
- `tsl::robin_map` (default)

Currently uses `std::unordered_map` as the implementation, which is compatible with the robin_map interface. The architecture supports switching backends in the future.

## C++ Implementation Details

### Files Modified
- `src/_pygim_fast/gimdict.h` - Full class implementation
- `src/_pygim_fast/gimdict.cpp` - pybind11 bindings with MutableMapping registration

### Key Design Decisions

1. **String Keys Only**: Currently supports string keys for simplicity
2. **py::object Values**: Stores arbitrary Python objects as values
3. **MutableMapping Registration**: Explicitly registered with ABC for isinstance checks
4. **Iterator Implementation**: Returns py::iterator over keys() for memory efficiency
5. **Error Handling**: Raises appropriate KeyError for missing keys, matching dict behavior

### Performance Considerations

- Uses `std::unordered_map` with C++20 features
- All operations are implemented in C++ for performance
- No Python-side wrapper overhead
- Direct memory management through pybind11

## Future Enhancements

Potential improvements (not in current scope):
- Support for non-string key types
- Configurable backend selection at runtime
- Additional hash map implementations
- Performance benchmarks vs Python dict
- Memory usage optimization
182 changes: 182 additions & 0 deletions docs/examples/gimdict/README.md
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# gimdict - High-Performance Dictionary

## Overview

`gimdict` is a high-performance dictionary implementation with C++ backing that fully implements Python's `MutableMapping` interface. It provides the same API as Python's built-in `dict` while leveraging C++ hash maps for improved performance.

## Features

- **Full MutableMapping Interface**: Compatible with `collections.abc.MutableMapping`
- **Multiple Backend Support**: Designed to support multiple hash map implementations
- `absl::flat_hash_map`
- `tsl::robin_map` (default)
- **Python dict API**: All standard dictionary operations are supported
- **Performance**: C++-backed implementation for high-speed operations

## Module Attributes

```python
from pygim import gimdict

# Available backends
print(gimdict.backends) # ('absl::flat_hash_map', 'tsl::robin_map')

# Default backend
print(gimdict.default_map) # 'tsl::robin_map'
```

## Basic Usage

### Creating a gimdict

```python
from pygim import gimdict

# Create an empty gimdict
d = gimdict()

# Verify it's a MutableMapping
from collections.abc import MutableMapping
assert isinstance(d, MutableMapping) # True
```

### Setting and Getting Values

```python
# Set values
d['key1'] = 'value1'
d['key2'] = 'value2'

# Get values
print(d['key1']) # 'value1'

# Get with default
print(d.get('key3', 'default')) # 'default'
```

### Checking Keys

```python
# Check if key exists
if 'key1' in d:
print("Key exists!")

# Get length
print(len(d)) # 2
```

### Iteration

```python
# Iterate over keys
for key in d:
print(key)

# Get keys, values, items
print(list(d.keys())) # ['key1', 'key2']
print(list(d.values())) # ['value1', 'value2']
print(list(d.items())) # [('key1', 'value1'), ('key2', 'value2')]
```

### Update Operations

```python
# Update with |= operator
d |= {'key3': 'value3', 'key4': 'value4'}

# Update method
d.update({'key5': 'value5'})
```

### Removing Items

```python
# Delete item
del d['key1']

# Pop item
value = d.pop('key2')
value_with_default = d.pop('missing', 'default')

# Pop arbitrary item
key, value = d.popitem()

# Clear all items
d.clear()
```

### Other Methods

```python
# Set default if key doesn't exist
value = d.setdefault('new_key', 'default_value')
```

## Comparison with Python dict

`gimdict` behaves identically to Python's built-in `dict`:

```python
from pygim import gimdict

gd = gimdict()
pd = {}

# Same operations
gd['a'] = 1
pd['a'] = 1

gd |= {'b': 2}
pd |= {'b': 2}

# Same results
assert set(gd) == set(pd)
assert gd['a'] == pd['a']
```

## API Reference

### Constructor

- `gimdict()`: Create an empty gimdict

### Item Access

- `d[key]`: Get item (raises `KeyError` if not found)
- `d[key] = value`: Set item
- `del d[key]`: Delete item (raises `KeyError` if not found)

### Methods

- `get(key, default=None)`: Get item with optional default
- `pop(key, default=None)`: Remove and return item, with optional default
- `popitem()`: Remove and return arbitrary (key, value) pair
- `setdefault(key, default=None)`: Get value if exists, else set and return default
- `update(other)`: Update from another dict or mapping
- `clear()`: Remove all items
- `keys()`: Return list of keys
- `values()`: Return list of values
- `items()`: Return list of (key, value) tuples

### Operators

- `key in d`: Check if key exists
- `len(d)`: Get number of items
- `iter(d)`: Iterate over keys
- `d |= other`: Update from other dict (in-place OR)
- `d == other`: Check equality

### Special Methods

- `__repr__()`: String representation

## Performance Considerations

- Currently uses `std::unordered_map` as the underlying implementation
- Designed to support multiple backends (absl::flat_hash_map, tsl::robin_map)
- C++ backing provides performance benefits for large dictionaries
- All keys are currently strings

## Examples

See `example_01_basic_usage.py` for a comprehensive example demonstrating all features.
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