Enhance README.md for better project discoverability (#79)

This PR significantly improves the README.md to enhance project
discoverability and user onboarding experience by addressing all
requirements from the automated analysis.

## Changes Made

- **Expanded project description**: Added comprehensive overview of core
utilities provided (math, datetime, typing, id, module)
- **Added Installation section**: Includes pip install instructions and
pyproject.toml dependency examples
- **Added Quick Start section**: Provides immediate overview of main
functionality with working code examples
- **Added detailed Code Examples**: Three comprehensive sections
demonstrating:
  - Math utilities (`is_close_to_zero`, `Interval` for range checking)
  - Typing utilities (`@disable_init` decorator for factory patterns)
  - Strongly-typed IDs (`BaseId` subclassing for type safety)

## Metrics Improvement

- **Lines**: 27 → 143 (requirement: >30)
- **Characters**: 1000 → 4058 (requirement: >1200)
- **Code blocks**: 0 → 6 comprehensive examples
- **Sections**: Added Installation, Quick Start, and Code Examples

## Quality Assurance

- All code examples have been tested and work correctly
- Maintains existing structure and links
- Follows modern Python best practices in examples
- Provides practical, copy-paste ready code snippets

The enhanced README now provides a much better first impression for
developers discovering the project, with clear installation instructions
and immediately usable examples that demonstrate the library's value.

Fixes #74.

---------

Signed-off-by: Leandro Lucarella <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: llucax <[email protected]>
Co-authored-by: Leandro Lucarella <[email protected]>
Co-authored-by: Marenz <[email protected]>

Author: 3 people

README.md

@@ -6,12 +6,14 @@
 
 ## Introduction
 
-Core utilities to complement Python's standard library.
+Core utilities to complement Python's standard library. This library provides
+essential building blocks for Python applications, including mathematical
+utilities, datetime constants, typing helpers, strongly-typed identifiers, and
+module introspection tools.
 
-## Documentation
-
-For information on how to use this library, please refer to the
-[documentation](https://frequenz-floss.github.io/frequenz-core-python/).
+The `frequenz-core` library is designed to be lightweight, type-safe, and
+follow modern Python best practices. It fills common gaps in the standard
+library with utilities that are frequently needed across different projects.
 
 ## Supported Platforms
 
@@ -21,6 +23,130 @@ The following platforms are officially supported (tested):
 - **Operating System:** Ubuntu Linux 20.04
 - **Architectures:** amd64, arm64
 
+## Installation
+
+You can install the library from PyPI using pip:
+
+```bash
+python -m pip install frequenz-core
+```
+
+Or add it to your project's dependencies in `pyproject.toml`:
+
+```toml
+[project]
+dependencies = [
+    "frequenz-core >= 1.0.2, < 2",
+]
+```
+
+> [!NOTE]
+> We recommend pinning the dependency to the latest version for programs,
+> like `"frequenz-core == 1.0.2"`, and specifying a version range spanning
+> one major version for libraries, like `"frequenz-core >= 1.0.2, < 2"`.
+> We follow [semver](https://semver.org/).
+
+## Quick Start
+
+Here's a quick overview of the main functionality:
+
+```python
+from frequenz.core.math import is_close_to_zero, Interval
+from frequenz.core.datetime import UNIX_EPOCH
+from frequenz.core.module import get_public_module_name
+
+# Math utilities
+print(is_close_to_zero(1e-10))  # True - check if float is close to zero
+interval = Interval(1, 10)
+print(5 in interval)  # True - check if value is in range
+
+# Datetime utilities
+print(UNIX_EPOCH)  # 1970-01-01 00:00:00+00:00
+
+# Module utilities
+public_name = get_public_module_name("my.package._private.module")
+print(public_name)  # "my.package"
+```
+
+## Code Examples
+
+### Math Utilities
+
+The math module provides utilities for floating-point comparisons and interval
+checking:
+
+```python
+from frequenz.core.math import is_close_to_zero, Interval
+
+# Robust floating-point zero comparison
+assert is_close_to_zero(1e-10)  # True
+assert not is_close_to_zero(0.1)  # False
+
+# Interval checking with inclusive bounds
+numbers = Interval(0, 100)
+assert 50 in numbers  # True
+assert not (150 in numbers)  # False - 150 is outside the interval
+
+# Unbounded intervals
+positive = Interval(0, None)  # [0, ∞]
+assert 1000 in positive  # True
+```
+
+### Typing Utilities
+
+Disable class constructors to enforce factory pattern usage:
+
+```python
+from frequenz.core.typing import disable_init
+
+@disable_init
+class ApiClient:
+    @classmethod
+    def create(cls, api_key: str) -> "ApiClient":
+        # Factory method with validation
+        instance = cls.__new__(cls)
+        # Custom initialization logic here
+        return instance
+
+# This will raise TypeError:
+# client = ApiClient()  # ❌ TypeError
+
+# Use factory method instead:
+client = ApiClient.create("my-api-key")  # ✅ Works
+```
+
+### Strongly-Typed IDs
+
+Create type-safe identifiers for different entities:
+
+```python
+from frequenz.core.id import BaseId
+
+class UserId(BaseId, str_prefix="USR"):
+    pass
+
+class OrderId(BaseId, str_prefix="ORD"):
+    pass
+
+user_id = UserId(123)
+order_id = OrderId(456)
+
+print(f"User: {user_id}")  # User: USR123
+print(f"Order: {order_id}")  # Order: ORD456
+
+# Type safety prevents mixing different ID types
+def process_user(user_id: UserId) -> None:
+    print(f"Processing user: {user_id}")
+
+process_user(user_id)  # ✅ Works
+# process_user(order_id)  # ❌ Type error
+```
+
+## Documentation
+
+For information on how to use this library, please refer to the
+[documentation](https://frequenz-floss.github.io/frequenz-core-python/).
+
 ## Contributing
 
 If you want to know how to build this project and contribute to it, please