Pymetrica

https://pypi.org/project/pymetrica/
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Pymetrica is a static analysis tool that computes software engineering metrics for Python codebases,...
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### Install Pymetrica from Source

Source: https://pypi.org/project/pymetrica/1.5.6

Clone the repository and install Pymetrica from source using pip.

```bash
git clone https://github.com/JuanJFarina/pymetrica
cd pymetrica
pip install -e .
```

--------------------------------

### Install Pymetrica from PyPI

Source: https://pypi.org/project/pymetrica/1.5.6

Install the latest published package from PyPI using pip.

```bash
pip install pymetrica
```

--------------------------------

### Install Pymetrica from Source

Source: https://pypi.org/project/pymetrica

Clone the repository and install Pymetrica in editable mode. This method is useful for development.

```bash
git clone https://github.com/JuanJFarina/pymetrica
cd pymetrica
pip install -e .

```

--------------------------------

### Install Pymetrica from PyPI

Source: https://pypi.org/project/pymetrica

Install the latest published package using pip. Requires Python 3.10 or newer.

```bash
pip install pymetrica

```

--------------------------------

### Get Base Statistics with Pymetrica

Source: https://pypi.org/project/pymetrica/1.5.6

Use the 'base-stats' command to get an initial overview of a codebase.

```bash
pymetrica base-stats path/to/project
```

--------------------------------

### Pymetrica Short Report Example

Source: https://pypi.org/project/pymetrica/1.5.6

Example output of a short terminal report from Pymetrica, showing key metrics like Abstract Lines Of Code, Cyclomatic Complexity, Halstead Volume, Primitive Obsession, Maintainability Cost, and Instability.

```text
----------------------------------------------------------------------------------------------------
Short Report
----------------------------------------------------------------------------------------------------
Metric: Abstract Lines Of Code
aloc_number: 6
aloc_percentage: 15.0
----------------------------------------------------------------------------------------------------
Metric: Cyclomatic Complexity
cc_number: 23
lloc_per_cc: 1.7391304347826086
----------------------------------------------------------------------------------------------------
Metric: Halstead Volume
hv_number: 704.5342159112735
hv_per_lloc: 17.613355397781838
----------------------------------------------------------------------------------------------------
Metric: Primitive Obsession
all_primitives_percent: 0.0
targeted_primitives_percent: 0.0
----------------------------------------------------------------------------------------------------
Metric: Maintainability Cost
maintainability_cost: 50.678396768622775
raw_line_cost: 50.638396768622776
----------------------------------------------------------------------------------------------------
Metric: Instability
root: 0.0
----------------------------------------------------------------------------------------------------


```

--------------------------------

### Run Pymetrica CLI

Source: https://pypi.org/project/pymetrica/1.5.6

Access the Pymetrica command-line interface after installation.

```bash
pymetrica
```

--------------------------------

### Run Pymetrica with Basic Hook Report

Source: https://pypi.org/project/pymetrica/1.5.6

Analyze a project using the 'run-all' command with the BASIC_HOOK report backend to enforce thresholds.

```bash
pymetrica run-all -rt BASIC_HOOK path/to/project
```

--------------------------------

### Analyze a Python Project with Pymetrica

Source: https://pypi.org/project/pymetrica/1.5.6

Use the 'run-all' command to analyze a specified Python project path.

```bash
pymetrica run-all path/to/project
```

--------------------------------

### List All Pymetrica CLI Commands

Source: https://pypi.org/project/pymetrica/1.5.6

View all available commands for the Pymetrica CLI.

```bash
pymetrica status
pymetrica base-stats
pymetrica aloc
pymetrica cc
pymetrica hv
pymetrica po
pymetrica mc
pymetrica li
pymetrica run-all
```

--------------------------------

### Pymetrica Architecture Overview

Source: https://pypi.org/project/pymetrica/1.5.6

Illustrates the flow of Pymetrica's analysis pipeline, from codebase parsing to report generation.

```text
Codebase Parsing
        ↓
Code Representation
        ↓
Metric Calculators
        ↓
Results
        ↓
Report Generators

```

--------------------------------

### Run Pymetrica with Hook Report Backend

Source: https://pypi.org/project/pymetrica

Enforce thresholds in automation by using the BASIC_HOOK report backend. This command analyzes the project and reports threshold violations.

```bash
pymetrica run-all -rt BASIC_HOOK path/to/project

```

--------------------------------

### Run Pymetrica Analysis

Source: https://pypi.org/project/pymetrica/1.5.6

Execute Pymetrica analysis on a specified project path. Use `--long-report` for detailed summaries and `-rt BASIC_HOOK` for CI integration with exit status.

```bash
pymetrica run-all path/to/project

```

--------------------------------

### Typical Pymetrica CLI Usage Pattern

Source: https://pypi.org/project/pymetrica/1.5.6

General pattern for using Pymetrica commands with a directory path.

```bash
pymetrica <command> DIR_PATH
```

--------------------------------

### Analyze Cyclomatic Complexity with Pymetrica

Source: https://pypi.org/project/pymetrica/1.5.6

Focus on a single metric like cyclomatic complexity (cc) using its dedicated command.

```bash
pymetrica cc path/to/project
```

--------------------------------

### Generate Architecture Diagram

Source: https://pypi.org/project/pymetrica/1.5.6

Use this command to generate a Mermaid diagram (`.mmd` file) representing the layered architecture of a specified project path. The diagram focuses on top-level layers and components, omitting root-level files and `__init__.py`-style files.

```bash
pymetrica base-stats --diagram path/to/project
```

--------------------------------

### Pymetrica Pre-commit Hooks Configuration

Source: https://pypi.org/project/pymetrica/1.5.6

Set up Pymetrica pre-commit hooks in your .pre-commit-config.yaml file.

```yaml
repos:
  - repo: https://github.com/JuanJFarina/pymetrica
    rev: v1.5.4
    hooks:
      - id: pymetrica
      - id: pymetrica-mc
      - id: pymetrica-po
```

--------------------------------

### Run Project Tests

Source: https://pypi.org/project/pymetrica/1.5.6

Execute the project's tests using pytest. These tests cover the parser, core metric calculators, diagram generation, and bundled sample codebases.

```bash
pytest
```

--------------------------------

### Python API Usage for Code Analysis

Source: https://pypi.org/project/pymetrica/1.5.6

Demonstrates a typical programmatic workflow using Pymetrica's Python API to parse a codebase, calculate various metrics, and generate a terminal report. Ensure the path to your project is correctly specified.

```python
from pymetrica.codebase_parser import create_diagram, parse_codebase
from pymetrica.metric_calculators import (
    AlocCalculator,
    CCCalculator,
    HalsteadVolumeCalculator,
    InstabilityCalculator,
    MaintainabilityCostCalculator,
    PrimitiveObsessionCalculator,
)
from pymetrica.report_generators import REPORTS_MAPPING

codebase = parse_codebase("path/to/project")

metrics = [
    AlocCalculator().calculate_metric(codebase),
    CCCalculator().calculate_metric(codebase),
    HalsteadVolumeCalculator().calculate_metric(codebase),
    PrimitiveObsessionCalculator().calculate_metric(codebase),
    MaintainabilityCostCalculator().calculate_metric(codebase),
    InstabilityCalculator().calculate_metric(codebase),
]

report_generator = REPORTS_MAPPING["BASIC_TERMINAL"](metrics)
print(report_generator.long_report().content)

create_diagram(codebase, filename="architecture.mmd")

```

--------------------------------

### Pymetrica Single Metric Analysis

Source: https://pypi.org/project/pymetrica/1.5.6

Analyze a specific metric, such as Cyclomatic Complexity (cc), for a project. This command defaults to printing the descriptive report format.

```bash
pymetrica cc path/to/project

```

--------------------------------

### Generate Mermaid Diagram

Source: https://pypi.org/project/pymetrica

Use this command to generate a Mermaid diagram representing the layered architecture of a project. The output is a .mmd file.

```bash
pymetrica base-stats --diagram path/to/project

```

--------------------------------

### Pymetrica Configuration in pyproject.toml

Source: https://pypi.org/project/pymetrica/1.5.6

Configure thresholds and exclusion patterns for Pymetrica in the pyproject.toml file.

```toml
[tool.pymetrica]
aloc_fail_threshold = 30
cc_fail_threshold = 10
hv_fail_threshold = 30
po_all_fail_threshold = 10
po_targeted_fail_threshold = 2
mc_fail_threshold = 25
exclude = ["generated/*", "vendor/*"]
top_findings = 5
```

--------------------------------

### Configure Pymetrica Thresholds and Exclusions

Source: https://pypi.org/project/pymetrica

Define custom thresholds and exclusion patterns for Pymetrica analysis in the `[tool.pymetrica]` section of `pyproject.toml`. Thresholds can be set to 0 to disable failure gating.

```toml
[tool.pymetrica]
aloc_fail_threshold = 30
cc_fail_threshold = 10
hv_fail_threshold = 30
po_all_fail_threshold = 10
po_targeted_fail_threshold = 2
mc_fail_threshold = 25
exclude = ["generated/*", "vendor/*"]
top_findings = 5

```

--------------------------------

### Instability Formula

Source: https://pypi.org/project/pymetrica/1.5.6

The formula for calculating package instability based on efferent and afferent coupling. Values range from 0 (stable) to 1 (unstable).

```mathematics
Instability = Efferent Coupling / (Afferent Coupling + Efferent Coupling)
```
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