Metadata-Version: 2.1
Name: tackle-dgi
Version: 1.0.0
Summary: Konveyor Tackle Data Gravity Insights
Home-page: https://github.com/konveyor/tackle-data-gravity-insights
Author: IBM
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: Click (==8.1.3)
Requires-Dist: neomodel (==4.0.10)
Requires-Dist: simple-ddl-parser (==0.25.0)
Requires-Dist: PyYAML (==6.0)
Requires-Dist: ipdb (==0.13.11)
Requires-Dist: pandas (==1.5.3)
Requires-Dist: tqdm (==4.65.0)
Requires-Dist: rich (==13.3.2)
Requires-Dist: rich-click (==1.6.1)
Requires-Dist: py2neo (==2021.2.3)
Requires-Dist: minerva-cargo (==1.1.0)
Provides-Extra: dev
Requires-Dist: nose (==1.3.7) ; extra == 'dev'
Requires-Dist: pinocchio (==0.4.3) ; extra == 'dev'
Requires-Dist: coverage (==7.1.0) ; extra == 'dev'
Requires-Dist: pylint (==2.16.2) ; extra == 'dev'
Requires-Dist: py2neo (==2021.2.3) ; extra == 'dev'
Requires-Dist: flake8 (==6.0.0) ; extra == 'dev'
Requires-Dist: black (==23.1.0) ; extra == 'dev'
Requires-Dist: tox (==3.24.5) ; extra == 'dev'

# Tackle Data Gravity Insights

[![Build Status](https://github.com/konveyor/tackle-data-gravity-insights/actions/workflows/ci-build.yml/badge.svg)](https://github.com/konveyor/tackle-data-gravity-insights/actions)
[![PyPI version](https://badge.fury.io/py/tackle-dgi.svg)](https://badge.fury.io/py/tackle-dgi)
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

Tackle Data Gravity Insights is a new way to gain insights into your monolithic application code so that you can better refactor it into domain driven microservices. It takes a wholistic approach to application modernization and refactoring by triangulating between code, and, data, and transactional boundaries.

Application modernization is a complex topic with refactoring being the most complicated undertaking. Current tools only look at the application source code or only at the runtime traces when refactoring. This, however, yields a myopic view that doesn't take into account data relationships and transactional scopes. This project hopes to join the three views of application, data, and transactions into a 3D view of the all of the application relationships so that you can easily discover application domains of interest and refactor them into microservices. Accordingly, DGI consists of three key components:

**1. Call-/Control-/Data-dependency Analysis (code2graph):** This is a source code analysis component that extracts various static code interaction features pertaining to object/dataflow dependencies and their respective lifecycle information. It presents this information in a graphical format with Classes as _nodes_ and their dataflow, call-return, and heap-dependency interactions _edges_.

**2. Schema:** This component of DGI infers the schema of the underlying databases used in the application. It presents this information in a graphical format with database tables and columns as _nodes_ and their relationships (e.g., foreign key, etc.) as _edges_.

**3. Transactions to graph (tx2graph):** This component of DGI leverages [Tackle-DiVA](https://github.com/konveyor/tackle-diva) to perform a data-centric application analysis. It imports a set of target application source files (*.java/xml) and provides following analysis result files. It presents this information in a graphical format with database tables and classes as _nodes_ and their transactional relationships as _edges_.

## Installation

Tackle Data Gravity Insights is written in Python and can be installed using the Python package manager `pip`.

```bash
pip install -U tackle-dgi
```

## Usage

You will need an instance of Neo4j to store the graphs that `dgi` creates. You can start one up in a docker container and set an environment variable to let `dgi` know where to find it.

```bash
docker run -d --name neo4j \
    -p 7474:7474 \
    -p 7687:7687 \
    -e NEO4J_AUTH="neo4j:konveyor" \
    neo4j:4.4.17
```

Save the bolt url for further use:
```
export NEO4J_BOLT_URL="neo4j://neo4j:konveyor@localhost:7687"
```

You can now use the `dgi` command to load information about your application into the graph database.

```man
 Usage: dgi [OPTIONS] COMMAND [ARGS]...

 Tackle Data Gravity Insights

╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --neo4j-bolt  -n  TEXT  Neo4j Bolt URL                                                                               │
│ --quiet       -q        Be more quiet                                                                                │
│ --validate    -v        Validate but don't populate graph                                                            │
│ --clear       -c        Clear graph before loading                                                                   │
│ --help                  Show this message and exit.                                                                  │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ───────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ c2g         Code2Graph add various program dependencies (i.e., call return, heap, and data) into the graph           │
│ partition   Partition is a command runs the CARGO algorithm to (re-)partition a monolith into microservices          │
│ s2g         Schema2Graph parses SQL schema (*.DDL file) into the graph                                               │
│ tx2g        Transaction2Graph add edges denoting CRUD operations to the graph.                                       │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```

## Demo

This is a demonstration of the usage of DGI

1. [Demonstration](docs/demo.md)

## Running DGI

To run this project please refer to the steps in the getting started guide

1. [Getting Started](docs/getting-started.md)

## Contributing

To contribute to this project you will need to set up your development environment and set up some files. The steps are in the following file:

1. [Set up your Developer Environment](docs/development.md)


