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‎CODE_OF_CONDUCT.md

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# Contributor Covenant Code of Conduct
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## Our Pledge
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We as members, contributors, and leaders pledge to make participation in our
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community a harassment-free experience for everyone, regardless of age, body
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size, visible or invisible disability, ethnicity, sex characteristics, gender
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identity and expression, level of experience, education, socio-economic status,
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nationality, personal appearance, race, caste, color, religion, or sexual
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identity and orientation.
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We pledge to act and interact in ways that contribute to an open, welcoming,
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diverse, inclusive, and healthy community.
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## Our Standards
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Examples of behavior that contributes to a positive environment for our
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community include:
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* Demonstrating empathy and kindness toward other people
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* Being respectful of differing opinions, viewpoints, and experiences
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* Giving and gracefully accepting constructive feedback
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* Accepting responsibility and apologizing to those affected by our mistakes,
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and learning from the experience
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* Focusing on what is best not just for us as individuals, but for the overall
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community
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Examples of unacceptable behavior include:
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* The use of sexualized language or imagery, and sexual attention or advances of
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any kind
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* Trolling, insulting or derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or email address,
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without their explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Enforcement Responsibilities
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Community leaders are responsible for clarifying and enforcing our standards of
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acceptable behavior and will take appropriate and fair corrective action in
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response to any behavior that they deem inappropriate, threatening, offensive,
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or harmful.
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Community leaders have the right and responsibility to remove, edit, or reject
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comments, commits, code, wiki edits, issues, and other contributions that are
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not aligned to this Code of Conduct, and will communicate reasons for moderation
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decisions when appropriate.
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## Scope
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This Code of Conduct applies within all community spaces, and also applies when
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an individual is officially representing the community in public spaces.
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Examples of representing our community include using an official email address,
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posting via an official social media account, or acting as an appointed
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representative at an online or offline event.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported to the community leaders responsible for enforcement at
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[INSERT CONTACT METHOD].
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All complaints will be reviewed and investigated promptly and fairly.
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All community leaders are obligated to respect the privacy and security of the
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reporter of any incident.
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## Enforcement Guidelines
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Community leaders will follow these Community Impact Guidelines in determining
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the consequences for any action they deem in violation of this Code of Conduct:
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### 1. Correction
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**Community Impact**: Use of inappropriate language or other behavior deemed
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unprofessional or unwelcome in the community.
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**Consequence**: A private, written warning from community leaders, providing
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clarity around the nature of the violation and an explanation of why the
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behavior was inappropriate. A public apology may be requested.
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### 2. Warning
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**Community Impact**: A violation through a single incident or series of
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actions.
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**Consequence**: A warning with consequences for continued behavior. No
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interaction with the people involved, including unsolicited interaction with
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those enforcing the Code of Conduct, for a specified period of time. This
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includes avoiding interactions in community spaces as well as external channels
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like social media. Violating these terms may lead to a temporary or permanent
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ban.
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### 3. Temporary Ban
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**Community Impact**: A serious violation of community standards, including
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sustained inappropriate behavior.
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**Consequence**: A temporary ban from any sort of interaction or public
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communication with the community for a specified period of time. No public or
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private interaction with the people involved, including unsolicited interaction
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with those enforcing the Code of Conduct, is allowed during this period.
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Violating these terms may lead to a permanent ban.
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### 4. Permanent Ban
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**Community Impact**: Demonstrating a pattern of violation of community
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standards, including sustained inappropriate behavior, harassment of an
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individual, or aggression toward or disparagement of classes of individuals.
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**Consequence**: A permanent ban from any sort of public interaction within the
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community.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage],
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version 2.1, available at
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[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
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Community Impact Guidelines were inspired by
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[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
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For answers to common questions about this code of conduct, see the FAQ at
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[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
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[https://www.contributor-covenant.org/translations][translations].
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[homepage]: https://www.contributor-covenant.org
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[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
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[Mozilla CoC]: https://github.com/mozilla/diversity
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[FAQ]: https://www.contributor-covenant.org/faq
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[translations]: https://www.contributor-covenant.org/translations
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‎CONTRIBUTING.md

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# Contribution Guidelines
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## Issues
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If you discover an issue with an algorithm, or test, open an issue to point out areas for improvement.
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If you are comfortable with it, implement the fix and open a PR.
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## Adding tests
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See the [testing contributors guide](tests/CONTRIBUTING.md)
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## Coding Standards
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### Languages
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*GSQL*
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- Follow the [GSQL Style Guide](https://docs.tigergraph.com/gsql-ref/current/appendix/gsql-style-guide)
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*Python*
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- Use the [ruff formatter](https://docs.astral.sh/ruff/formatter/#the-ruff-formatter) to format your code
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- tests: pytest and networkx wherever applicable
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*C/CPP*
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## Pull Requests
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- Make sure git knows your name and email address:
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```
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$ git config user.name "J. Random User"
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$ git config user.email "[email protected]"
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```
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- The name and email address must be valid as we cannot accept anonymous contributions.
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- Write good commit messages.
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- Concise commit messages that describe your changes help us better understand your contributions.
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## General Guidelines
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Ensure your pull request (PR) adheres to the following guidelines:
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- Try to make the name concise and descriptive.
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- Give a good description of the change being made. Since this is very subjective, see the [Updating Your Pull Request (PR)](#updating-your-pull-request-pr) section below for further details.
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- Every pull request should be associated with one or more issues. If no issue exists yet, please create your own.
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- Make sure that all applicable issues are mentioned somewhere in the PR description. This can be done by typing # to bring up a list of issues.
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### Updating Your Pull Request (PR)
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A lot of times, making a PR adhere to the standards above can be difficult. If the maintainers notice anything that we'd like changed, we'll ask you to edit your PR before we merge it.
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This applies to both the content documented in the PR and the changed contained within the branch being merged. There's no need to open a new PR. Just edit the existing one.
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---
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Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.
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[email]: mailto:[email protected]

‎tests/CONTRIBUTING.md

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# Contribution Guidelines for Adding Tests
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### Contents
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- [Running the tests](#running-the-tests)
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- [Directory Layout](#directory-layout)
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- [Adding tests](#adding-tests)
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- [Available Graphs](#available-graphs)
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## Running the tests
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Execute the following to download the dependencies and run the tests. Make sure you're in a venv.
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```sh
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echo '
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HOST_NAME="https://tg-hostname"
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USER_NAME=tigergraph
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PASS=tigergraph
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' >> test/.env
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pip install -r requirements.txt
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./run.sh
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```
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`test/.env`
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- HOST_NAME: A that you have querywriter access to so setup.py can load data and queries to a subgraph named `graph_algorithms_testing`
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- USER_NAME=admin/writer
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- PASS=users_pass
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`run.sh` does a few things:
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- runs `data/create_baseline.py`
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- this creates the baselines from the graphs listed in that file
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- runs the setup script to make sure the graph is created and data is loaded
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- runs the tests with pytest
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## Directory layout
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Data: stores the satic data for creating graphs, and algorithm baseline results.
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- CSV files under `data/[heterogeneous_edges, unweighted_edges, weighted_edges]` store the adjacency information for creating graphs.
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- for example `data/weighted_edges/line_edges.csv` stores the edges and weights to create a weighted, line graph.
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- JSON files under `data/baseline` store the results for a given algorithm on a given graph type.
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- for example `data/baseline/centrality/pagerank/Line_Directed.json` stores the results for pagerank on a directed line graph
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test:
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- setup.py: creates the graph, loads the data and installs the queries from pyTG's featurizer. Any new/custom queries need to be manually installed
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- test<algo_family>.py: houses the testing code for each family of algorithms
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```
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├── data
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│   ├── baseline
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│   │   ├── <algo_family>
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│   │   │   └── <algo_name>
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│   │ │ └── <GraphType>.json
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│   ├── <edge_family>
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│   │ └── <graph_type>.csv
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│   └── create_baseline.py
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├── requirements.txt
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├── run.sh
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├── test
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│   ├── pyrightconfig.json
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│   ├── setup.py
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│   ├── test_centrality.py
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│   ├── test_community.py
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│   ├── test_path_finding.py
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│   ├── test_topological_link_prediction.py
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│   └── util.py
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```
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## Adding tests
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Start with the baseline. Add a section or module to `create_baseline.py` that creates a baseline for all the necessary graph types. The outline of the baseline should be written to the correct
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baseline path (see above [layout](#directory-layout)).
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Add a method to the correct test file (i.e., community algorigthms go in community.py). The first test method in `test/test_centrality.py` is a good template to follow:
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```py
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# this function will run once for each of the graph names in the undirected_graphs list
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@pytest.mark.parametrize("test_name", undirected_graphs)
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def test_degree_centrality1(self, test_name):
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# query params
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params = {
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"v_type_set": ["V20"],
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"e_type_set": [test_name],
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"reverse_e_type_set": [test_name],
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"in_degree": True,
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"out_degree": False,
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"top_k": 100,
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"print_results": True,
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"result_attribute": "",
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"file_path": "",
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}
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with open(f"data/baseline/centrality/degree_centrality/{test_name}.json") as f:
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baseline = json.load(f)
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baseline = sorted(baseline[0]["top_scores"], key=lambda x: x["Vertex_ID"])
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# call the the algorithm through the featurizer
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result = self.feat.runAlgorithm("tg_degree_cent", params=params)
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result = sorted(result[0]["top_scores"], key=lambda x: x["Vertex_ID"])
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# check that the results agree with the baseline
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for b in baseline:
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for r in result:
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if r["Vertex_ID"] == b["Vertex_ID"] and r["score"] != pytest.approx(
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b["score"]
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):
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pytest.fail(f'{r["score"]} != {b["score"]}')
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```
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## Available Graphs
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Example usage:
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- If you want to run a query on a directed, weighted, line graph, use the V20 verts and Line_Directed_Weighted edges.
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| Graph | Type | Vertices | Edges |
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| --------------------------- | ------------------------------------------------------------ | -------- | -------------------------------- |
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| Null | | V0 | |
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| Single node | | V1 | |
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| Empty graph | Undirected | V20 | Empty |
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| | Directed | | Empty_Directed |
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| Line | Undirected, unweighted | V20 | Line |
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| | Directed, unweighted | | Line_Directed |
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| | Undirected, weighted | | Line_Weighted |
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| | Directed, weighted | | Line_Directed_Weighted |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | Line_Heterogeneous |
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| Ring | Undirected, unweighted | V20 | Ring |
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| | Directed, unweighted | | Ring_Directed |
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| | Undirected, weighted | | Ring_Weighted |
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| | Directed, weighted | | Ring_Directed_Weighted |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | Ring_Heterogeneous |
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| Hub & spoke | Undirected, unweighted | V20 | Hub_Spoke |
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| | Directed (towards the spokes), unweighted Hub_Spoke_Directed | | |
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| | Undirected, weighted Hub_Spoke_Weighted | | |
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| | Directed, weighted Hub_Spoke_Directed_Weighted | | |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | Hub_Spoke_Heterogeneous |
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| Hub-connected hub & spoke | Undirected, unweighted | V20 | Hub_Connected_Hub_Spoke |
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| | Undirected, weighted | | Hub_Connected_Hub_Spoke_Weighted |
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| Tree | Undirected, unweighted | V20 | Tree |
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| | Directed, unweighted | | Tree_Directed |
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| | Undirected, weighted | | Tree_Weighted |
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| | Directed, weighted | | Tree_Directed_Weighted |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | Tree_Heterogeneous |
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| Complete | Undirected, unweighted | V8 | Complete |
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| | Directed, unweighted | | Complete_Directed |
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| | Undirected, weighted | | Complete_Weighted |
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| | Directed, weighted | | Complete_Directed_Weighted |
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| | Heterogeneous vertex types, directed, weighted | V4, V8 | Complete_Heterogeneous |
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| DAG | Directed, unweighted | V20 | DAG_Directed |
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| | Directed, weighted | | DAG_Directed_Weighted |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | DAG_Heterogeneous |
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| Graph with negative cycles | Directed, weighted | V20 | Negative_cycles |
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| | Heterogeneous vertex types, directed, weighted | V20, V8 | Negative_Cycle_Heterogeneous |
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| Topological link prediction | Unweighted, undirected | V8 | topo_link1 |
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| | topo_link2 | | |
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| | topo_link3 | | |
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| | topo_link4 | | |
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| | topo_link5 | | |
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| | topo_link6 | | |
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| | Unweighted, directed | | topo_link_directed |
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| Same Community | no edges | V4 | |

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