Egyptian Names (`egy-names`) #

The Production-Grade Onomastic Intelligence and Computational Linguistic Engine for Egyptian Names #

Documentation

Why Egyptian Names Are Unique and Computationally Complex #

Unlike Western naming conventions (Given Name + Surname), Egyptian personal naming is governed by an unbroken patronymic genealogical chain where an individual's full legal name is an ordered succession of ancestral personal names:

$$\text{Full Legal Name} = \text{Personal Name} \to \text{Father} \to \text{Grandfather} \to \text{Great-Grandfather} \to \text{Family Surname / Clan}$$

This ancient onomastic system—intertwined with Pharaonic and Coptic substrates, Classical Arabic morphology, Ottoman Turkish guild surnames, and Nile Delta and Upper Egypt geographic toponyms—presents extraordinary linguistic richness:

The Egyptian Onomastic Spectrum #

Cultural Heritage	Example Names (Arabic)	Transliteration	Historical and Etymological Origin
Ancient / Coptic Substrate	مهرائيل , سوريال , بهنس , مينا	Mehraeil, Soryal, Bahnas, Mina	Pharaonic theophoric names and Coptic Christian heritage dating back millennia
Classical Islamic / Arabic	محمد , عبد الرحمن , فاطمة , نور الدين	Mohamed, Abdelrahman, Fatma, Nour Eldin	Pure Semitic triliteral roots (h-m-d, a-b-d, f-t-m) and honorific compounds
Ottoman / Turkish Guilds	بوادقجي , الجوهرجي , شلتوت , خاقان	Bawadqgy, Gowharji, Shaltout, Khaqan	Professional trade guilds, military titles, and aristocratic family surnames
Nile Geographic Toponyms	المنياوي , الطهطاوي , الشناوي , الدمياطي	Elminyawy, Tahtawy, Elshenawy, Domyaty	Surnames of geographic attribution across the 27 Governorates of Upper and Lower Egypt

The 5 Hard Problems Solved by `egy-names` #

Unspaced Concatenation in Legacy Databases: Egyptian civil records and bank databases frequently compress full chains without spaces (محمدأحمدعليحسنالشناوي). Standard splitters fail; egy-names solves this via Dynamic Programming shortest-path lattice segmentation.
Generational Slot Drift and Demographics: The exact same name (فاروق, شهد, كريم) possesses radically different statistical probabilities depending on whether it occupies Slot 1 (Student/Child), Slot 2 (Father), or Slot 3 (Grandfather).
Compound Name Integrity: Prefix-bound names (عبد الرحمن, أبو بكر, نور الدين, فاطمة الزهراء, ذو الفقار) are recognized as atomic entities without corrupting patronymic slot counting.
Phonetic Egyptian Passport Transliteration: Standard Arabic transliterators use Levantine or Gulf phonetics (Jamal, Hamid). egy-names enforces authentic Egyptian Civil Registry phonetics (Gamal, Hamed, El-, Abou-).
100% Arabic Vocalization and Deep Root Etymology: Complete Tashkeel (diacritization) and root analysis across all 44,626 canonical entries.

Feature Engineering Deep Dive #

egy-names is designed as a zero-hallucination, high-performance linguistic engine. Here is the architectural philosophy and execution behind each capability:

1. Grounded 6-Slot Patronymic Name Generation #

The Problem with Generic Generators: Tools like Faker randomly choose words from a flat list, creating culturally absurd chains (such as putting female names as fathers, pairing incompatible religious markers, or using archaic 19th-century surnames as first names for children).
Our Architecture: We formulated name generation as a joint multi-variate transition graph over 6 genealogical positions: $$P(N_1, N_2, N_3, N_4, N_5) = P(N_1 \mid G, R, A) \times \left[ \prod_{k=2}^{4} P(N_k \mid \text{Male}, R, S_k) \right] \times P(N_5 \mid \text{Surname})$$
Why It Is Robust:
- $N_1$ respects requested gender ($G$), religion ($R$), and age cohort ($A$).
- $N_2, N_3, N_4$ are mathematically bounded to authentic male given names matching religious continuity.
- $N_5$ samples from real Egyptian clan and toponymic surname distributions.

2. Generational Gaussian Age Intelligence Engine #

The Core Insight: Names are temporal cultural artifacts. A name like شهد or يارا belongs overwhelmingly to Egyptian youth born in the 2000s, whereas فاروق or بسيوني belongs to grandfathers born in the 1930s–1940s.
Mathematical Modeling: We anchored the national corpus to its mean examination year ($Y_{\text{data}} = 2020$) and graduation age ($A_{\text{grad}} = 18$), yielding a baseline birth center of 2002 for Slot 1. Applying the national inter-generational span ($\Delta_{\text{gen}} = 30\text{ years}$):
- $\text{Slot }1 \text{ (Student): Center } 2002 \ (\approx 24\text{ yrs in }2026)$
- $\text{Slot }2 \text{ (Father): Center } 1972 \ (\approx 54\text{ yrs in }2026)$
- $\text{Slot }3 \text{ (Grandfather): Center } 1942 \ (\approx 84\text{ yrs in }2026)$
- $\text{Slot }4 \text{ (Great-Grandfather): Center } 1912 \ (\text{Historical})$
Continuous Gaussian Scoring: $$w_i = \exp\left(-\frac{1}{2} \left(\frac{\text{Target Birth Year} - \text{Center}_i}{\sigma}\right)^2\right), \quad \sigma = 12\text{ years}$$
Multi-Token Cross-Generational Corroboration: When analyzing a full name chain (e.g. "كريم أشرف فاروق"), the engine checks the person (كريم, youth) + father (أشرف, parent) + grandfather (فاروق, grandparent). When all generational vectors align, it triggers a Bayesian corroboration boost, elevating confidence to 0.641.

3. Dynamic Programming (DP) Unspaced Text Segmentation #

The Challenge: Egyptian government and bank archives frequently contain concatenated strings without spaces (e.g. محمدأحمدعليحسنالشناوي).
Our Solution: Formulated as a Unicode codepoint shortest-path DAG optimization: $$\text{Cost}(i) = \min_{j < i} \Big( \text{Cost}(j) + \text{BaseCost} + \text{Bonus}(\text{Freq}{j..i}) + \lambda \cdot \text{Length}{j..i} \Big)$$
Why It Is Robust:
- Splits 3-to-6-part unspaced chains in $< 0.05\text{ ms}$.
- Intelligently preserves prefixed compound names (عبد الرحمن, نور الدين, فاطمة الزهراء).
- Recovers smoothly if non-Arabic or foreign noise tokens are embedded.

4. 100% Arabic Tashkeel (Diacritization) and Vocalization #

The Challenge: Arabic without Tashkeel is ambiguous (محمد could theoretically be read as Mohamed, Mahmad, or Mohamad).
Our Solution: Every single one of the 44,626 canonical lemmas is 100% vocalized with classical diacritics (Fathah, Dammah, Kasrah, Shaddah, Sukun).
Compound Awareness: Handles bound genitive constructs (عبدالرحمن $\to$ عَبْدُ الرَّحْمَن, حسام الدين $\to$ حُسَامُ الدِّين).

5. Authentic Egyptian Passport Transliteration #

The Challenge: Generic Arabic transliterators use Levantine or Gulf rules (producing Jamal, Hamid, Jihan).
Our Solution: We engineered an authentic Egyptian Civil Registry phonetic engine enforcing the distinctive Egyptian pronunciation:
- ج $\to$ G (Gamal, Gihan, Magdy)
- ح $\to$ H (Hassan, Hamed)
- Definite article $\to$ El- (Elshazly, Elsayed, Elsharkawy)
- Theophoric compounds $\to$ Abdel- / Abou- (Abdelrahman, Abdelhamid, Aboubakr)

6. Deep Morphological Etymology, Roots, and Toponyms #

100% Bilingual Coverage: Every entry in the 44.6K lexicon includes rich Arabic and English linguistic definitions:
- Semitic Triliteral Roots: e.g., محمد $\to$ المحمود؛ كثير الخصال المحمودة (من الجذر ح م د).
- Coptic/Ancient Heritage: e.g., مهرائيل $\to$ اسم قبطي/سرياني مركب يعني هبة الله أو عطية النور.
- Ottoman Guild Occupations: e.g., بوادقجي $\to$ صانع أو بائع البارود في العهد العثماني.
- Nile Delta and Upper Egypt Toponyms: e.g., المنياوي $\to$ نسبة إلى مدينة المنيا في صعيد مصر.

7. 23,457 Deterministic Typo and Orthographic Correction Rules #

The Challenge: Real-world citizen data entry is plagued by typos, keyboard slips, and OCR scanning noise.
Our Solution: Extracted from 15.88M+ records to build an in-memory $O(1)$ lookup hash index covering:
- Missing/Extra letters (ابراهم $\to$ إبراهيم)
- Compound fusion/spacing (عبدالرحمن $\to$ عبد الرحمن)
- Alif Maqsura vs. Ya (مصطفا $\to$ مصطفى, يحي $\to$ يحيى)
- Hamza normalization (اسماعيل $\to$ إسماعيل)
- Ta Marbuta vs. Ha (فاطمه $\to$ فاطمة)

8. Bayesian Demographic and Religion Inference #

How It Works: Applies empirical frequency marginalization over patronymic chains.
Lineage Continuity: Distinguishes between neutral names shared across denominations (إبراهيم, يوسف, سمير, عادل) and distinct markers (ميخائيل, جرجس, شنودة vs محمد, أحمد, مصطفى), calculating calibrated Bayesian confidence scores.

9. Authentic Egyptian Pet Names (أسماء الدلع) #

The Cultural Nuance: Egyptian pet names follow deeply rooted morphological diminutive patterns (فَعُّول, مَيْفُو, فَعُّودَة) distinct from Levantine or Gulf nicknames.
4-Way Multi-Modal Representation: Every pet name is provided in:
1. Plain Arabic lemma (ميدو, حمو, حمودة)
2. Full Egyptian vocalized Tashkeel (مِيدُو, حَمُّو, حَمُّودَة)
3. Transliterated English (Mido, Hamou, Hamouda)
4. Egyptian Colloquial IPA phonetics ([ˈmiːdu], [ˈħæm.mu], [ħæmˈmuːdæ])

10. Iconic Egyptian Public Figures (الأسماء المشهورة) #

Empirical Validation: Filtered exclusively for notable Egyptian historical leaders, scientists, authors, athletes, artists, and Nobel laureates.
Bilingual Descriptions: Provides concise historical context in both Arabic and English (e.g. محمد صلاح - قائد منتخب مصر وهداف ليفربول العالمي / Mohamed Salah - Egyptian National Football Captain & Global Icon).

11. Dual Vocalization (Standard vs. Egyptian Colloquial Tashkeel) #

Standard Tashkeel (tashkeel_standard): Full Modern Standard Arabic / Classical Quranic vocalization (مُحَمَّد, آيَات).
Egyptian Tashkeel (tashkeel_eg): Real-world Egyptian colloquial vocalization with word-final sukun and dialectal vowel harmony (مُحَمَّدْ, آيَاتْ).

12. Standard & Egyptian IPA Phonetics (for AI TTS & Linguistics) #

The Phonetic Bridge: Built specifically for Speech Synthesis (TTS), Voice AI, and non-native learners.
Accurate Glottal & Velar Shifts: Correctly reflects Egyptian /d͡ʒ/ $\to$ [ɡ] (Gamal [ɡæˈmæːl]) and vowel elongation.

13. Multi-Criteria Onomastic Search & Lexical Filtering #

High-Performance Search Engine: Sub-millisecond filtering across all 44,626 names by prefix, infix, suffix, gender, religion, etymological origin, and sociological generation trend.

14. Patronymic Chain Role Assignment & Custom Formatting #

Structural Decomposition: Dynamically classifies every token in a multi-part chain into its exact genealogical position (person, father, grandfather, ancestor, family_name).
Custom Template Engine: Format strings with arbitrary templates (e.g. "{person} {father} {family}" $\to$ "محمد أحمد الشاذلي").

The Mathematics of Grounded Patronymic Generation #

The 6-Slot Generational Model #

Slot	Role	Typical Demographics	Generation Era	Example Realization
Slot 1	Person ($N_1$)	Youth / Student (Male or Female)	Age ~24 in 2026	`يارا` (Yara)
Slot 2	Father ($N_2$)	Direct Paternal Lineage (Male Only)	Age ~54 in 2026	`عادل` (Adel)
Slot 3	Grandfather ($N_3$)	Paternal Grandfather (Male Only)	Age ~84 in 2026	`فاروق` (Farouk)
Slot 4	Ancestor ($N_4$)	Ancestral Patriarch (Male Only)	Historical Era	`مخلوف` (Makhlouf)
Slot 5	Family Surname ($N_5$)	Clan / Toponymic Surname	All Generations	`الشناوي` (Elshenawy)

Comparison with Existing Systems #

Dimension	Standard Open-Source / LLMs	`egy-names` (v0.2.1)
National Empirical Corpus	Synthetic / web-scraped (<50K records)	15.88M+ Verified Official Records (30M+ total corpus)
Master Lexicon Size	1,000–5,000 common names	44,626 Unique Canonical Lemmas (>99.9% population coverage)
Spelling Typo Corrections	Basic regex / none	23,457 Deterministic Correction Rules
Execution Latency	500ms – 2,000ms (LLM API call)	< 0.01 ms (Sub-microsecond In-Memory Hash Trie)
Dependencies and Privacy	Cloud APIs / Internet required	Zero Dependencies • 100% Offline and Deterministic
Arabic Diacritization (Tashkeel)	Partial guessing	100.0% Verified Arabic Tashkeel (44,626/44,626)
Morphological Etymology	None	100.0% Roots and Toponyms in Arabic and English
Age Intelligence Engine	Non-existent	Continuous Gaussian Generational Demographic Model
Cross-Language Parity	Python-only	7 Native SDKs (Python, TS, Swift, C#, Dart, Java, C++)

National Corpus Genesis and Empirical Grounding #

egy-names is extracted from 15,875,535 official examination records spanning 5 nation-wide cohorts across all 27 Egyptian Governorates:

Transformation Phase	Entity Count	Description
Phase 0: Raw National Records	15,875,535 Records	Official student and citizen examination rows across 494 national dataset files
Phase 1: Patronymic Occurrences	~63,500,000 Tokens	Individual name slot occurrences across all genealogical positions
Phase 2: Raw Unique Word Tokens	43,333 Distinct Words	Unique word forms before spelling normalization
Phase 3: Typo and Orthography Rules	23,457 Rules	Mappings for misspellings and unspaced compounds (`عبدالرحمن` $\to$ `عبد الرحمن`)
Phase 4: Master Canonical Lexicon	44,626 Master Lemmas	The complete verified onomastic dictionary of Egypt

Installation and Multi-Language Usage #

Full Documentation: For exhaustive method signatures, parameter tables, and advanced configurations, see the Complete API Reference.

1. Python (3.9+) #

pip install --upgrade egy-names==0.3.2

from egy_names import EgyNames

e = EgyNames()

# 1. Authentic Egyptian Pet Names (أسماء الدلع)
print(e.dallaa("محمد", format="tashkeel"))  # ['مِيدُو', 'حَمُّو', 'حَمُّودَة']
print(e.dallaa("محمد", format="ipa"))       # ['[ˈmiːdu]', '[ˈħæm.mu]', '[ħæmˈmuːdæ]']
print(e.dallaa_info("محمد"))                # [PetName(ar='ميدو', tashkeel='مِيدُو', en='Mido', ipa='[ˈmiːdu]'), ...]

# 2. Authentic Egyptian Public Figures (الأسماء المشهورة)
print(e.famous_figures("محمد", lang="en"))
# -> ['Mohamed Salah (Egyptian National Football Captain & Global Icon)', 'Mohamed Ali Pasha (Founder of Modern Egypt)', ...]

# 3. Dual Vocalization (Tashkeel) & IPA Transcriptions
print(e.tashkeel("محمد عبدالرحمن الشرقاوي")) # "مُحَمَّد عَبْدُ الرَّحْمَن الشَّرْقَاوِيّ"
print(e.tashkeel_eg("محمد"))                 # "مُحَمَّدْ"
print(e.ipa_eg("جمال"))                      # "[ɡæˈmæːl]" (Authentic Egyptian [ɡ])
print(e.ipa_standard("جمال"))                # "/d͡ʒamaːl/"

# 4. Concatenated Dynamic Programming Splitting
print(e.split("محمدأحمدعليحسنالشناوي"))
# -> ['محمد', 'أحمد', 'علي', 'حسن', 'الشناوي']

# 5. Deterministic Typo and OCR Correction
print(e.correct("احمد مصطفا عبد الرحيم يحي"))
# -> "أحمد مصطفى عبدالرحيم يحيى"

# 6. Morphological Roots and Etymology
print(e.info("محمد").root)                   # "ح-م-د"
print(e.meaning("المنياوي"))
# -> {'ar': 'نسبة إلى مدينة المنيا في صعيد مصر...', 'en': 'Attributed to Minya in Upper Egypt...'}

# 7. Grounded 6-Slot Patronymic Generation
names = e.generate(count=3, gender="female", religion="christian", length=4)
for n in names:
    print(f"{n.ar}  --  {n.en}")

# 8. Generational Age Intelligence
det = e.detect_age("كريم أشرف فاروق")
print(f"Age: ~{det.estimated_age} yrs | Conf: {det.confidence} | {det.generation_label}")

2. TypeScript / JavaScript (Node.js & Modern Browsers) #

npm install egy-names@0.3.2

import { EgyNames, Gender, Religion } from 'egy-names';

const en = new EgyNames();

// 1. Pet Names & Figures
console.log(en.dallaa("محمد", "tashkeel")); // ['مِيدُو', 'حَمُّو', 'حَمُّودَة']
console.log(en.famousFigures("محمد", "en")); // ['Mohamed Salah (Egyptian National Football Captain & Global Icon)', ...]

// 2. Translation, Tashkeel & IPA
console.log(en.translate("محمد أحمد علي")); // "Mohamed Ahmed Ali"
console.log(en.tashkeel("محمد عبدالرحمن")); // "مُحَمَّد عَبْدُ الرَّحْمَن"
console.log(en.ipaEg("جمال")); // "[ɡæˈmæːl]"

// 3. Dynamic Programming Splitting
console.log(en.split("محمدأحمدعليحسن")); // ["محمد", "أحمد", "علي", "حسن"]

// 4. Demographic Inferences
console.log(en.detectGender("فاطمة الزهراء")); // { gender: 'female', confidence: 0.95 }
console.log(en.detectReligion("مينا جرجس بطرس")); // { religion: 'christian', confidence: 0.98 }

3. Swift (iOS / macOS / watchOS / visionOS) #

Add in Xcode or Package.swift:

dependencies: [
    .package(url: "https://github.com/AbdullahAfifyKhalil/egy-names.git", from: "0.3.2")
]

import EgyNames

let en = EgyptianNames()

// Pet Names and Public Figures
let petNames = en.dallaa("محمد", format: "tashkeel") // ["مِيدُو", "حَمُّو", "حَمُّودَة"]
let figures = en.famousFigures("محمد", lang: "en")

// Splitting and Tashkeel
let parts = en.split("محمدأحمدعليحسن") // ["محمد", "أحمد", "علي", "حسن"]
print(en.tashkeel("محمد عبدالرحمن")) // "مُحَمَّد عَبْدُ الرَّحْمَن"
print(en.translate("محمد أحمد علي")) // "Mohamed Ahmed Ali"

4. .NET / C# #

dotnet add package egy-names --version 0.3.2

using EgyNames;

var en = new EgyptianNamesEngine();

// Generation & Transliteration
var names = en.Generate(count: 3, gender: "female");
Console.WriteLine(en.Translate("محمد أحمد علي")); // Mohamed Ahmed Ali

// 14D Features
Console.WriteLine(string.Join(", ", en.Dallaa("محمد", "tashkeel"))); // مِيدُو, حَمُّو, حَمُّودَة
Console.WriteLine(en.Tashkeel("محمد عبدالرحمن")); // مُحَمَّد عَبْدُ الرَّحْمَن
Console.WriteLine(string.Join(", ", en.Split("محمدأحمدعليحسن"))); // محمد, أحمد, علي, حسن

5. Dart / Flutter #

flutter pub add egy_names:^0.3.2

import 'package:egy_names/egy_names.dart';

void main() {
  final en = EgyNames();
  
  // 14D Features & Pet Names
  print(en.dallaa('محمد', format: 'ipa')); // ['[ˈmiːdu]', '[ˈħæm.mu]', '[ħæmˈmuːdæ]']
  print(en.famousFigures('محمد', lang: 'ar'));
  print(en.ipaEg('محمد')); // '[moˈħamːæd]'

  // Splitting & Translation
  print(en.translate("محمد أحمد علي")); // Mohamed Ahmed Ali
  print(en.tashkeel("محمد عبدالرحمن")); // مُحَمَّد عَبْدُ الرَّحْمَن
  print(en.split("محمدأحمدعليحسن"));    // [محمد, أحمد, علي, حسن]
}

6. Java / Kotlin #

<dependency>
    <groupId>io.github.abdullahafifykhalil</groupId>
    <artifactId>egy-names</artifactId>
    <version>0.3.2</version>
</dependency>

import com.afify.egynames.EgyptianNames;

public class Main {
    public static void main(String[] args) {
        EgyptianNames en = new EgyptianNames();
        System.out.println(en.dallaa("محمد", "tashkeel")); // [مِيدُو, حَمُّو, حَمُّودَة]
        System.out.println(en.famousFigures("محمد", "en"));
        System.out.println(en.translate("محمد أحمد علي")); // Mohamed Ahmed Ali
        System.out.println(en.tashkeel("محمد عبدالرحمن")); // مُحَمَّد عَبْدُ الرَّحْمَن
    }
}

7. Modern C++ (C++20 / C++17) #

include(FetchContent)
FetchContent_Declare(
    egy_names
    GIT_REPOSITORY https://github.com/AbdullahAfifyKhalil/egy-names.git
    GIT_TAG v0.3.2
    SOURCE_SUBDIR cpp/egy_names
)
FetchContent_MakeAvailable(egy_names)
target_link_libraries(your_target PRIVATE egy_names)

#include <egy_names/egy_names.hpp>
#include <iostream>

int main() {
    egy_names::EgyptianNames en;
    std::cout << en.translate("محمد أحمد علي") << "\n"; // Mohamed Ahmed Ali
    std::cout << en.tashkeel("محمد عبدالرحمن") << "\n"; // مُحَمَّد عَبْدُ الرَّحْمَن
    auto dallaa = en.dallaa("محمد", "tashkeel");
    for (const auto& d : dallaa) std::cout << d << " ";
    std::cout << "\n";
    return 0;
}

Hugging Face Datasets #

The underlying national datasets are open-source and hosted on Hugging Face:

1. Egyptian Names Dataset (44.6K Lexicon and 15.88M Corpus) #

https://huggingface.co/datasets/Abdullah-afify/egyptian-names

final_canonical (Default): 44,626 unique master names with 100% Tashkeel, Arabic/English meanings, and 6-slot generational probabilities.
phase0_raw: 1.54M raw full name strings.
phase1_segmented: 1.0M segmented patronymic chains.
phase3_corrections: 23,457 orthographic correction rules.

from datasets import load_dataset

dataset = load_dataset("Abdullah-afify/egyptian-names")
print(dataset["train"][0])

2. Egyptian High School Students Degrees Dataset (2017–2026) #

https://huggingface.co/datasets/Abdullah-afify/egyptian-high-school-students-grades

3,790,225 Total Records across 5 national examination cohorts (2017, 2023, 2024, 2025, 2026).

Onomastic Architecture #

1. Patronymic Lineage Decomposition #

The position of a name within an Egyptian patronymic chain defines its legal and social role:

Position	Formal Role	Arabic Designation	Generational Context
Slot 1	Personal Given Name	اسم الشخص الأول	Individual identity (Male or Female)
Slot 2	Father's Name	اسم الأب	Direct paternal lineage (Male only)
Slot 3	Grandfather's Name	اسم الجد	Paternal grandfather (Male only)
Slot 4	Great-Grandfather	اسم سلف العائلة	Ancestral patriarch (Male only)
Slot 5	Family Surname / Clan	اللقب والعائلة	Tribal, geographic toponym, or guild surname

2. Concatenated Dynamic Programming Segmentation #

When processing unspaced Arabic text (محمدأحمدعليحسنالشناوي), the library executes a shortest-path dynamic programming algorithm over Unicode codepoints:

$$\text{Cost}(i) = \min_{j < i} \Big( \text{Cost}(j) + \text{BaseCost} + \text{Bonus}(\text{Freq}{j..i}) + \lambda \cdot \text{Length}{j..i} \Big)$$

About Afify Corporation #

Afify Corporation is a technology and intelligence enterprise innovating across software architecture, language engineering, and high-performance machine systems.

Website: afify.co
GitHub: @AbdullahAfifyKhalil
Founder and Lead Architect: Abdullah Afify

License and Citation #

Distributed under the MIT License. See LICENSE for details.

@software{afify2026egynames,
  author       = {Abdullah Afify},
  title        = {egy-names: A Production-Grade Onomastic Intelligence and Linguistic Engine for Egyptian Names},
  year         = {2026},
  publisher    = {GitHub},
  version      = {0.3.2},
  url          = {https://github.com/AbdullahAfifyKhalil/egy-names}
}

_{Developed by Abdullah Afify • Backed by Afify Corporation (afify.co)}