exonware-xwquery 0.9.0.14

Universal query language for data structures - 50+ operations, 35+ format converters

xwquery

Company: eXonware.com
Author: eXonware Backend Team
Email: [e-mail]

Query and transform native Python data structures with one API: SQL-style scripts, graph patterns, aggregations, and 35+ alternate surface syntaxes (Cypher, GraphQL, JMESPath, and others). It works directly with dictionaries, lists, and mixed in-memory structures; xwnode, xwdata, and xwentity integrations are optional add-ons when you want deeper stack features.

📦 Install

pip install exonware-xwquery
pip install exonware-xwquery[lazy]
pip install exonware-xwquery[full]

🚀 Basic usage

from exonware.xwquery import XWQuery

data = {'users': [
    {'name': 'Alice', 'age': 30, 'city': 'NYC'},
    {'name': 'Bob', 'age': 25, 'city': 'LA'},
    {'name': 'Charlie', 'age': 35, 'city': 'NYC'}
]}

result = XWQuery.execute("""
    SELECT name, age
    FROM users
    WHERE age > 25 AND city = 'NYC'
""", data)

print(result)
# [{'name': 'Alice', 'age': 30}, {'name': 'Charlie', 'age': 35}]

✨ What you get

• Broad operation set - Core CRUD (SELECT, INSERT, UPDATE, DELETE, CREATE, ALTER, DROP), filtering (WHERE, FILTER, LIKE, IN, RANGE, …), aggregation (GROUP BY, HAVING, SUM, COUNT, …), graph helpers (MATCH, PATH, …), and advanced pieces (JOIN, UNION, WITH, WINDOW, PIPE, …).
• Many input languages - Strategies for SQL-family dialects, Cypher/Gremlin/SPARQL/GraphQL, document and log query languages (MQL, Elasticsearch DSL, PromQL, Flux, …), and more. Parse or convert between them where supported.
• Structure-aware execution - The engine can adapt work to linear, tree, graph, or hybrid shapes when the backend exposes that metadata.

linear_data = [1, 2, 3, 4, 5]
tree_data = {'a': 1, 'b': 2, 'c': 3}
graph_data = {'nodes': [...], 'edges': [...]}

XWQuery.execute("SELECT * WHERE value > 2", linear_data)
XWQuery.execute("SELECT * WHERE key BETWEEN 'a' AND 'c'", tree_data)
XWQuery.execute("MATCH (n)-[r]->(m)", graph_data)

📄 Script examples

SELECT name, email, age FROM users WHERE age >= 18;

SELECT department, COUNT(*) AS employee_count, AVG(salary) AS avg_salary
FROM employees
GROUP BY department
HAVING avg_salary > 50000;

MATCH (u:User)-[:FRIENDS_WITH]->(f:User)
WHERE u.age > 25
RETURN u.name, f.name;

🔄 Format conversion

sql_query = "SELECT id, name FROM users WHERE age > 25"
graphql = XWQuery.convert(sql_query, from_format='sql', to_format='graphql')

cypher_query = "MATCH (u:User)-[:WORKS_AT]->(c:Company) RETURN u.name, c.name"
sql = XWQuery.convert(cypher_query, from_format='cypher', to_format='sql')

any_query = XWQuery.parse(query_string)
target_format = any_query.to_format('mongodb')

🔗 Stack integration

xwnode

from exonware.xwnode import XWNode
from exonware.xwquery import XWQuery

node = XWNode.from_native({'users': [...]})
result = XWQuery.execute("SELECT * FROM users WHERE active = true", node)

xwdata

from exonware.xwdata import XWData
from exonware.xwquery import XWQuery

data = XWData.load('users.json')
filtered = XWQuery.execute("SELECT * WHERE age > 18", data)
filtered.save('adults.xml')

xwentity

from exonware.xwentity import XWEntity
from exonware.xwquery import XWQuery

class User(XWEntity):
    name: str
    age: int
    email: str

users = XWQuery.execute("SELECT * FROM User WHERE age > 18")

🌐 Ecosystem functional contributions

xwquery provides query execution; sibling XW libraries provide data shapes, domain contracts, and persistence targets that those queries operate on. You can use xwquery standalone over native Python data structures without the full XW stack. Broader XW integration is optional and mainly intended for enterprise and mission-critical query infrastructure where unified storage/schema/domain contracts are required.

Supporting XW lib	What it provides to xwquery workflows	Functional requirement it satisfies
XWNode	Graph/tree/list strategy abstractions and structural metadata.	Shape-aware execution planning across linear, tree, and graph data.
XWData	Multi-format data ingestion/export around query execution.	Querying heterogeneous input/output formats with one pipeline.
XWEntity	Entity/domain model surfaces that can be queried directly.	Domain-level querying rather than raw structure-only filtering.
XWStorage	Backend persistence/query integration for stored datasets.	Query execution against durable data, not only in-memory objects.
XWSchema	Optional schema validation before/after query transformations.	Safer transformations and contract compliance in pipelines.
XWSystem	Shared runtime and utility infrastructure used by parsers/executors.	Consistent execution behavior and lower operational duplication.

Competitive edge: xwquery unifies many query syntaxes while remaining tightly connected to structure, schema, and storage layers in the same ecosystem.

📖 Docs

• docs/INDEX.md - full map
• docs/GUIDE_01_USAGE.md - usage
• docs/REF_15_API.md - API
• docs/REF_13_ARCH.md - architecture
• docs/PROJECT_PHASES.md - phases and roadmap
• docs/REF_51_TEST.md - tests

🛠️ Development

pip install -e .
python tests/runner.py
python tests/runner.py --core
python tests/runner.py --unit
python tests/runner.py --integration

📜 License

Apache-2.0 - see LICENSE.

🌐 Ecosystem

• xwsystem
• xwnode
• xwquery (this repo)
• xwdata
• xwschema
• xwaction
• xwentity
• xwstorage
• xwbase

⏱️ Async Support

• xwquery includes asynchronous execution paths in production code.
• Source validation: 50 async def definitions and 24 await usages under src/.
• Use async APIs for I/O-heavy or concurrent workloads to improve throughput and responsiveness.

Version: 0.9.0.14 | Updated: 11-Apr-2026

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