dacite
Simple creation of data classes from dictionaries.
Decision gist · record as of 2026-08-14
Yes, if you use dataclasses and frequently convert dictionaries to typed objects. The library is stable (Production/Stable status), has no known vulnerabilities, and installs with minimal friction. The aging maintenance status (555 days since last release) is a minor concern for a mature, narrow-purpose tool—monitor the repository if you depend on new features, but the core functionality is unlikely to break. Pair it with a validation library if you need to check data before conversion.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.7 or later; dataclasses are built-in to the standard library from Python 3.7 onward.
- Low friction installation with a single pure-Python dependency (dataclasses).
- Maintenance status is aging—last release was 555 days ago, though the repository remains active with a recent commit on 2025-03-17 and 2041 stars.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.
last release 2025-02-05 (555 days) · last repo commit 2025-03-17 · 2,041 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 23,712,751 downloads/mo, #935 on PyPI
Alternatives
Verify before relying
from dataclasses import dataclass
from dacite import from_dict
@dataclass
class User:
name: str
age: int
data = {'name': 'John', 'age': 30}
user = from_dict(data_class=User, data=data)- Performance characteristics when handling very large or deeply nested structures.
- Compatibility with third-party type annotation libraries beyond the standard typing module.
What it is and what it does
Dacite is a lightweight library that bridges the gap between plain dictionaries and Python dataclasses. It takes a dictionary and a dataclass type, then instantiates the dataclass with the dictionary's values, handling type conversions and nested structures automatically. The library was designed to simplify creation of type-hinted data transfer objects (DTOs) that cross application boundaries—for example, converting JSON payloads from HTTP requests or database rows into strongly-typed Python objects.
The core function is `from_dict`, which accepts a dataclass type, input dictionary, and optional configuration. It supports nested dataclasses, optional fields, union types, generic dataclasses, type hooks for custom transformations, casting for enum-like conversions, and strict mode to reject unexpected keys. The library explicitly does not validate data; it assumes input is already valid or will be validated separately.
Use it for
- Convert JSON request payloads into dataclass instances for HTTP API handlers.
- Transform database query results (as dictionaries) into typed domain objects.
- Build type-safe configuration objects from YAML or JSON config files.
- Deserialize nested API responses into hierarchical dataclass structures.
- Create DTOs for inter-service communication with automatic type coercion.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you use dataclasses and frequently convert dictionaries to typed objects.
The library is stable (Production/Stable status), has no known vulnerabilities, and installs with minimal friction. The aging maintenance status (555 days since last release) is a minor concern for a mature, narrow-purpose tool—monitor the repository if you depend on new features, but the core functionality is unlikely to break. Pair it with a validation library if you need to check data before conversion.
Install
dacite on PyPI
Before you install
Low friction installation with a single pure-Python dependency (dataclasses). Maintenance status is aging—last release was 555 days ago, though the repository remains active with a recent commit on 2025-03-17 and 2041 stars.
Requires Python 3.7 or later; dataclasses are built-in to the standard library from Python 3.7 onward.
License in practice
MIT license (permissive) places no restrictions on use, modification, or distribution in proprietary or open-source projects.
Quickstart
from dataclasses import dataclass
from dacite import from_dict
@dataclass
class User:
name: str
age: int
data = {'name': 'John', 'age': 30}
user = from_dict(data_class=User, data=data)Verify before relying
- Performance characteristics when handling very large or deeply nested structures.
- Compatibility with third-party type annotation libraries beyond the standard typing module.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagedataclasses |
| Maintenance | Aging 555 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 23,712,751 / month, #935 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules |
Evidence: dacite-1.9.2-py3-none-any.whl
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See also class-resolver · typed-json-dataclass · databind · dataclasses · databind.json · dataclass-wizard · databind.core · dataclasses-json · dataclasses-json-speakeasy · dataclass-csv