date-spacy
A spaCy extension for enhanced date and number entity recognition and extraction as structured data.
Decision gist · record as of 2026-08-14
Yes, if your date extraction needs are simple and stable. The package is low-friction to install and has no known vulnerabilities. However, it is abandoned (last updated 2023-08-24) with no ongoing maintenance, so install only if the fixed functionality is sufficient and you do not expect bug fixes or compatibility updates with future spacy or dateparser versions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires spacy and dateparser to be installed; assumes current year if no year is provided in the date text.
- Low friction install with only two runtime dependencies (spacy and dateparser).
- However, the package is abandoned—last release was 2023-08-24 with no updates since, and the repository shows no recent activity.
License · maintenance · safety
permissive license (permissive) — Licensed under MIT (permissive), so you can use, modify, and distribute the package freely with minimal restrictions.
last release 2023-08-24 (1086 days) · last repo commit 2023-08-24 · 22 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 89,185 downloads/mo, #13,675 on PyPI
Alternatives
Verify before relying
pip install date-spacy
import spacy
from date_spacy import find_dates
nlp = spacy.blank('en')
nlp.add_pipe('find_dates')
doc = nlp("Meeting on 25th August 2023")
for ent in doc.ents:
if ent.label_ == "DATE":
print(ent._.date)- Whether the regex-based approach handles all date formats you need (e.g., ISO, locale-specific, ambiguous formats).
- Compatibility with recent spacy versions (package last released 2023-08-24).
- Performance characteristics on large document volumes or complex date patterns.
What it is and what it does
Date spaCy is a lightweight spaCy pipeline component that finds date expressions in text and converts them to structured datetime objects. It works by applying regex patterns to locate date strings, then passes them to dateparser for parsing into standardized datetime format. The parsed result is attached to each matched entity via a custom `._.date` extension, making it accessible during spaCy's standard entity iteration.
The component is designed to integrate into existing spaCy pipelines (ideally before the NER model) or to run on a blank model. Its main limitation is that dates without an explicit year default to the current year. Since the package is abandoned with no releases after August 2023, it is best suited for projects with stable, unchanging requirements and no expectation of upstream maintenance.
Use it for
- Extract and normalize dates from unstructured text in documents or emails for downstream processing.
- Build a temporal information extraction pipeline as part of a larger spaCy NLP workflow.
- Convert informal date expressions (e.g., 'twelfth of October') into machine-readable datetime objects for database storage.
- Augment spaCy's default entity recognition with specialized date handling before applying other NER models.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if your date extraction needs are simple and stable.
The package is low-friction to install and has no known vulnerabilities. However, it is abandoned (last updated 2023-08-24) with no ongoing maintenance, so install only if the fixed functionality is sufficient and you do not expect bug fixes or compatibility updates with future spacy or dateparser versions.
Install
date-spacy on PyPI
Before you install
Low friction install with only two runtime dependencies (spacy and dateparser). However, the package is abandoned—last release was 2023-08-24 with no updates since, and the repository shows no recent activity. Use only if the fixed functionality meets your needs without expecting maintenance or bug fixes.
Requires spacy and dateparser to be installed; assumes current year if no year is provided in the date text.
License in practice
Licensed under MIT (permissive), so you can use, modify, and distribute the package freely with minimal restrictions.
Quickstart
pip install date-spacy
import spacy
from date_spacy import find_dates
nlp = spacy.blank('en')
nlp.add_pipe('find_dates')
doc = nlp("Meeting on 25th August 2023")
for ent in doc.ents:
if ent.label_ == "DATE":
print(ent._.date)Verify before relying
- Whether the regex-based approach handles all date formats you need (e.g., ISO, locale-specific, ambiguous formats).
- Compatibility with recent spacy versions (package last released 2023-08-24).
- Performance characteristics on large document volumes or complex date patterns.
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesspacydateparser |
| Maintenance | Abandoned 1,086 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 89,185 / month, #13,675 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3 |
Evidence: date_spacy-0.0.1-py3-none-any.whl
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