streamlit-faker
streamlit-faker is a library to very easily fake Streamlit commands
Decision gist · record as of 2026-08-14
Yes, if you are prototyping Streamlit UIs and want to skip manual fixture setup. The low install friction and active repository make it a lightweight addition. However, verify the license status and confirm that altex is a real dependency before committing to production use. The 409-day release cycle suggests infrequent updates, so expect to maintain a fork if you need urgent fixes.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.9 and a working Streamlit environment; run with `streamlit run <app>.py`.
- Low friction install with four runtime dependencies (streamlit, altex, faker, matplotlib).
- The package is aging—last release was 409 days ago—but the repository remains active and unarchived, suggesting maintenance is infrequent rather than abandoned.
License · maintenance · safety
(unclear) — License status is unclear; no SPDX identifier or raw license text is recorded. Before using in a commercial or copyleft-sensitive context, verify the actual license from the repository.
last release 2025-07-01 (409 days) · last repo commit 2025-07-01 · 26 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 263,077 downloads/mo, #8,363 on PyPI
Alternatives
Verify before relying
pip install streamlit-faker
from streamlit_faker import get_streamlit_faker
st_faker = get_streamlit_faker()
st_faker.subheader()
st_faker.slider()- Whether altex is a typo or a real dependency; it does not appear in standard package indexes.
- Scope of Streamlit commands supported (whether all commands or a subset are faked).
- Whether the package is maintained actively or in maintenance-only mode given the 409-day release gap.
What it is and what it does
streamlit-faker wraps Streamlit commands to execute them with randomly generated parameters, eliminating the need to manually provide arguments during UI drafting. It builds on the faker library to generate realistic placeholder data and integrates with Streamlit's widget ecosystem (text inputs, sliders, maps, etc.) to populate them automatically.
The package is designed for two main workflows: rapid UI prototyping when you want to see what a Streamlit app layout looks like without writing sample data, and QA testing to verify that your app handles a variety of input types and values. You call a Streamlit command (e.g., `st_faker.subheader()`) with no arguments, and the library executes the real Streamlit command with random data injected.
Use it for
- Quickly mock up a Streamlit dashboard layout without writing fixture data or sample inputs.
- Test how your Streamlit app renders with various widget types and random values during development.
- Generate placeholder content for UI reviews or demos before connecting real data sources.
- Verify that Streamlit commands handle edge cases and diverse input types without crashing.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are prototyping Streamlit UIs and want to skip manual fixture setup.
The low install friction and active repository make it a lightweight addition. However, verify the license status and confirm that altex is a real dependency before committing to production use. The 409-day release cycle suggests infrequent updates, so expect to maintain a fork if you need urgent fixes.
Install
streamlit-faker on PyPI
Before you install
Low friction install with four runtime dependencies (streamlit, altex, faker, matplotlib). The package is aging—last release was 409 days ago—but the repository remains active and unarchived, suggesting maintenance is infrequent rather than abandoned.
Requires Python >=3.9 and a working Streamlit environment; run with `streamlit run <app>.py`.
License in practice
License status is unclear; no SPDX identifier or raw license text is recorded. Before using in a commercial or copyleft-sensitive context, verify the actual license from the repository.
Quickstart
pip install streamlit-faker
from streamlit_faker import get_streamlit_faker
st_faker = get_streamlit_faker()
st_faker.subheader()
st_faker.slider()Verify before relying
- Whether altex is a typo or a real dependency; it does not appear in standard package indexes.
- Scope of Streamlit commands supported (whether all commands or a subset are faked).
- Whether the package is maintained actively or in maintenance-only mode given the 409-day release gap.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesstreamlitaltexfakermatplotlib |
| Maintenance | Aging 409 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 263,077 / month, #8,363 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: Python :: 3 |
Evidence: streamlit_faker-0.0.4-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “streamlit mock data generator”
- streamlit-fakerGenerates random fake data to populate Streamlit UI commands without…
- namesGenerates random human names (first, last, or full) with optional…
- polyfactoryPolyfactory generates mock data objects from type hints, supporting…
Give your agent the search over MCP, or paste the wish link into any chat.
More Testing packages
Pluggy provides a plugin system that lets you define hook specifications and register implementations to be called in sequence, enabling extensible Python applications without tight coupling.
Install it if you're building an extensible application or framework.
pytest is a testing framework that lets you write test functions using plain assert statements and automatically discovers and runs them, with detailed failure reporting.
virtualenv creates isolated Python environments where packages can be installed independently without affecting the system Python or other projects.
Coverage.py measures which lines of Python code are executed during test runs, reporting coverage percentages and identifying untested code paths.
Install it if you want to measure test completeness or enforce coverage thresholds in your project.
pytest-asyncio is a pytest plugin that enables writing and running async test functions using the asyncio library, allowing developers to await code directly within test cases.
Install it if you write tests for any asyncio-based code.
A pytest plugin that generates test reports in Common Test Report Format (CTRF) as JSON, compatible with pytest-xdist and pytest-playwright for distributed and browser-based testing.
Install it if you need CTRF-formatted test output for CI/CD integration or cross-tool reporting.
See also autofaker · Faker · robotframework-faker · fake-factory · faker-enum · pytest-faker · faker-e164 · snowfakery · essential-generators · names