pipebio
A PipeBio client package
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained (released 1 day ago), has low install friction, no known vulnerabilities, and permissive licensing. Install it if you need to integrate PipeBio's biologics discovery platform into Python workflows. The main prerequisite is obtaining a PipeBio API key and running Python 3.10+.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires PIPE_API_KEY environment variable set (obtain from https://app.pipebio.com/AbLabs/me); Python 3.10 or later.
- Low friction install with a pure-wheel distribution.
- Actively maintained with a release 1 day old.
License · maintenance · safety
BSD 3-clause (permissive) — BSD 3-clause is permissive; you can use this package in commercial and proprietary projects with minimal restrictions, provided you include the license notice.
last release 2026-08-13 (1 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 118,961 downloads/mo, #12,096 on PyPI
Alternatives
Verify before relying
pip install pipebio
from pipebio.pipebio_client import PipebioClient
client = PipebioClient(url='https://app.pipebio.com')
response = client.session.get(url='me')
print(response.json())- Whether the SDK covers all endpoints you need or if you'll need to extend it with raw session calls.
- Performance characteristics when handling large NGS or single-cell datasets.
- Whether the llms.txt reference files are sufficient for your AI coding assistant use case.
What it is and what it does
PipeBio is a Python SDK for connecting to PipeBio's cloud-based biologics discovery platform. It provides a client interface to configure and run bioinformatics workflows for antibody and peptide analysis, including sequence analysis, engineering, and NGS/Sanger/PacBio data processing. The SDK wraps HTTP requests to the PipeBio API and includes authentication via API key, with support for loading credentials from environment variables or .env files.
The package is built on standard Python data and HTTP libraries (pandas, requests, biopython, openpyxl, pyarrow) and is designed for both wet lab scientists running standard workflows and bioinformaticians deploying custom code. It ships machine-readable reference files (llms.txt) for AI coding assistants and allows direct session access for unsupported endpoints.
Use it for
- Automate antibody sequence analysis and discovery workflows on the PipeBio platform from Python scripts.
- Integrate NGS, Sanger, PacBio, or single-cell sequence data into bioinformatics pipelines.
- Deploy custom bioinformatics code to PipeBio and trigger workflows programmatically.
- Build SOPs and standard analysis workflows for antibody engineering and peptide discovery.
- Extend the SDK with raw HTTP requests when a specific endpoint is not yet wrapped by the client.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained (released 1 day ago), has low install friction, no known vulnerabilities, and permissive licensing. Install it if you need to integrate PipeBio's biologics discovery platform into Python workflows. The main prerequisite is obtaining a PipeBio API key and running Python 3.10+.
Install
pipebio on PyPI
Before you install
Low friction install with a pure-wheel distribution. Actively maintained with a release 1 day old. Depends on common data and HTTP libraries (pandas, requests, biopython) with no compiled dependencies.
Requires PIPE_API_KEY environment variable set (obtain from https://app.pipebio.com/AbLabs/me); Python 3.10 or later.
License in practice
BSD 3-clause is permissive; you can use this package in commercial and proprietary projects with minimal restrictions, provided you include the license notice.
Quickstart
pip install pipebio
from pipebio.pipebio_client import PipebioClient
client = PipebioClient(url='https://app.pipebio.com')
response = client.session.get(url='me')
print(response.json())Verify before relying
- Whether the SDK covers all endpoints you need or if you'll need to extend it with raw session calls.
- Performance characteristics when handling large NGS or single-cell datasets.
- Whether the llms.txt reference files are sufficient for your AI coding assistant use case.
Package facts
| License | BSD 3-clause permissive |
| Python support | Supports the current Python release <3.14,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesrequestsurllib3pandasbiopythonpython-dotenvrequests-toolbeltopenpyxlpyarrow |
| Maintenance | Actively maintained 1 days since the last release |
| First released | |
| Downloads | 118,961 / month, #12,096 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: BSD LicenseOperating System :: MacOS :: MacOS XOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: pipebio-5.6.0-py3-none-any.whl
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