scitex-dev 0.6.1

Shared developer utilities for the SciTeX ecosystem

SciTeX Dev (scitex-dev)

Shared developer utilities for the SciTeX ecosystem

Full Documentation · pip install scitex-dev

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Problem

The SciTeX ecosystem spans multiple packages (scitex-clew, scitex-writer, scitex-stats, figrecipe, etc.), each with their own documentation, versions, APIs, and CLI commands. Keeping them in sync, discovering what's available, and maintaining consistency across the ecosystem becomes increasingly difficult as it grows.

Solution

scitex-dev (v0.5.1) provides a unified toolkit for developing and maintaining the SciTeX ecosystem:

• Version management — detect and fix version mismatches across pyproject.toml, __init__.py, git tags, and PyPI
• CI/CD — check GitHub Actions status, wait for workflows, verify PyPI publish
• Deployment — deploy and verify production on remote hosts
• Skills — aggregate, export, and verify AI agent skill pages across the ecosystem
• Docs aggregation — discover, build, and search documentation across all packages
• LLM-friendly types — Result, ErrorCode, @supports_return_as for consistent structured responses

Zero runtime dependencies. Pure stdlib.

Installation

pip install scitex-dev

# With CLI support:
pip install scitex-dev[cli]

# With MCP server:
pip install scitex-dev[mcp]

# Everything:
pip install scitex-dev[all]

Modules

Module	Functions	Purpose
skills	list_skills, get_skill, export_skills, verify_docs_and_skills	AI agent skill discovery and export
fix	detect_mismatches, fix_local, fix_remote, fix_init_version, bump_version, determine_bump_type, verify_versions	Version mismatch detection and repair
ci	check_ci, get_failing_packages, verify_pypi_config, create_github_release, wait_for_workflow, check_pypi_publish	GitHub Actions and PyPI integration
deploy	deploy_scitex_cloud, verify_production	Remote host deployment
versions	get_commits_since_tag	Commit tracking since last release
_dist_info	clean_stale_dist_info	Internal: stale dist-info cleanup

Quick Start

from scitex_dev.fix import detect_mismatches, fix_local, verify_versions
from scitex_dev.ci import check_ci, get_failing_packages
from scitex_dev.skills import list_skills, export_skills

# Detect version mismatches across the ecosystem
mismatches = detect_mismatches()

# Fix mismatches locally (dry run by default)
fix_local(packages=["scitex-stats"], confirm=True)

# Check CI status
status = check_ci(packages=["scitex", "figrecipe"])
failing = get_failing_packages()

# List and export AI agent skills
skills = list_skills()
export_skills()

Four Interfaces

Python API

# Version management
from scitex_dev.fix import detect_mismatches, fix_local, fix_remote, verify_versions
mismatches = detect_mismatches()
fix_local(packages=["scitex-stats"], confirm=True)
verify_versions()

# CI/CD
from scitex_dev.ci import check_ci, get_failing_packages, check_pypi_publish
status = check_ci()
failing = get_failing_packages()

# Skills
from scitex_dev.skills import list_skills, get_skill, export_skills
skills = list_skills()
page = get_skill(package="scitex-stats")
export_skills()

# Deployment
from scitex_dev.deploy import deploy_scitex_cloud, verify_production
deploy_scitex_cloud(host="nas", confirm=True)

# Commit tracking
from scitex_dev.versions import get_commits_since_tag
commits = get_commits_since_tag("scitex-stats")

# LLM-friendly types
from scitex_dev import Result, supports_return_as

CLI Commands

# Ecosystem management
scitex-dev ecosystem list
scitex-dev ecosystem list --versions
scitex-dev ecosystem fix-mismatches --dry-run
scitex-dev ecosystem sync

# Documentation
scitex-dev docs --package scitex-writer
scitex-dev search "save figure"

# Bulk rename
scitex-dev rename old_name new_name --dry-run

# See all commands
scitex-dev --help
scitex-dev --help-recursive

MCP Server

# Start server
scitex-dev mcp start

# Check setup
scitex-dev mcp doctor
scitex-dev mcp list-tools

# Installation info
scitex-dev mcp installation

Claude Code Setup — add .mcp.json to your project root. Use SCITEX_DEV_ENV_SRC to load configuration from a .src file:

{
  "mcpServers": {
    "scitex-dev": {
      "command": "scitex-dev",
      "args": ["mcp", "start"],
      "env": {
        "SCITEX_DEV_ENV_SRC": "${SCITEX_DEV_ENV_SRC}"
      }
    }
  }
}

Switch environments via your shell profile:

# Local machine
export SCITEX_DEV_ENV_SRC=~/.scitex/dev/local.src

# Remote server
export SCITEX_DEV_ENV_SRC=~/.scitex/dev/remote.src

Skills — for AI Agent Discovery

Skills provide workflow-oriented guides that AI agents query to discover capabilities and usage patterns.

scitex-dev skills list              # List available skill pages
scitex-dev skills get SKILL         # Show main skill page
scitex-dev skills export --package scitex-dev  # Export to Claude Code

Skill	Content
result-types	Result, ErrorCode, @supports_return_as for LLM-friendly responses
cli-mcp-utils	CLI and MCP utility helpers
versions	Version management, mismatch detection and fixing
ecosystem	Ecosystem list, sync, and commit workflows
rename	Safe bulk rename with cross-reference updates
docs-search	Documentation aggregation and unified search
test-runner	Local and HPC test execution
config	Package configuration and priority config patterns

Part of SciTeX

scitex-dev is part of SciTeX. It provides the shared infrastructure that keeps the ecosystem consistent and discoverable. When used with the orchestrator package scitex, it enables unified version management, CI monitoring, and deployment across all modules:

from scitex_dev.fix import detect_mismatches, verify_versions
from scitex_dev.ci import check_ci, get_failing_packages

# See the entire ecosystem at a glance
mismatches = detect_mismatches()
verify_versions()

# Monitor CI across all packages
failing = get_failing_packages()

The SciTeX system follows the Four Freedoms for Research below, inspired by the Free Software Definition:

Four Freedoms for Research

0. The freedom to run your research anywhere — your machine, your terms.
1. The freedom to study how every step works — from raw data to final manuscript.
2. The freedom to redistribute your workflows, not just your papers.
3. The freedom to modify any module and share improvements with the community.

AGPL-3.0 — because we believe research infrastructure deserves the same freedoms as the software it runs on.

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