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Read and write the original Schichtplaner5 FoxPro .DBF database files, plus the SQLite/PostgreSQL ORM and sync layer used by OpenSchichtplaner5.

Project description

libopenschichtplaner5

CI PyPI ghcr.io GitHub release License: MIT

The core library behind OpenSchichtplaner5 — a pip-installable package that reads and writes the original Schichtplaner5 FoxPro/dBASE .DBF database files, so an open replacement can run on the exact same data as the proprietary Windows tool, with no migration.

Import name: the distribution is libopenschichtplaner5, but the importable package keeps its historical name sp5lib (like pip install PyYAMLimport yaml). This keeps OpenSchichtplaner5's imports unchanged after the extraction.

📚 Full documentation lives in the project wiki — DBF format notes, calculation features, the ORM guide and development setup. For a quick start see Installation and the CLI below; the in-repo module map is in docs/architecture.md.

What's inside

Module Purpose
sp5lib.dbf_reader Pure-Python DBF reader (UTF-16-LE detection, date parsing, field decode)
sp5lib.dbf_writer Safe DBF writer — exclusive flock, TOCTOU-safe record count, rollback, EOF marker preservation; interop with a running original client via the -L change journal and CDX invalidation (stale .CDX of a modified table is deleted so the original rebuilds it)
sp5lib.calculations Central, side-effect-free calculation layer implementing the original's rules (spec chapter 3): nominal/actual hours, absence crediting, leave accounts, surcharges, demand/utilization
sp5lib.database High-level SP5Database facade over the DBF tables (employees, shifts, schedule, absences, statistics via sp5lib.calculations, auth, 2FA …)
sp5lib.db_factory / sqlite_adapter / pg_database Optional SQLite / PostgreSQL backends; pg_database shares the calculation layer with the DBF facade (equivalence-tested)
sp5lib.orm SQLAlchemy models (models.py SQLite, models_pg.py Postgres), repository, sync
sp5lib.auto_migrate Alembic-based automatic migrations
sp5lib.email_service SMTP notification emails (HTML-escaped templates)
sp5lib.color_utils FoxPro BGR ↔ hex/RGB color helpers

See docs/architecture.md for the full module map and wiring.

Installation

Releases are published to PyPI:

pip install libopenschichtplaner5
# with the optional PostgreSQL backend:
pip install "libopenschichtplaner5[postgres]"

For the latest development state straight from Git:

pip install "libopenschichtplaner5 @ git+https://github.com/mschabhuettl/libopenschichtplaner5.git"

Usage

from sp5lib.database import SP5Database

db = SP5Database("/path/to/SP5/Daten")        # directory of .DBF files
for emp in db.get_employees():
    print(emp["ID"], emp["NAME"], emp["FIRSTNAME"])

Low-level DBF access:

from sp5lib.dbf_reader import read_dbf
from sp5lib.dbf_writer import append_record, get_table_fields

rows   = read_dbf("/path/to/SP5/Daten/5EMPL.DBF")
fields = get_table_fields("/path/to/SP5/Daten/5EMPL.DBF")
append_record("/path/to/SP5/Daten/5NOTE.DBF", fields, {"ID": 1, "TEXT": "hello"})

CLI & Docker

The package installs an sp5lib command for standalone work on a Schichtplaner5 database directory (the folder containing the 5*.DBF files):

sp5lib info     /path/to/SP5/Daten                  # table overview: records per table, SP5 build
sp5lib dump     /path/to/SP5/Daten 5EMPL --limit 5  # table contents as JSON (default) or --csv
sp5lib validate /path/to/SP5/Daten                  # read all tables, report errors/encoding issues
sp5lib sync     /path/to/SP5/Daten --target sqlite:/tmp/sp5.db        # DBF → SQLite
sp5lib sync     /path/to/SP5/Daten --target postgres://user:pw@host/db  # DBF → PostgreSQL

The same CLI is the default stage of the Dockerfile (slim, non-root, ENTRYPOINT ["sp5lib"]) — no local Python required. Each release publishes a multi-arch image to the GitHub Container Registry, so no local build is needed:

# published image (multi-arch amd64+arm64, no build required):
docker run --rm -v /path/to/SP5/Daten:/data:ro \
  ghcr.io/mschabhuettl/libopenschichtplaner5:latest info /data   # or :1.12.0

# or build it locally:
docker build -t libopenschichtplaner5 .
docker run --rm -v /path/to/SP5/Daten:/data:ro libopenschichtplaner5 info /data
docker run --rm -v /path/to/SP5/Daten:/data:ro libopenschichtplaner5 dump /data 5EMPL --limit 5
docker run --rm -v /path/to/SP5/Daten:/data -v "$PWD":/out \
  libopenschichtplaner5 sync /data --target sqlite:/out/sp5.db

# or via compose (service "tools"):
SP5_DB_DIR=/path/to/SP5/Daten docker compose run --rm tools info /data

Dependencies

Runtime: SQLAlchemy, alembic, bcrypt, pyotp, packaging. Optional: psycopg2-binary (via the postgres extra) for the PostgreSQL backend.

Development

python -m venv .venv && . .venv/bin/activate
pip install -e ".[dev,postgres]"
pytest
ruff check .

Optional golden regression suite against the original Schichtplaner 5 sample database (local reference material, never committed):

SP5_GOLDEN_DB=/path/to/sp5/Daten pytest tests/test_golden_sample_db.py -v

Docker (Build-/Test-Stage)

Stage test of the Dockerfile provides a reproducible lint + test environment (python:3.12-slim, runs ruff check . and pytest):

docker compose run --rm test
# equivalent: docker build --target test -t libopenschichtplaner5:test . && docker run --rm libopenschichtplaner5:test

License

MIT — see LICENSE. Extracted (with full git history) from OpenSchichtplaner5's backend/sp5lib/.

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