Generate basic GEDCOM files using genealogy data in a relational PostgreSQL database
A configurable Python-based GEDCOM file generator that creates Lineage-Linked GEDCOM-compliant (v5.5) genealogy data files from a relational PostgreSQL database. At this point in time, only FAM (Family) and INDI (Individual) record types are supported.
After defining your configuration file (see below) simply run init.py. This utility is purposefully designed not to require interactive user inputs so that it can be executed as part of automated pipelines. For example, you could deploy this to an Azure Function App / AWS Lambda and run it on a schedule to maintain an up-to-date GEDCOM representation of your database.
Define a config.ini file with the following information:
[DATABASE]
HOST=xxxx
PORT=5432
NAME=app
USERNAME=xxxx
PASSWORD=xxxx
[OPTIONS]
NAME=Family Tree
VERSION=0.1.0
OUTPUT_PATH=./
OUTPUT_MODE=ADVANCED
GROUPS=["Smith","Turner"]
ENFORCE_REFERENTIAL_INTEGRITY=True
FORCE_FULL_DATES=True
SOURCE_DATE_FORMAT=%%Y
#OUTPUT_MODE can be set as 'SIMPLE' or 'ADVANCED'. 'SIMPLE' will output a single GEDCOM file with all records. 'ADVANCED' will output a separate GEDCOM file for each item in 'GROUPS', based on the values in 'GROUP_COLUMN'
#GROUPS only required if OUTPUT_MODE is 'ADVANCED'
#In 'ADVANCED' mode, if ENFORCE_REFERENTIAL_INTEGRITY is enabled, any individuals referenced in FAM records from other groups will also be included as INDI records to avoid a cross-referencing integrity issue.
#If FORCE_FULL_DATES is enabled, any partial dates that can be successfully parsed will be transformed into a 01 JAN 1901 format.
[INDIVIDUALS]
TABLE_NAME=persons
ID_COLUMN=id
FIRSTNAME_COLUMN=first_name
LASTNAME_COLUMN=last_name
SEX_COLUMN=gender
SEX_MALE_VALUE=m
SEX_FEMALE_VALUE=f
BIRTHDATE_COLUMN=year_birth
DEATHDATE_COLUMN=year_death
GROUP_COLUMN=family_group
#GROUP_COLUMN required if OUTPUT_MODE is 'ADVANCED'
[SPOUSES]
TABLE_NAME=spouses
INDIVIDUAL1_COLUMN=first_person_id
INDIVIDUAL2_COLUMN=second_person_id
[PARENTS]
TABLE_NAME=persons
INDIVIDUALID_COLUMN=id
MOTHERID_COLUMN=mother_id
FATHERID_COLUMN=father_id