Migration tooling from Google App Engine (webapp2, ndb) to python-cdd supported (FastAPI, SQLalchemy).
Project description
cdd-python-gae
Migration tooling from Google App Engine (webapp2, ndb) to python-cdd supported (FastAPI, SQLalchemy).
Public SDK works with filenames, source code, and even in memory constructs (e.g., as imported into your REPL). CLI available also.
Install package
PyPi
pip install python-cdd-gae
Master
pip install -r https://raw.githubusercontent.com/offscale/cdd-python-gae/master/requirements.txt
pip install https://api.github.com/repos/offscale/cdd-python-gae/zipball#egg=cdd
Goal
Migrate from Google App Engine to cloud-independent runtime (e.g., vanilla CPython 3.11 with SQLite).
Relation to other projects
This was created independent of cdd-python
project for two reasons:
- Unidirectional;
- Relevant to fewer people.
SDK
Approach
Traverse the AST for ndb and webapp2.
Advantages
Disadvantages
Alternatives
Minor other use-cases this facilitates
CLI for this project
$ python -m cdd_gae --help
usage: python -m cdd_gae [-h] [--version]
{ndb2sqlalchemy,ndb2sqlalchemy_migrator,webapp2_to_fastapi}
...
Migration tooling from Google App Engine (webapp2, ndb) to python-cdd
supported (FastAPI, SQLalchemy).
positional arguments:
{ndb2sqlalchemy,ndb2sqlalchemy_migrator,webapp2_to_fastapi}
ndb2sqlalchemy Parse NDB emit SQLalchemy
ndb2sqlalchemy_migrator
Create migration scripts from NDB to SQLalchemy
webapp2_to_fastapi Parse WebApp2 emit FastAPI
optional arguments:
-h, --help show this help message and exit
--version show program's version number and exit
ndb2sqlalchemy
(webapp2_to_fastapi
takes same args)
$ python -m cdd_gae ndb2sqlalchemy --help
usage: python -m cdd_gae ndb2sqlalchemy [-h] -i INPUT_FILE -o OUTPUT_FILE
[--dry-run]
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input-file INPUT_FILE
Python file to parse NDB `class`es out of
-o OUTPUT_FILE, --output-file OUTPUT_FILE
Empty file to generate SQLalchemy classes to
--dry-run Show what would be created; don't actually write to
the filesystem.
webapp2_to_fastapi
(ndb2sqlalchemy
takes same args)
$ python -m cdd_gae webapp2_to_fastapi --help
usage: python -m cdd_gae webapp2_to_fastapi [-h] -i INPUT_FILE -o OUTPUT_FILE
[--dry-run]
options:
-h, --help show this help message and exit
-i INPUT_FILE, --input-file INPUT_FILE
Python file to parse WebApp2 `class`es out of
-o OUTPUT_FILE, --output-file OUTPUT_FILE
Empty file to generate FastAPI functions to
--dry-run Show what would be created; don't actually write to
the filesystem.
python -m cdd_gae ndb2sqlalchemy_migrator --help
$ ndb2sqlalchemy_migrator
usage: python -m cdd_gae ndb2sqlalchemy_migrator [-h] --ndb-file NDB_FILE
--sqlalchemy-file
SQLALCHEMY_FILE
--ndb-mod-to-import
NDB_MOD_TO_IMPORT
--sqlalchemy-mod-to-import
SQLALCHEMY_MOD_TO_IMPORT -o
OUTPUT_FOLDER [--dry-run]
optional arguments:
-h, --help show this help message and exit
--ndb-file NDB_FILE Python file containing the NDB `class`es
--sqlalchemy-file SQLALCHEMY_FILE
Python file containing the NDB `class`es
--ndb-mod-to-import NDB_MOD_TO_IMPORT
NDB module name that the entity will be imported from
--sqlalchemy-mod-to-import SQLALCHEMY_MOD_TO_IMPORT
SQLalchemy module name that the entity will be
imported from
-o OUTPUT_FOLDER, --output-folder OUTPUT_FOLDER
Empty folder to generate scripts that migrate from one
NDB class to one SQLalchemy class
--dry-run Show what would be created; don't actually write to
the filesystem.
Data migration
The most efficient way seems to be:
- Backup from NDB to Google Cloud Storage
- Import from Google Cloud Storage to Google BigQuery
- Export from Google BigQuery to Apache Parquet files in Google Cloud Storage
- Download and parse the Parquet files, then insert into SQL
(for the following scripts set GOOGLE_PROJECT_ID
, GOOGLE_BUCKET_NAME
, NAMESPACE
, GOOGLE_LOCATION
)
Backup from NDB to Google Cloud Storage
for entity in kind0 kind1; do
gcloud datastore export 'gs://'"$GOOGLE_BUCKET_NAME" --project "$GOOGLE_PROJECT_ID" --kinds "$entity" --async &
done
Import from Google Cloud Storage to Google BigQuery
printf 'bq mk "%s"\n' "$NAMESPACE" > migrate.bash
gsutil ls 'gs://'"$GOOGLE_BUCKET_NAME"'/**/all_namespaces/kind_*' | python3 -c 'import sys, posixpath, fileinput; f=fileinput.input(encoding="utf-8"); d=dict(map(lambda e: (posixpath.basename(posixpath.dirname(e)), posixpath.dirname(e)), sorted(f))); f.close(); print("\n".join(map(lambda k: "( bq mk \"'"$NAMESPACE"'.{k}\" && bq --location='"$GOOGLE_LOCATION"' load --source_format=DATASTORE_BACKUP \"'"$NAMESPACE"'.{k}\" \"{v}/all_namespaces_{k}.export_metadata\" ) &".format(k=k, v=d[k]), sorted(d.keys()))),sep="");' >> migrate.bash
# Then run `bash migrate.bash`
Export from Google BigQuery to Apache Parquet files in Google Cloud Storage
for entity in kind0 kind1; do
bq extract --location="$GOOGLE_LOCATION" --destination_format='PARQUET' "$NAMESPACE"'.kind_'"$entity" 'gs://'"$GOOGLE_BUCKET_NAME"'/'"$entity"'/*' &
done
License
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or https://opensource.org/licenses/MIT)
at your option.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
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