superset/tests/integration_tests/csv_upload_tests.py

206 lines
6.7 KiB
Python

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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing,
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# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# isort:skip_file
"""Unit tests for Superset CSV upload"""
import json
import logging
import os
import shutil
from typing import Dict, Optional
from unittest import mock
import pandas as pd
import pytest
import superset.utils.database
from superset.sql_parse import Table
from superset import security_manager
from tests.integration_tests.conftest import ADMIN_SCHEMA_NAME
from tests.integration_tests.test_app import app # isort:skip
from superset import db
from superset.models.core import Database
from superset.utils import core as utils
from tests.integration_tests.base_tests import get_resp, login, SupersetTestCase
logger = logging.getLogger(__name__)
test_client = app.test_client()
CSV_UPLOAD_DATABASE = "csv_explore_db"
CSV_FILENAME1 = "testCSV1.csv"
CSV_FILENAME2 = "testCSV2.csv"
EXCEL_FILENAME = "testExcel.xlsx"
PARQUET_FILENAME1 = "testZip/testParquet1.parquet"
PARQUET_FILENAME2 = "testZip/testParquet2.parquet"
ZIP_DIRNAME = "testZip"
ZIP_FILENAME = "testZip.zip"
EXCEL_UPLOAD_TABLE = "excel_upload"
CSV_UPLOAD_TABLE = "csv_upload"
PARQUET_UPLOAD_TABLE = "parquet_upload"
CSV_UPLOAD_TABLE_W_SCHEMA = "csv_upload_w_schema"
CSV_UPLOAD_TABLE_W_EXPLORE = "csv_upload_w_explore"
@pytest.fixture(scope="module")
def setup_csv_upload():
with app.app_context():
login(test_client, username="admin")
upload_db = superset.utils.database.get_or_create_db(
CSV_UPLOAD_DATABASE, app.config["SQLALCHEMY_EXAMPLES_URI"]
)
extra = upload_db.get_extra()
extra["explore_database_id"] = superset.utils.database.get_example_database().id
upload_db.extra = json.dumps(extra)
upload_db.allow_file_upload = True
db.session.commit()
yield
upload_db = get_upload_db()
engine = upload_db.get_sqla_engine()
engine.execute(f"DROP TABLE IF EXISTS {EXCEL_UPLOAD_TABLE}")
engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE}")
engine.execute(f"DROP TABLE IF EXISTS {PARQUET_UPLOAD_TABLE}")
engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE_W_SCHEMA}")
engine.execute(f"DROP TABLE IF EXISTS {CSV_UPLOAD_TABLE_W_EXPLORE}")
db.session.delete(upload_db)
db.session.commit()
@pytest.fixture(scope="module")
def create_csv_files():
with open(CSV_FILENAME1, "w+") as test_file:
for line in ["a,b", "john,1", "paul,2"]:
test_file.write(f"{line}\n")
with open(CSV_FILENAME2, "w+") as test_file:
for line in ["b,c,d", "john,1,x", "paul,2,"]:
test_file.write(f"{line}\n")
yield
os.remove(CSV_FILENAME1)
os.remove(CSV_FILENAME2)
@pytest.fixture()
def create_excel_files():
pd.DataFrame({"a": ["john", "paul"], "b": [1, 2]}).to_excel(EXCEL_FILENAME)
yield
os.remove(EXCEL_FILENAME)
@pytest.fixture()
def create_columnar_files():
os.mkdir(ZIP_DIRNAME)
pd.DataFrame({"a": ["john", "paul"], "b": [1, 2]}).to_parquet(PARQUET_FILENAME1)
pd.DataFrame({"a": ["max", "bob"], "b": [3, 4]}).to_parquet(PARQUET_FILENAME2)
shutil.make_archive(ZIP_DIRNAME, "zip", ZIP_DIRNAME)
yield
os.remove(ZIP_FILENAME)
shutil.rmtree(ZIP_DIRNAME)
def get_upload_db():
return db.session.query(Database).filter_by(database_name=CSV_UPLOAD_DATABASE).one()
def upload_csv(filename: str, table_name: str, extra: Optional[Dict[str, str]] = None):
csv_upload_db_id = get_upload_db().id
schema = utils.get_example_default_schema()
form_data = {
"csv_file": open(filename, "rb"),
"sep": ",",
"name": table_name,
"con": csv_upload_db_id,
"if_exists": "fail",
"index_label": "test_label",
"mangle_dupe_cols": False,
}
if schema:
form_data["schema"] = schema
if extra:
form_data.update(extra)
return get_resp(test_client, "/csvtodatabaseview/form", data=form_data)
def upload_excel(
filename: str, table_name: str, extra: Optional[Dict[str, str]] = None
):
excel_upload_db_id = get_upload_db().id
schema = utils.get_example_default_schema()
form_data = {
"excel_file": open(filename, "rb"),
"name": table_name,
"con": excel_upload_db_id,
"sheet_name": "Sheet1",
"if_exists": "fail",
"index_label": "test_label",
"mangle_dupe_cols": False,
}
if schema:
form_data["schema"] = schema
if extra:
form_data.update(extra)
return get_resp(test_client, "/exceltodatabaseview/form", data=form_data)
def upload_columnar(
filename: str, table_name: str, extra: Optional[Dict[str, str]] = None
):
columnar_upload_db_id = get_upload_db().id
schema = utils.get_example_default_schema()
form_data = {
"columnar_file": open(filename, "rb"),
"name": table_name,
"con": columnar_upload_db_id,
"if_exists": "fail",
"index_label": "test_label",
}
if schema:
form_data["schema"] = schema
if extra:
form_data.update(extra)
return get_resp(test_client, "/columnartodatabaseview/form", data=form_data)
def mock_upload_to_s3(filename: str, upload_prefix: str, table: Table) -> str:
"""
HDFS is used instead of S3 for the unit tests.integration_tests.
:param filename: The file to upload
:param upload_prefix: The S3 prefix
:param table: The table that will be created
:returns: The HDFS path to the directory with external table files
"""
# only needed for the hive tests
import docker
client = docker.from_env()
container = client.containers.get("namenode")
# docker mounted volume that contains csv uploads
src = os.path.join("/tmp/superset_uploads", os.path.basename(filename))
# hdfs destination for the external tables
dest_dir = os.path.join("/tmp/external/superset_uploads/", str(table))
container.exec_run(f"hdfs dfs -mkdir -p {dest_dir}")
dest = os.path.join(dest_dir, os.path.basename(filename))
container.exec_run(f"hdfs dfs -put {src} {dest}")
# hive external table expectes a directory for the location
return dest_dir