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# 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

from superset.sql_parse import Table
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 = utils.get_or_create_db(
            CSV_UPLOAD_DATABASE, app.config["SQLALCHEMY_EXAMPLES_URI"]
        )
        extra = upload_db.get_extra()
        extra["explore_database_id"] = utils.get_example_database().id
        upload_db.extra = json.dumps(extra)
        upload_db.allow_csv_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
    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 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
):
    form_data = {
        "excel_file": open(filename, "rb"),
        "name": table_name,
        "con": get_upload_db().id,
        "sheet_name": "Sheet1",
        "if_exists": "fail",
        "index_label": "test_label",
        "mangle_dupe_cols": False,
    }
    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
    form_data = {
        "columnar_file": open(filename, "rb"),
        "name": table_name,
        "con": columnar_upload_db_id,
        "if_exists": "fail",
        "index_label": "test_label",
    }
    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


@mock.patch(
    "superset.models.core.config",
    {**app.config, "ALLOWED_USER_CSV_SCHEMA_FUNC": lambda d, u: ["admin_database"]},
)
@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
def test_import_csv_enforced_schema(setup_csv_upload, create_csv_files):
    if utils.backend() == "sqlite":
        pytest.skip("Sqlite doesn't support schema / database creation")

    full_table_name = f"admin_database.{CSV_UPLOAD_TABLE_W_SCHEMA}"

    # no schema specified, fail upload
    resp = upload_csv(CSV_FILENAME1, CSV_UPLOAD_TABLE_W_SCHEMA)
    assert (
        f'Database "{CSV_UPLOAD_DATABASE}" schema "None" is not allowed for csv uploads'
        in resp
    )

    success_msg = f'CSV file "{CSV_FILENAME1}" uploaded to table "{full_table_name}"'
    resp = upload_csv(
        CSV_FILENAME1,
        CSV_UPLOAD_TABLE_W_SCHEMA,
        extra={"schema": "admin_database", "if_exists": "replace"},
    )
    assert success_msg in resp

    engine = get_upload_db().get_sqla_engine()
    data = engine.execute(
        f"SELECT * from {ADMIN_SCHEMA_NAME}.{CSV_UPLOAD_TABLE_W_SCHEMA}"
    ).fetchall()
    assert data == [("john", 1), ("paul", 2)]

    # user specified schema doesn't match, fail
    resp = upload_csv(
        CSV_FILENAME1, CSV_UPLOAD_TABLE_W_SCHEMA, extra={"schema": "gold"}
    )
    assert (
        f'Database "{CSV_UPLOAD_DATABASE}" schema "gold" is not allowed for csv uploads'
        in resp
    )

    # user specified schema matches the expected schema, append
    if utils.backend() == "hive":
        pytest.skip("Hive database doesn't support append csv uploads.")
    resp = upload_csv(
        CSV_FILENAME1,
        CSV_UPLOAD_TABLE_W_SCHEMA,
        extra={"schema": "admin_database", "if_exists": "append"},
    )
    assert success_msg in resp


@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
def test_import_csv_explore_database(setup_csv_upload, create_csv_files):
    if utils.backend() == "sqlite":
        pytest.skip("Sqlite doesn't support schema / database creation")

    resp = upload_csv(CSV_FILENAME1, CSV_UPLOAD_TABLE_W_EXPLORE)
    assert (
        f'CSV file "{CSV_FILENAME1}" uploaded to table "{CSV_UPLOAD_TABLE_W_EXPLORE}"'
        in resp
    )
    table = SupersetTestCase.get_table(name=CSV_UPLOAD_TABLE_W_EXPLORE)
    assert table.database_id == utils.get_example_database().id


@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
def test_import_csv(setup_csv_upload, create_csv_files):
    success_msg_f1 = (
        f'CSV file "{CSV_FILENAME1}" uploaded to table "{CSV_UPLOAD_TABLE}"'
    )

    # initial upload with fail mode
    resp = upload_csv(CSV_FILENAME1, CSV_UPLOAD_TABLE)
    assert success_msg_f1 in resp

    # upload again with fail mode; should fail
    fail_msg = (
        f'Unable to upload CSV file "{CSV_FILENAME1}" to table "{CSV_UPLOAD_TABLE}"'
    )
    resp = upload_csv(CSV_FILENAME1, CSV_UPLOAD_TABLE)
    assert fail_msg in resp

    if utils.backend() != "hive":
        # upload again with append mode
        resp = upload_csv(
            CSV_FILENAME1, CSV_UPLOAD_TABLE, extra={"if_exists": "append"}
        )
        assert success_msg_f1 in resp

    # upload again with replace mode and specific columns
    resp = upload_csv(
        CSV_FILENAME1,
        CSV_UPLOAD_TABLE,
        extra={"if_exists": "replace", "usecols": '["a"]'},
    )
    assert success_msg_f1 in resp

    # make sure only specified column name was read
    table = SupersetTestCase.get_table(name=CSV_UPLOAD_TABLE)
    assert "b" not in table.column_names

    # upload again with replace mode
    resp = upload_csv(CSV_FILENAME1, CSV_UPLOAD_TABLE, extra={"if_exists": "replace"})
    assert success_msg_f1 in resp

    # try to append to table from file with different schema
    resp = upload_csv(CSV_FILENAME2, CSV_UPLOAD_TABLE, extra={"if_exists": "append"})
    fail_msg_f2 = (
        f'Unable to upload CSV file "{CSV_FILENAME2}" to table "{CSV_UPLOAD_TABLE}"'
    )
    assert fail_msg_f2 in resp

    # replace table from file with different schema
    resp = upload_csv(CSV_FILENAME2, CSV_UPLOAD_TABLE, extra={"if_exists": "replace"})
    success_msg_f2 = (
        f'CSV file "{CSV_FILENAME2}" uploaded to table "{CSV_UPLOAD_TABLE}"'
    )
    assert success_msg_f2 in resp

    table = SupersetTestCase.get_table(name=CSV_UPLOAD_TABLE)
    # make sure the new column name is reflected in the table metadata
    assert "d" in table.column_names

    # null values are set
    upload_csv(
        CSV_FILENAME2,
        CSV_UPLOAD_TABLE,
        extra={"null_values": '["", "john"]', "if_exists": "replace"},
    )
    # make sure that john and empty string are replaced with None
    engine = get_upload_db().get_sqla_engine()
    data = engine.execute(f"SELECT * from {CSV_UPLOAD_TABLE}").fetchall()
    assert data == [(None, 1, "x"), ("paul", 2, None)]

    # default null values
    upload_csv(CSV_FILENAME2, CSV_UPLOAD_TABLE, extra={"if_exists": "replace"})
    # make sure that john and empty string are replaced with None
    data = engine.execute(f"SELECT * from {CSV_UPLOAD_TABLE}").fetchall()
    assert data == [("john", 1, "x"), ("paul", 2, None)]


@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
def test_import_excel(setup_csv_upload, create_excel_files):
    if utils.backend() == "hive":
        pytest.skip("Hive doesn't excel upload.")

    success_msg = (
        f'Excel file "{EXCEL_FILENAME}" uploaded to table "{EXCEL_UPLOAD_TABLE}"'
    )

    # initial upload with fail mode
    resp = upload_excel(EXCEL_FILENAME, EXCEL_UPLOAD_TABLE)
    assert success_msg in resp

    # upload again with fail mode; should fail
    fail_msg = f'Unable to upload Excel file "{EXCEL_FILENAME}" to table "{EXCEL_UPLOAD_TABLE}"'
    resp = upload_excel(EXCEL_FILENAME, EXCEL_UPLOAD_TABLE)
    assert fail_msg in resp

    if utils.backend() != "hive":
        # upload again with append mode
        resp = upload_excel(
            EXCEL_FILENAME, EXCEL_UPLOAD_TABLE, extra={"if_exists": "append"}
        )
        assert success_msg in resp

    # upload again with replace mode
    resp = upload_excel(
        EXCEL_FILENAME, EXCEL_UPLOAD_TABLE, extra={"if_exists": "replace"}
    )
    assert success_msg in resp

    # make sure that john and empty string are replaced with None
    data = (
        get_upload_db()
        .get_sqla_engine()
        .execute(f"SELECT * from {EXCEL_UPLOAD_TABLE}")
        .fetchall()
    )
    assert data == [(0, "john", 1), (1, "paul", 2)]


@mock.patch("superset.db_engine_specs.hive.upload_to_s3", mock_upload_to_s3)
def test_import_parquet(setup_csv_upload, create_columnar_files):
    if utils.backend() == "hive":
        pytest.skip("Hive doesn't allow parquet upload.")

    success_msg_f1 = f'Columnar file "[\'{PARQUET_FILENAME1}\']" uploaded to table "{PARQUET_UPLOAD_TABLE}"'

    # initial upload with fail mode
    resp = upload_columnar(PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE)
    assert success_msg_f1 in resp

    # upload again with fail mode; should fail
    fail_msg = f'Unable to upload Columnar file "[\'{PARQUET_FILENAME1}\']" to table "{PARQUET_UPLOAD_TABLE}"'
    resp = upload_columnar(PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE)
    assert fail_msg in resp

    if utils.backend() != "hive":
        # upload again with append mode
        resp = upload_columnar(
            PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE, extra={"if_exists": "append"}
        )
        assert success_msg_f1 in resp

    # upload again with replace mode and specific columns
    resp = upload_columnar(
        PARQUET_FILENAME1,
        PARQUET_UPLOAD_TABLE,
        extra={"if_exists": "replace", "usecols": '["a"]'},
    )
    assert success_msg_f1 in resp

    # make sure only specified column name was read
    table = SupersetTestCase.get_table(name=PARQUET_UPLOAD_TABLE)
    assert "b" not in table.column_names

    # upload again with replace mode
    resp = upload_columnar(
        PARQUET_FILENAME1, PARQUET_UPLOAD_TABLE, extra={"if_exists": "replace"}
    )
    assert success_msg_f1 in resp

    data = (
        get_upload_db()
        .get_sqla_engine()
        .execute(f"SELECT * from {PARQUET_UPLOAD_TABLE} ORDER BY b")
        .fetchall()
    )
    assert data == [("john", 1), ("paul", 2)]

    # replace table with zip file
    resp = upload_columnar(
        ZIP_FILENAME, PARQUET_UPLOAD_TABLE, extra={"if_exists": "replace"}
    )
    success_msg_f2 = f'Columnar file "[\'{ZIP_FILENAME}\']" uploaded to table "{PARQUET_UPLOAD_TABLE}"'
    assert success_msg_f2 in resp

    data = (
        get_upload_db()
        .get_sqla_engine()
        .execute(f"SELECT * from {PARQUET_UPLOAD_TABLE} ORDER BY b")
        .fetchall()
    )
    assert data == [("john", 1), ("paul", 2), ("max", 3), ("bob", 4)]