superset/utils/csv.py

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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
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
import re
import urllib.request
from typing import Any, Dict, Optional
from urllib.error import URLError

import pandas as pd
import simplejson

negative_number_re = re.compile(r"^-[0-9.]+$")

# This regex will match if the string starts with:
#
#     1. one of -, @, +, |, =, %
#     2. two double quotes immediately followed by one of -, @, +, |, =, %
#     3. one or more spaces immediately followed by one of -, @, +, |, =, %
#
problematic_chars_re = re.compile(r'^(?:"{2}|\s{1,})(?=[\-@+|=%])|^[\-@+|=%]')


def escape_value(value: str) -> str:
    """
    Escapes a set of special characters.

    http://georgemauer.net/2017/10/07/csv-injection.html
    """
    needs_escaping = problematic_chars_re.match(value) is not None
    is_negative_number = negative_number_re.match(value) is not None

    if needs_escaping and not is_negative_number:
        # Escape pipe to be extra safe as this
        # can lead to remote code execution
        value = value.replace("|", "\\|")

        # Precede the line with a single quote. This prevents
        # evaluation of commands and some spreadsheet software
        # will hide this visually from the user. Many articles
        # claim a preceding space will work here too, however,
        # when uploading a csv file in Google sheets, a leading
        # space was ignored and code was still evaluated.
        value = "'" + value

    return value


def df_to_escaped_csv(df: pd.DataFrame, **kwargs: Any) -> Any:
    escape_values = lambda v: escape_value(v) if isinstance(v, str) else v

    # Escape csv headers
    df = df.rename(columns=escape_values)

    # Escape csv rows
    df = df.applymap(escape_values)

    return df.to_csv(**kwargs)


def get_chart_csv_data(
    chart_url: str, auth_cookies: Optional[Dict[str, str]] = None
) -> Optional[bytes]:
    content = None
    if auth_cookies:
        opener = urllib.request.build_opener()
        cookie_str = ";".join([f"{key}={val}" for key, val in auth_cookies.items()])
        opener.addheaders.append(("Cookie", cookie_str))
        response = opener.open(chart_url)
        content = response.read()
    if response.getcode() != 200:
        raise URLError(response.getcode())
    if content:
        return content
    return None


def get_chart_dataframe(
    chart_url: str, auth_cookies: Optional[Dict[str, str]] = None
) -> Optional[pd.DataFrame]:
    content = get_chart_csv_data(chart_url, auth_cookies)
    if content is None:
        return None

    result = simplejson.loads(content.decode("utf-8"))
    df = pd.DataFrame.from_dict(result["result"][0]["data"])

    # rebuild hierarchical columns and index
    df.columns = pd.MultiIndex.from_tuples(
        tuple(colname) if isinstance(colname, list) else (colname,)
        for colname in result["result"][0]["colnames"]
    )
    df.index = pd.MultiIndex.from_tuples(
        tuple(indexname) if isinstance(indexname, list) else (indexname,)
        for indexname in result["result"][0]["indexnames"]
    )
    return df