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feat: Onboard Google Political Ads dataset #149

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@@ -0,0 +1,38 @@
# Copyright 2021 Google LLC
#
# Licensed 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.

# The base image for this build
# FROM gcr.io/google.com/cloudsdktool/cloud-sdk:slim
FROM python:3.8

# Allow statements and log messages to appear in Cloud logs
ENV PYTHONUNBUFFERED True

# Copy the requirements file into the image
COPY requirements.txt ./

# Install the packages specified in the requirements file
RUN python3 -m pip install --no-cache-dir -r requirements.txt

# The WORKDIR instruction sets the working directory for any RUN, CMD,
# ENTRYPOINT, COPY and ADD instructions that follow it in the Dockerfile.
# If the WORKDIR doesn’t exist, it will be created even if it’s not used in
# any subsequent Dockerfile instruction
WORKDIR /custom

# Copy the specific data processing script/s in the image under /custom/*
COPY ./csv_transform.py .

# Command to run the data processing script when the container is run
CMD ["python3", "csv_transform.py"]
@@ -0,0 +1,13 @@
[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"

[packages]
requests = "*"
vaex = "*"

[dev-packages]

[requires]
python_version = "3.9"
@@ -0,0 +1,157 @@
# Copyright 2021 Google LLC
#
# Licensed 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 datetime
import fnmatch
import json
import logging
import math
import os
import pathlib
import typing
from zipfile import ZipFile

import pandas as pd
import requests
from google.cloud import storage


def main(
source_url: str,
source_file: pathlib.Path,
source_csv_name: str,
target_file: pathlib.Path,
target_gcs_bucket: str,
target_gcs_path: str,
headers: typing.List[str],
rename_mappings: dict,
pipeline_name: str,
) -> None:

logging.info(
f"google political ads {pipeline_name} process started at "
+ str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
)

logging.info("creating 'files' folder")
pathlib.Path("./files").mkdir(parents=True, exist_ok=True)

logging.info(f"Downloading file {source_url}")
download_file(source_url, source_file)

logging.info(f"Opening file {source_file}")
df = read_csv_file(source_file, source_csv_name)

logging.info(f"Transforming.. {source_file}")

logging.info(f"Transform: Rename columns for {pipeline_name}..")
rename_headers(df, rename_mappings)

if pipeline_name == "creative_stats":
logging.info(f"Transform: converting to integer for {pipeline_name}..")
df["spend_range_max_usd"] = df["spend_range_max_usd"].apply(convert_to_int)
df["spend_range_max_eur"] = df["spend_range_max_eur"].apply(convert_to_int)
df["spend_range_max_inr"] = df["spend_range_max_inr"].apply(convert_to_int)
df["spend_range_max_bgn"] = df["spend_range_max_bgn"].apply(convert_to_int)
df["spend_range_max_hrk"] = df["spend_range_max_hrk"].apply(convert_to_int)
df["spend_range_max_czk"] = df["spend_range_max_czk"].apply(convert_to_int)
df["spend_range_max_dkk"] = df["spend_range_max_dkk"].apply(convert_to_int)
df["spend_range_max_huf"] = df["spend_range_max_huf"].apply(convert_to_int)
df["spend_range_max_pln"] = df["spend_range_max_pln"].apply(convert_to_int)
df["spend_range_max_ron"] = df["spend_range_max_ron"].apply(convert_to_int)
df["spend_range_max_gbp"] = df["spend_range_max_gbp"].apply(convert_to_int)
df["spend_range_max_sek"] = df["spend_range_max_sek"].apply(convert_to_int)
df["spend_range_max_nzd"] = df["spend_range_max_nzd"].apply(convert_to_int)
else:
df = df

logging.info(f"Transform: Reordering headers for {pipeline_name}.. ")
df = df[headers]

logging.info(f"Saving to output file.. {target_file}")
try:
save_to_new_file(df, file_path=str(target_file))
except Exception as e:
logging.error(f"Error saving output file: {e}.")

logging.info(
f"Uploading output file to.. gs://{target_gcs_bucket}/{target_gcs_path}"
)
upload_file_to_gcs(target_file, target_gcs_bucket, target_gcs_path)

logging.info(
f"Google Political Ads {pipeline_name} process completed at "
+ str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
)


def save_to_new_file(df: pd.DataFrame, file_path: str) -> None:
df.to_csv(file_path, index=False)


def upload_file_to_gcs(file_path: pathlib.Path, gcs_bucket: str, gcs_path: str) -> None:
storage_client = storage.Client()
bucket = storage_client.bucket(gcs_bucket)
blob = bucket.blob(gcs_path)
blob.upload_from_filename(file_path)


def download_file(source_url: str, source_file: pathlib.Path) -> None:
logging.info(f"Downloading {source_url} into {source_file}")
r = requests.get(source_url, stream=True)
if r.status_code == 200:
with open(source_file, "wb") as f:
for chunk in r:
f.write(chunk)
else:
logging.error(f"Couldn't download {source_url}: {r.text}")


def read_csv_file(source_file: pathlib.Path, source_csv_name: str) -> pd.DataFrame:
with ZipFile(source_file) as zipfiles:
file_list = zipfiles.namelist()
csv_files = fnmatch.filter(file_list, source_csv_name)
data = [pd.read_csv(zipfiles.open(file_name)) for file_name in csv_files]
df = pd.concat(data)
return df


def rename_headers(df: pd.DataFrame, rename_mappings: dict) -> None:
df.rename(columns=rename_mappings, inplace=True)


def convert_to_int(input: str) -> str:
str_val = ""
if input == "" or (math.isnan(input)):
str_val = ""
else:
str_val = str(int(round(input, 0)))
return str_val


if __name__ == "__main__":
logging.getLogger().setLevel(logging.INFO)

main(
source_url=os.environ["SOURCE_URL"],
source_file=pathlib.Path(os.environ["SOURCE_FILE"]).expanduser(),
source_csv_name=os.environ["FILE_NAME"],
target_file=pathlib.Path(os.environ["TARGET_FILE"]).expanduser(),
target_gcs_bucket=os.environ["TARGET_GCS_BUCKET"],
target_gcs_path=os.environ["TARGET_GCS_PATH"],
headers=json.loads(os.environ["CSV_HEADERS"]),
rename_mappings=json.loads(os.environ["RENAME_MAPPINGS"]),
pipeline_name=os.environ["PIPELINE_NAME"],
)
@@ -0,0 +1,3 @@
requests
google-cloud-storage
pandas
@@ -0,0 +1,39 @@
/**
* Copyright 2021 Google LLC
*
* Licensed 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.
*/


resource "google_bigquery_table" "advertiser_declared_stats" {
project = var.project_id
dataset_id = "google_political_ads"
table_id = "advertiser_declared_stats"

description = "advertiser_declared_stats dataset"




depends_on = [
google_bigquery_dataset.google_political_ads
]
}

output "bigquery_table-advertiser_declared_stats-table_id" {
value = google_bigquery_table.advertiser_declared_stats.table_id
}

output "bigquery_table-advertiser_declared_stats-id" {
value = google_bigquery_table.advertiser_declared_stats.id
}
@@ -0,0 +1,39 @@
/**
* Copyright 2021 Google LLC
*
* Licensed 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.
*/


resource "google_bigquery_table" "advertiser_stats" {
project = var.project_id
dataset_id = "google_political_ads"
table_id = "advertiser_stats"

description = "advertiser_stats dataset"




depends_on = [
google_bigquery_dataset.google_political_ads
]
}

output "bigquery_table-advertiser_stats-table_id" {
value = google_bigquery_table.advertiser_stats.table_id
}

output "bigquery_table-advertiser_stats-id" {
value = google_bigquery_table.advertiser_stats.id
}
@@ -0,0 +1,39 @@
/**
* Copyright 2021 Google LLC
*
* Licensed 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.
*/


resource "google_bigquery_table" "advertiser_weekly_spend" {
project = var.project_id
dataset_id = "google_political_ads"
table_id = "advertiser_weekly_spend"

description = "advertiser_weekly_spend dataset"




depends_on = [
google_bigquery_dataset.google_political_ads
]
}

output "bigquery_table-advertiser_weekly_spend-table_id" {
value = google_bigquery_table.advertiser_weekly_spend.table_id
}

output "bigquery_table-advertiser_weekly_spend-id" {
value = google_bigquery_table.advertiser_weekly_spend.id
}
@@ -0,0 +1,39 @@
/**
* Copyright 2021 Google LLC
*
* Licensed 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.
*/


resource "google_bigquery_table" "campaign_targeting" {
project = var.project_id
dataset_id = "google_political_ads"
table_id = "campaign_targeting"

description = "campaign_targeting dataset"




depends_on = [
google_bigquery_dataset.google_political_ads
]
}

output "bigquery_table-campaign_targeting-table_id" {
value = google_bigquery_table.campaign_targeting.table_id
}

output "bigquery_table-campaign_targeting-id" {
value = google_bigquery_table.campaign_targeting.id
}