feat: Onboard sunroof dataset

datasets/sunroof/_images/run_csv_transform_kub/Dockerfile

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+# 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"]

datasets/sunroof/_images/run_csv_transform_kub/csv_transform.py

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+# 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 modules
+import logging
+import os
+import pathlib
+from subprocess import PIPE, Popen
+
+import pandas as pd
+from google.cloud import storage
+
+
+def main(
+    source_url: str,
+    source_file: pathlib.Path,
+    target_file: pathlib.Path,
+    chunksize: str,
+    target_gcs_bucket: str,
+    target_gcs_path: str,
+) -> None:
+
+    logging.info("Sunroof solar potential started")
+
+    pathlib.Path("./files").mkdir(parents=True, exist_ok=True)
+    download_file_gs(source_url, source_file)
+
+    chunksz = int(chunksize)
+
+    logging.info(f"Opening batch file {source_file}")
+    with pd.read_csv(
+        source_file,  # path to main source file to load in batches
+        engine="python",
+        encoding="utf-8",
+        quotechar='"',  # string separator, typically double-quotes
+        chunksize=chunksz,  # size of batch data, in no. of records
+        sep=",",  # data column separator, typically ","
+    ) as reader:
+        for chunk_number, chunk in enumerate(reader):
+            target_file_batch = str(target_file).replace(
+                ".csv", "-" + str(chunk_number) + ".csv"
+            )
+            df = pd.DataFrame()
+            df = pd.concat([df, chunk])
+            process_chunk(df, target_file_batch, target_file, (not chunk_number == 0))
+
+    upload_file_to_gcs(target_file, target_gcs_bucket, target_gcs_path)
+
+    logging.info("Sunroof solar potential process completed")
+
+
+def process_chunk(
+    df: pd.DataFrame, target_file_batch: str, target_file: str, skip_header: bool
+) -> None:
+    df = rename_headers(df)
+    df = remove_nan_cols(df)
+    df = generate_location(df)
+    df = reorder_headers(df)
+    save_to_new_file(df, file_path=str(target_file_batch))
+    append_batch_file(target_file_batch, target_file, skip_header, not (skip_header))
+
+
+def append_batch_file(
+    batch_file_path: str, target_file_path: str, skip_header: bool, truncate_file: bool
+) -> None:
+    data_file = open(batch_file_path, "r")
+    if truncate_file:
+        target_file = open(target_file_path, "w+").close()
+    target_file = open(target_file_path, "a+")
+    if skip_header:
+        logging.info(
+            f"Appending batch file {batch_file_path} to {target_file_path} with skip header"
+        )
+        next(data_file)
+    else:
+        logging.info(f"Appending batch file {batch_file_path} to {target_file_path}")
+    target_file.write(data_file.read())
+    data_file.close()
+    target_file.close()
+    if os.path.exists(batch_file_path):
+        os.remove(batch_file_path)
+
+
+def generate_location(df: pd.DataFrame) -> pd.DataFrame:
+    logging.info("Generating location data")
+    df["center_point"] = (
+        "POINT( " + df["lng_avg"].map(str) + " " + df["lat_avg"].map(str) + " )"
+    )
+
+    return df
+
+
+def reorder_headers(df: pd.DataFrame) -> pd.DataFrame:
+    logging.info("Reordering headers..")
+    df = df[
+        [
+            "region_name",
+            "state_name",
+            "lat_max",
+            "lat_min",
+            "lng_max",
+            "lng_min",
+            "lat_avg",
+            "lng_avg",
+            "yearly_sunlight_kwh_kw_threshold_avg",
+            "count_qualified",
+            "percent_covered",
+            "percent_qualified",
+            "number_of_panels_n",
+            "number_of_panels_s",
+            "number_of_panels_e",
+            "number_of_panels_w",
+            "number_of_panels_f",
+            "number_of_panels_median",
+            "number_of_panels_total",
+            "kw_median",
+            "kw_total",
+            "yearly_sunlight_kwh_n",
+            "yearly_sunlight_kwh_s",
+            "yearly_sunlight_kwh_e",
+            "yearly_sunlight_kwh_w",
+            "yearly_sunlight_kwh_f",
+            "yearly_sunlight_kwh_median",
+            "yearly_sunlight_kwh_total",
+            "install_size_kw_buckets",
+            "carbon_offset_metric_tons",
+            "existing_installs_count",
+            "center_point",
+        ]
+    ]
+
+    return df
+
+
+def remove_nan(dt_str: str) -> int:
+    if not dt_str or str(dt_str) == "nan":
+        return int()
+    else:
+        return int(dt_str)
+
+
+def remove_nan_cols(df: pd.DataFrame) -> pd.DataFrame:
+    logging.info("Resolve NaN data")
+    cols = {
+        "count_qualified",
+        "existing_installs_count",
+        "number_of_panels_n",
+        "number_of_panels_s",
+        "number_of_panels_e",
+        "number_of_panels_w",
+        "number_of_panels_f",
+        "number_of_panels_median",
+        "number_of_panels_total",
+    }
+
+    for col in cols:
+        df[col] = df[col].apply(remove_nan)
+
+    return df
+
+
+def rename_headers(df: pd.DataFrame) -> pd.DataFrame:
+    logging.info("Renaming columns")
+    header_names = {"install_size_kw_buckets_json": "install_size_kw_buckets"}
+    df = df.rename(columns=header_names)
+
+    return df
+
+
+def save_to_new_file(df: pd.DataFrame, file_path) -> None:
+    df.to_csv(file_path, index=False)
+
+
+def download_file_gs(source_url: str, source_file: pathlib.Path) -> None:
+    process = Popen(["gsutil", "cp", source_url, source_file], stdout=PIPE, stderr=PIPE)
+    process.communicate()
+
+
+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)
+
+
+if __name__ == "__main__":
+    logging.getLogger().setLevel(logging.INFO)
+
+    main(
+        source_url=os.environ["SOURCE_URL"],
+        source_file=pathlib.Path(os.environ["SOURCE_FILE"]).expanduser(),
+        target_file=pathlib.Path(os.environ["TARGET_FILE"]).expanduser(),
+        chunksize=os.environ["CHUNKSIZE"],
+        target_gcs_bucket=os.environ["TARGET_GCS_BUCKET"],
+        target_gcs_path=os.environ["TARGET_GCS_PATH"],
+    )

datasets/sunroof/_images/run_csv_transform_kub/requirements.txt

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+pandas
+google-cloud-storage
+gsutil

datasets/sunroof/_terraform/provider.tf

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+/**
+ * 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.
+ */
+
+
+provider "google" {
+  project                     = var.project_id
+  impersonate_service_account = var.impersonating_acct
+  region                      = var.region
+}
+
+data "google_client_openid_userinfo" "me" {}
+
+output "impersonating-account" {
+  value = data.google_client_openid_userinfo.me.email
+}

datasets/sunroof/_terraform/solar_potential_by_census_tract_pipeline.tf

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+/**
+ * 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" "solar_potential_by_census_tract" {
+  project    = var.project_id
+  dataset_id = "sunroof"
+  table_id   = "solar_potential_by_census_tract"
+
+  description = "Sunroof Solar Potential By Census Tract"
+
+
+
+
+  depends_on = [
+    google_bigquery_dataset.sunroof
+  ]
+}
+
+output "bigquery_table-solar_potential_by_census_tract-table_id" {
+  value = google_bigquery_table.solar_potential_by_census_tract.table_id
+}
+
+output "bigquery_table-solar_potential_by_census_tract-id" {
+  value = google_bigquery_table.solar_potential_by_census_tract.id
+}

datasets/sunroof/_terraform/solar_potential_by_postal_code_pipeline.tf

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+/**
+ * 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" "solar_potential_by_postal_code" {
+  project    = var.project_id
+  dataset_id = "sunroof"
+  table_id   = "solar_potential_by_postal_code"
+
+  description = "Sunroof Solar Potential By Postal Code"
+
+
+
+
+  depends_on = [
+    google_bigquery_dataset.sunroof
+  ]
+}
+
+output "bigquery_table-solar_potential_by_postal_code-table_id" {
+  value = google_bigquery_table.solar_potential_by_postal_code.table_id
+}
+
+output "bigquery_table-solar_potential_by_postal_code-id" {
+  value = google_bigquery_table.solar_potential_by_postal_code.id
+}

datasets/sunroof/_terraform/sunroof_dataset.tf

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+/**
+ * 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_dataset" "sunroof" {
+  dataset_id  = "sunroof"
+  project     = var.project_id
+  description = "sunroof"
+}
+
+output "bigquery_dataset-sunroof-dataset_id" {
+  value = google_bigquery_dataset.sunroof.dataset_id
+}