feat: Onboard Chicago Crime dataset

datasets/chicago_crime/_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/chicago_crime/_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 datetime
+import logging
+import math
+import os
+import pathlib
+import typing
+
+import pandas as pd
+import requests
+from google.cloud import storage
+
+
+def main(
+    source_url: str,
+    source_file: pathlib.Path,
+    target_file: pathlib.Path,
+    target_gcs_bucket: str,
+    target_gcs_path: str,
+) -> None:
+
+    logging.info(
+        "Chicago Crime 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 = pd.read_csv(source_file)
+
+    logging.info(f"Transforming {source_file} ...")
+
+    logging.info(f"Transform: Rename columns {source_file} ...")
+    rename_headers(df)
+
+    logging.info("Transform: Converting date format.. ")
+    convert_values(df)
+
+    logging.info("Transform: Removing null values.. ")
+    filter_null_rows(df)
+
+    logging.info("Transform: Converting to integers..")
+    convert_values_to_integer_string(df)
+
+    logging.info("Transform: Converting to float..")
+    removing_nan_values(df)
+
+    logging.info("Transform: Reordering headers..")
+    df = df[
+        [
+            "unique_key",
+            "case_number",
+            "date",
+            "block",
+            "iucr",
+            "primary_type",
+            "description",
+            "location_description",
+            "arrest",
+            "domestic",
+            "beat",
+            "district",
+            "ward",
+            "community_area",
+            "fbi_code",
+            "x_coordinate",
+            "y_coordinate",
+            "year",
+            "updated_on",
+            "latitude",
+            "longitude",
+            "location",
+        ]
+    ]
+
+    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(
+        "Chicago crime process completed at "
+        + str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
+    )
+
+
+def resolve_nan(input: typing.Union[str, float]) -> str:
+    str_val = ""
+    if not input or (math.isnan(input)):
+        str_val = ""
+    else:
+        str_val = str(input)
+    return str_val.replace("None", "")
+
+
+def removing_nan_values(df: pd.DataFrame) -> None:
+    cols = ["x_coordinate", "y_coordinate", "latitude", "longitude"]
+
+    for cols in cols:
+        df[cols] = df[cols].apply(resolve_nan)
+
+
+def convert_to_integer_string(input: typing.Union[str, float]) -> str:
+    str_val = ""
+    if not input or (math.isnan(input)):
+        str_val = ""
+    else:
+        str_val = str(int(round(input, 0)))
+    return str_val
+
+
+def convert_values_to_integer_string(df: pd.DataFrame) -> None:
+    cols = ["unique_key", "beat", "district", "ward", "community_area", "year"]
+
+    for cols in cols:
+        df[cols] = df[cols].apply(convert_to_integer_string)
+
+
+def rename_headers(df: pd.DataFrame) -> None:
+    header_names = {
+        "ID": "unique_key",
+        "Case Number": "case_number",
+        "Date": "date",
+        "Block": "block",
+        "IUCR": "iucr",
+        "Primary Type": "primary_type",
+        "Description": "description",
+        "Location Description": "location_description",
+        "Arrest": "arrest",
+        "Domestic": "domestic",
+        "Beat": "beat",
+        "District": "district",
+        "Ward": "ward",
+        "Community Area": "community_area",
+        "FBI Code": "fbi_code",
+        "X Coordinate": "x_coordinate",
+        "Y Coordinate": "y_coordinate",
+        "Year": "year",
+        "Updated On": "updated_on",
+        "Latitude": "latitude",
+        "Longitude": "longitude",
+        "Location": "location",
+    }
+
+    df.rename(columns=header_names, inplace=True)
+
+
+def convert_dt_format(dt_str: str) -> str:
+    # Old format: MM/dd/yyyy hh:mm:ss aa
+    # New format: yyyy-MM-dd HH:mm:ss
+    if dt_str is None or len(dt_str) == 0:
+        return dt_str
+    else:
+        return datetime.datetime.strptime(dt_str, "%m/%d/%Y %H:%M:%S %p").strftime(
+            "%Y-%m-%d %H:%M:%S"
+        )
+
+
+def convert_values(df: pd.DataFrame) -> None:
+    dt_cols = ["date", "updated_on"]
+
+    for dt_col in dt_cols:
+        df[dt_col] = df[dt_col].apply(convert_dt_format)
+
+
+def filter_null_rows(df: pd.DataFrame) -> None:
+    df = df[df.unique_key != ""]
+
+
+def save_to_new_file(df: pd.DataFrame, file_path: pathlib.Path) -> None:
+    df.to_csv(file_path, index=False)
+
+
+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 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(),
+        target_gcs_bucket=os.environ["TARGET_GCS_BUCKET"],
+        target_gcs_path=os.environ["TARGET_GCS_PATH"],
+    )

datasets/chicago_crime/_images/run_csv_transform_kub/requirements.txt

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+requests
+pandas
+google-cloud-storage

datasets/chicago_crime/_terraform/chicago_crime_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" "chicago_crime" {
+  dataset_id  = "chicago_crime"
+  project     = var.project_id
+  description = "chicago crime"
+}
+
+output "bigquery_dataset-chicago_crime-dataset_id" {
+  value = google_bigquery_dataset.chicago_crime.dataset_id
+}

datasets/chicago_crime/_terraform/crime_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" "crime" {
+  project    = var.project_id
+  dataset_id = "chicago_crime"
+  table_id   = "crime"
+
+  description = "chicago crime dataset"
+
+
+
+
+  depends_on = [
+    google_bigquery_dataset.chicago_crime
+  ]
+}
+
+output "bigquery_table-crime-table_id" {
+  value = google_bigquery_table.crime.table_id
+}
+
+output "bigquery_table-crime-id" {
+  value = google_bigquery_table.crime.id
+}

datasets/chicago_crime/_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/chicago_crime/_terraform/variables.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.
+ */
+
+
+variable "project_id" {}
+variable "bucket_name_prefix" {}
+variable "impersonating_acct" {}
+variable "region" {}
+variable "env" {}
+