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Feat: Onboard SEC Failure to Deliver dataset (#309)
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datasets/sec_failure_to_deliver/infra/fails_to_deliver_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. | ||
*/ | ||
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resource "google_bigquery_table" "sec_failure_to_deliver_fails_to_deliver" { | ||
project = var.project_id | ||
dataset_id = "sec_failure_to_deliver" | ||
table_id = "fails_to_deliver" | ||
description = "fails_to_deliver Dataset" | ||
depends_on = [ | ||
google_bigquery_dataset.sec_failure_to_deliver | ||
] | ||
} | ||
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output "bigquery_table-sec_failure_to_deliver_fails_to_deliver-table_id" { | ||
value = google_bigquery_table.sec_failure_to_deliver_fails_to_deliver.table_id | ||
} | ||
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output "bigquery_table-sec_failure_to_deliver_fails_to_deliver-id" { | ||
value = google_bigquery_table.sec_failure_to_deliver_fails_to_deliver.id | ||
} |
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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. | ||
*/ | ||
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provider "google" { | ||
project = var.project_id | ||
impersonate_service_account = var.impersonating_acct | ||
region = var.region | ||
} | ||
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data "google_client_openid_userinfo" "me" {} | ||
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output "impersonating-account" { | ||
value = data.google_client_openid_userinfo.me.email | ||
} |
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datasets/sec_failure_to_deliver/infra/sec_failure_to_deliver_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. | ||
*/ | ||
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resource "google_bigquery_dataset" "sec_failure_to_deliver" { | ||
dataset_id = "sec_failure_to_deliver" | ||
project = var.project_id | ||
description = "sec_failure_to_deliver datasets" | ||
} | ||
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output "bigquery_dataset-sec_failure_to_deliver-dataset_id" { | ||
value = google_bigquery_dataset.sec_failure_to_deliver.dataset_id | ||
} |
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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. | ||
*/ | ||
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variable "project_id" {} | ||
variable "bucket_name_prefix" {} | ||
variable "impersonating_acct" {} | ||
variable "region" {} | ||
variable "env" {} | ||
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datasets/sec_failure_to_deliver/pipelines/_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. | ||
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# The base image for this build | ||
FROM python:3.8 | ||
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# Allow statements and log messages to appear in Cloud logs | ||
ENV PYTHONUNBUFFERED True | ||
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RUN apt-get -y update && apt-get install -y apt-transport-https ca-certificates gnupg &&\ | ||
echo "deb https://packages.cloud.google.com/apt cloud-sdk main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list &&\ | ||
curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - &&\ | ||
apt-get -y update && apt-get install -y google-cloud-sdk | ||
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# Copy the requirements file into the image | ||
COPY requirements.txt ./ | ||
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# Install the packages specified in the requirements file | ||
RUN python3 -m pip install --no-cache-dir -r requirements.txt | ||
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# 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 | ||
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# Copy the specific data processing script/s in the image under /custom/* | ||
COPY ./csv_transform.py . | ||
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# Command to run the data processing script when the container is run | ||
CMD ["python3", "csv_transform.py"] |
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datasets/sec_failure_to_deliver/pipelines/_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. | ||
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import json | ||
import logging | ||
import os | ||
import pathlib | ||
import subprocess | ||
import typing | ||
from glob import glob | ||
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import pandas as pd | ||
from google.cloud import storage | ||
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def main( | ||
source_url: str, | ||
source_file: pathlib.Path, | ||
target_file: pathlib.Path, | ||
chunksize: str, | ||
target_gcs_bucket: str, | ||
target_gcs_path: str, | ||
input_headers: typing.List[str], | ||
data_dtypes: dict, | ||
output_headers: typing.List[str], | ||
) -> None: | ||
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logging.info("Creating 'files' folder") | ||
pathlib.Path("./files").mkdir(parents=True, exist_ok=True) | ||
source_folder = os.path.split(source_file)[0] | ||
download_file(source_url, source_folder) | ||
concatenate_files(source_folder, source_file) | ||
process_data( | ||
source_file, target_file, chunksize, input_headers, data_dtypes, output_headers | ||
) | ||
upload_file_to_gcs(target_file, target_gcs_bucket, target_gcs_path) | ||
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def save_to_new_file(df, file_path): | ||
df.to_csv(file_path, index=False) | ||
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def download_file(source_url: str, source_file: pathlib.Path) -> None: | ||
logging.info(f"Downloading files at {source_url}") | ||
subprocess.check_call( | ||
["gsutil", "-m", "cp", "-r", f"{source_url}", f"{source_file}"] | ||
) | ||
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def concatenate_files(source_folder: str, source_file: str) -> None: | ||
logging.info("Concatenating files") | ||
file_number = 1 | ||
for path, subdir, files in os.walk(source_folder + "/FTD"): | ||
for file in glob(os.path.join(path, "*.csv")): | ||
resolve_source_data_issues(path, file) | ||
if file_number == 1: | ||
append_file(file, source_file, True, True) | ||
else: | ||
append_file(file, source_file, False, False) | ||
file_number = file_number + 1 | ||
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def resolve_source_data_issues(path: str, file: str) -> None: | ||
cmd_list = [ | ||
# resolve newlines in quoted text | ||
f"sed -zi 's/\\n\\\"\\n/\\\"\\n/g' {file}", | ||
f"sed -zi 's/\\n\\\",,,,,\\n/\\\",,,,,\\n/g' {file}", | ||
f"sed -i '/^\\\",,,,,/d' {file}", | ||
# remove NUL characters | ||
"sed -i 's/\\x0//g' " + file, | ||
# remove trailer text from all source files under the source path recursively | ||
f'find {path} -type f -name "*.csv" -exec sed -i "/Trailer record count/d" {{}} +', | ||
f'find {path} -type f -name "*.csv" -exec sed -i "/Trailer total quantity of shares/d" {{}} +', | ||
] | ||
logging.info(f"Resolving source data issues on file {file}") | ||
for cmd in cmd_list: | ||
logging.info("cmd: " + cmd) | ||
subprocess.check_call([cmd], shell=True) | ||
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def process_data( | ||
source_file: str, | ||
target_file: str, | ||
chunksize: str, | ||
input_headers: typing.List[str], | ||
data_dtypes: dict, | ||
output_headers: typing.List[str], | ||
) -> None: | ||
logging.info(f"Processing {source_file} started") | ||
with pd.read_csv( | ||
source_file, | ||
engine="python", | ||
encoding="utf-8", | ||
quotechar='"', | ||
chunksize=int(chunksize), | ||
sep=",", | ||
names=input_headers, | ||
skiprows=1, | ||
dtype=data_dtypes, | ||
) as reader: | ||
for chunk_number, chunk in enumerate(reader): | ||
logging.info( | ||
f"Processing chunk #{chunk_number} of file {source_file} started" | ||
) | ||
target_file_batch = str(target_file).replace(".csv", f"-{chunk_number}.csv") | ||
df = pd.DataFrame() | ||
df = pd.concat([df, chunk]) | ||
process_chunk( | ||
df, | ||
target_file_batch, | ||
target_file, | ||
chunk_number == 0, | ||
chunk_number == 0, | ||
output_headers, | ||
) | ||
logging.info( | ||
f"Processing chunk #{chunk_number} of file {source_file} completed" | ||
) | ||
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def process_chunk( | ||
df: pd.DataFrame, | ||
target_file_batch: str, | ||
target_file: str, | ||
include_header: bool, | ||
truncate_file: bool, | ||
output_headers: typing.List[str], | ||
) -> None: | ||
logging.info(f"Processing Batch {target_file_batch} started") | ||
df = search_and_replace_values(df) | ||
df = reorder_headers(df, output_headers) | ||
save_to_new_file(df, file_path=str(target_file_batch)) | ||
append_file(target_file_batch, target_file, include_header, truncate_file, True) | ||
logging.info(f"Processing Batch {target_file_batch} completed") | ||
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def append_file( | ||
batch_file_path: str, | ||
target_file_path: str, | ||
include_header: bool, | ||
truncate_target_file: bool, | ||
remove_source: bool = False, | ||
) -> None: | ||
logging.info( | ||
f"Appending file {batch_file_path} to file {target_file_path} with include_header={include_header} and truncate_target_file={truncate_target_file}" | ||
) | ||
with open(batch_file_path, "r") as data_file: | ||
if truncate_target_file: | ||
target_file = open(target_file_path, "w+").close() | ||
with open(target_file_path, "a+") as target_file: | ||
if not include_header: | ||
logging.info( | ||
f"Appending batch file {batch_file_path} to {target_file_path} without header" | ||
) | ||
next(data_file) | ||
else: | ||
logging.info( | ||
f"Appending batch file {batch_file_path} to {target_file_path} with header" | ||
) | ||
target_file.write(data_file.read()) | ||
data_file.close() | ||
target_file.close() | ||
if os.path.exists(batch_file_path) and remove_source: | ||
os.remove(batch_file_path) | ||
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def search_and_replace_values(df: pd.DataFrame) -> pd.DataFrame: | ||
logging.info("Search and replacing values..") | ||
df.drop( | ||
df[df.settlement_date.astype(str).str.startswith("Trailer")].index, inplace=True | ||
) | ||
df["settlement_date"] = pd.to_datetime( | ||
df["settlement_date"].astype(str), errors="coerce" | ||
) | ||
df["total_shares"] = df["total_shares"].fillna(0).astype(int) | ||
df = df.replace( | ||
to_replace={ | ||
"share_price": {'"': ""}, | ||
} | ||
) | ||
df = df.replace( | ||
to_replace={"share_price": {"^.$": "", "\n": ""}, "company_name": {"\n": ""}}, | ||
regex=True, | ||
) | ||
return df | ||
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def reorder_headers(df: pd.DataFrame, headers: typing.List[str]) -> pd.DataFrame: | ||
logging.info("Transform: Reordering headers..") | ||
df = df[headers] | ||
return df | ||
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def upload_file_to_gcs( | ||
file_path: pathlib.Path, target_gcs_bucket: str, target_gcs_path: str | ||
) -> None: | ||
if os.path.exists(file_path): | ||
logging.info( | ||
f"Uploading output file to gs://{target_gcs_bucket}/{target_gcs_path}" | ||
) | ||
storage_client = storage.Client() | ||
bucket = storage_client.bucket(target_gcs_bucket) | ||
blob = bucket.blob(target_gcs_path) | ||
blob.upload_from_filename(file_path) | ||
else: | ||
logging.info( | ||
f"Cannot upload file to gs://{target_gcs_bucket}/{target_gcs_path} as it does not exist." | ||
) | ||
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if __name__ == "__main__": | ||
logging.getLogger().setLevel(logging.INFO) | ||
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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"], | ||
input_headers=json.loads(os.environ["INPUT_CSV_HEADERS"]), | ||
data_dtypes=json.loads(os.environ["DATA_DTYPES"]), | ||
output_headers=json.loads(os.environ["OUTPUT_CSV_HEADERS"]), | ||
) |
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datasets/sec_failure_to_deliver/pipelines/_images/run_csv_transform_kub/requirements.txt
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requests | ||
pandas | ||
google-cloud-storage |
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