diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml index 96cb87b..7e54daf 100644 --- a/.github/workflows/python-package.yml +++ b/.github/workflows/python-package.yml @@ -1,40 +1,31 @@ -# This workflow will install Python dependencies, run tests and lint with a variety of Python versions -# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python - +--- name: Python package - on: - push: - branches: [ "master" ] pull_request: - branches: [ "master" ] + branches: + - master + +permissions: + contents: write jobs: build: - runs-on: ubuntu-latest strategy: - fail-fast: false matrix: - python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"] - + python-version: + - "3.11" + - "3.12" + - "3.13" + - "3.14" steps: - - uses: actions/checkout@v4 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v3 - with: - python-version: ${{ matrix.python-version }} - - name: Install dependencies - run: | - python -m pip install --upgrade pip - python -m pip install flake8 pytest - if [ -f requirements.txt ]; then pip install -r requirements.txt; fi - - name: Lint with flake8 - run: | - # stop the build if there are Python syntax errors or undefined names - flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics - # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics - - name: Test with pytest - run: | - pytest + - uses: actions/checkout@v6 + - name: Install uv and set Python version + uses: astral-sh/setup-uv@08807647e7069bb48b6ef5acd8ec9567f424441b + with: + python-version: ${{ matrix.python-version }} + - name: Install dependencies + run: uv sync --dev + - name: Lint with Ruff + run: | + uv run ruff check . --fix diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..b0e8215 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,34 @@ +# syntax=docker/dockerfile:1 +FROM python:3.11-slim + +# Install uv from official image +COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/ + +# System dependencies + SQL Server ODBC driver +RUN apt-get update && \ + apt-get install -y --no-install-recommends curl gnupg2 ca-certificates unixodbc-dev build-essential && \ + curl -fsSL https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor -o /usr/share/keyrings/microsoft-prod.gpg && \ + echo "deb [signed-by=/usr/share/keyrings/microsoft-prod.gpg] https://packages.microsoft.com/debian/12/prod bookworm main" > /etc/apt/sources.list.d/mssql-release.list && \ + apt-get update && \ + ACCEPT_EULA=Y apt-get install -y --no-install-recommends msodbcsql18 && \ + DRIVER_PATH="$(ls /opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18*.so* | head -n 1)" && \ + printf "[SQL Server]\nDescription=Microsoft ODBC Driver 18 for SQL Server (alias)\nDriver=%s\nUsageCount=1\n" "$DRIVER_PATH" >> /etc/odbcinst.ini && \ + rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +ENV UV_PYTHON=python3.11 +ENV UV_SYSTEM_PYTHON=1 + +# Install dependencies first for better layer caching +COPY pyproject.toml ./ +COPY uv.lock ./ +RUN uv sync --frozen + +# Copy project files +COPY . . + +# Runtime default environment for main.py arg +ENV APP_ENV=hpc_dev + +CMD ["sh", "-c", "uv run python main.py --db"] diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..1727ced --- /dev/null +++ b/Makefile @@ -0,0 +1,101 @@ +#* Variables +SHELL := /usr/bin/env bash +PYTHON := python +PYTHONPATH := `pwd`/src + +#* INSTALL + +#* Install dependencies and package +.PHONY: install +install: + uv sync --all-extras --dev --frozen + +#* LINTING + +#* Check formatting +.PHONY: check-codestyle +check-codestyle: + uv run isort --diff --check-only --settings-path pyproject.toml ./ + uv run black --diff --check --config pyproject.toml ./ + uv run ruff check . + +#* Fix formatting +.PHONY: codestyle +codestyle: + uv run isort --settings-path pyproject.toml ./ + uv run black --fast --config pyproject.toml ./ + uv run ruff check . --fix + +# .PHONY: test +# test: +# uv run pytest tests/unit --cov=data_bridges_knots --cov-report=html +# uv run coverage-badge -o assets/images/coverage.svg -f + +#* Typing +.PHONY: mypy +mypy: + uv run mypy --config-file pyproject.toml ./ + +# .PHONY: check-safety +# check-safety: +# uv run bandit -r src + +#* All in one +.PHONY: lint +lint: test check-codestyle mypy + +#* DOCS + +# #* Documentation +# # Test +# .PHONY: docs-test +# docs-test: +# uv run python -m doctest data_bridges_knots/client.py + +#* DOCKER + +# Example: make docker-build VERSION=latest +# Example: make docker-build IMAGE=some_name VERSION=0.1.0 +.PHONY: docker-build +docker-build: + @echo Building docker $(IMAGE):$(VERSION) ... + docker build \ + -t $(IMAGE):$(VERSION) . \ + -f ./docker/Dockerfile --no-cache + +# Example: make docker-remove VERSION=latest +# Example: make docker-remove IMAGE=some_name VERSION=0.1.0 +.PHONY: docker-remove +docker-remove: + @echo Removing docker $(IMAGE):$(VERSION) ... + docker rmi -f $(IMAGE):$(VERSION) + + +#* CLEANING + +.PHONY: pycache-remove +pycache-remove: + find . | grep -E "(__pycache__|\.pyc|\.pyo$$)" | xargs rm -rf + +.PHONY: dsstore-remove +dsstore-remove: + find . | grep -E ".DS_Store" | xargs rm -rf + +.PHONY: mypycache-remove +mypycache-remove: + find . | grep -E ".mypy_cache" | xargs rm -rf + +.PHONY: ipynbcheckpoints-remove +ipynbcheckpoints-remove: + find . | grep -E ".ipynb_checkpoints" | xargs rm -rf + +.PHONY: pytestcache-remove +pytestcache-remove: + find . | grep -E ".pytest_cache" | xargs rm -rf + +.PHONY: build-remove +build-remove: + rm -rf build/ + +.PHONY: cleanup +cleanup: pycache-remove dsstore-remove mypycache-remove ipynbcheckpoints-remove pytestcache-remove \ No newline at end of file diff --git a/README.md b/README.md index 0828d53..3f6f46b 100644 --- a/README.md +++ b/README.md @@ -21,7 +21,7 @@ This is a Python CLI tool to query the [WFP Data Library API](https://datalib.va - Packages listed in `requirements.txt` ## Documentation -For more details on the Data Library API endpoints, see the [API documentation](http://docs.ckan.org/en/2.9/api/). +For more details on the Data Library API endpoints, see the [API documentation](http://docs.ckan.org/en/2.11/api/). ## Contributing Contributions to add more API querying/exporting functionality are welcome! diff --git a/datalibrary/__init__.py b/datalibrary/__init__.py index f839c6c..599de80 100644 --- a/datalibrary/__init__.py +++ b/datalibrary/__init__.py @@ -1,3 +1,9 @@ -from .extract import DataLibrary, get_survey_data, get_user_data, get_member_data, get_data +from .extract import ( + DataLibrary, + get_data, + get_member_data, + get_survey_data, + get_user_data, +) -__all__ = ["DataLibrary"] \ No newline at end of file +__all__ = ["DataLibrary"] diff --git a/datalibrary/extract.py b/datalibrary/extract.py index c2fe2eb..6024a32 100644 --- a/datalibrary/extract.py +++ b/datalibrary/extract.py @@ -1,40 +1,42 @@ -import requests import json import logging + import pandas as pd +import requests logger = logging.getLogger(__name__) BASE_URL = "https://datalib.vam.wfp.org/api/3/" ENDPOINTS = { -'users': 'action/user_list', -'all_surveys_information': 'action/current_package_list_with_resources', -'all_surveys_code': 'action/package_list', -'member_list': 'action/member_list', + "users": "action/user_list", + "all_surveys_information": "action/current_package_list_with_resources", + "all_surveys_code": "action/package_list", + "member_list": "action/member_list", } + class DataLibrary: """Class to query WFP Data Library API. -Attributes: - api_key (str): API key for authentication + Attributes: + api_key (str): API key for authentication -Methods: - get_users: Get list of Data Library users - get_surveys: Get list of survey codes - get_survey_info: Get info on all surveys - """ + Methods: + get_users: Get list of Data Library users + get_surveys: Get list of survey codes + get_survey_info: Get info on all surveys + """ def __init__(self, api_key): """Initialize DataLibrary instance. Args: api_key (str): API key for authentication - """ + """ self.api_key = api_key self.session = requests.Session() self._ua = "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:147.0) Gecko/20100101 Firefox/147.0" - + def get_response(self, url, params=None): """Send API request. @@ -45,14 +47,14 @@ def get_response(self, url, params=None): Returns: dict: API response """ - headers = {'Authorization': f'{self.api_key}', 'User-Agent': self._ua} + headers = {"Authorization": f"{self.api_key}", "User-Agent": self._ua} if params is None: params = {} elif isinstance(params, int): - params = {'limit': params} + params = {"limit": params} - logger.info(f'Querying {url} with params {params}') + logger.info(f"Querying {url} with params {params}") r = self.session.get(url, headers=headers, params=params) if r.status_code == 200: @@ -64,36 +66,40 @@ def get_response(self, url, params=None): def help(self): """Get basic information on the usage of the API.""" - print(f'\n---\n This library helps RAM users to query the Data Library API:{BASE_URL}\n') - print('You can get information about the following:') + print( + f"\n---\n This library helps RAM users to query the Data Library API:{BASE_URL}\n" + ) + print("You can get information about the following:") for k, v in ENDPOINTS.items(): info = k.replace("_", " ").capitalize() - print(f'{info} on endpoint {BASE_URL + v}') + print(f"{info} on endpoint {BASE_URL + v}") - print("\n---\n For documentation visit: http://docs.ckan.org/en/2.9/api/\n---\n") + print( + "\n---\n For documentation visit: http://docs.ckan.org/en/2.11/api/\n---\n" + ) def get_users(self): """Get list of users""" - url = BASE_URL + ENDPOINTS['users'] - response = self.get_response(url) + url = BASE_URL + ENDPOINTS["users"] + response = self.get_response(url) data = response["result"] return data def get_survey_list(self, limit=None): """Get package list""" - url = BASE_URL + ENDPOINTS['all_surveys_code'] - response = self.get_response(url, params=limit) + url = BASE_URL + ENDPOINTS["all_surveys_code"] + response = self.get_response(url, params=limit) data = response["result"] return data def get_surveys_with_resources(self, limit=None): """Get all surveys with country, type of survey and description""" - url = BASE_URL + ENDPOINTS['all_surveys_information'] - response = self.get_response(url, params=limit) + url = BASE_URL + ENDPOINTS["all_surveys_information"] + response = self.get_response(url, params=limit) data = response["result"] return data - + def get_member_list(self, id=None, object_type=None, capacity=None, limit=None): """Get list of members of a group. @@ -106,34 +112,35 @@ def get_member_list(self, id=None, object_type=None, capacity=None, limit=None): Returns: list: List of tuples containing (id, type, capacity) for each member. """ - url = BASE_URL + ENDPOINTS['member_list'] - params = {'id': id, 'object_type': object_type, 'limit': limit} + url = BASE_URL + ENDPOINTS["member_list"] + params = {"id": id, "object_type": object_type, "limit": limit} response = self.get_response(url, params=params) data = response.get("result", []) return data - + def __repr__(self): - return f'DataLibraryData({self.api_key})' + return f"DataLibraryData({self.api_key})" def __str__(self): - return f'The API key used in this DataLibraryData is {self.api_key}' + return f"The API key used in this DataLibraryData is {self.api_key}" def get_survey_data(client): - survey_list = client.get_survey_list() - total_surveys = len(survey_list) + survey_list = client.get_survey_list() + total_surveys = len(survey_list) - all_surveys = client.get_surveys_with_resources(limit=total_surveys) - all_surveys_df = pd.json_normalize(all_surveys) + all_surveys = client.get_surveys_with_resources(limit=total_surveys) + all_surveys_df = pd.json_normalize(all_surveys) - return all_surveys_df + return all_surveys_df def get_user_data(client): - users = client.get_users() - users_df = pd.DataFrame(users) + users = client.get_users() + users_df = pd.DataFrame(users) + + return users_df - return users_df def get_member_data(client, id=None): members = client.get_member_list(id=id) @@ -142,21 +149,23 @@ def get_member_data(client, id=None): def get_data(client): - survey_df = get_survey_data(client) - user_df = get_user_data(client) - - result = [] - container_ids = set(survey_df['organization.id']) - for container_id in container_ids: - container_members = get_member_data(client, id=container_id) - if container_members is not None: - container_members.insert(3, "container_id", container_id) # Check if container_members is not None - result.append(container_members) - # BUG: container id should be included as column, along with user_id - member_df = pd.concat(result, ignore_index=True) - - return survey_df, user_df, member_df + survey_df = get_survey_data(client) + user_df = get_user_data(client) + + result = [] + container_ids = set(survey_df["organization.id"]) + for container_id in container_ids: + container_members = get_member_data(client, id=container_id) + if container_members is not None: + container_members.insert( + 3, "container_id", container_id + ) # Check if container_members is not None + result.append(container_members) + # BUG: container id should be included as column, along with user_id + member_df = pd.concat(result, ignore_index=True) + + return survey_df, user_df, member_df if __name__ == "__main__": - pass \ No newline at end of file + pass diff --git a/datalibrary/load.py b/datalibrary/load.py index 0a76d4f..fc170d0 100644 --- a/datalibrary/load.py +++ b/datalibrary/load.py @@ -1,10 +1,10 @@ -import os -import pandas as pd -from sqlalchemy import create_engine -from dotenv import load_dotenv import logging +import os from datetime import date +from dotenv import load_dotenv +from sqlalchemy import create_engine + logger = logging.getLogger(__name__) load_dotenv() # take environment variables from .env. @@ -14,20 +14,25 @@ USERNAME = os.getenv("DB_USERNAME") PASSWORD = os.getenv("DB_PASSWORD") -conn_str = f'mssql+pyodbc://{USERNAME}:{PASSWORD}@{SERVER}/{DATABASE}?driver=ODBC+Driver+17+for+SQL+Server&Encrypt=yes&TrustServerCertificate=yes' +conn_str = f"mssql+pyodbc://{USERNAME}:{PASSWORD}@{SERVER}/{DATABASE}?driver=ODBC+Driver+18+for+SQL+Server&Encrypt=yes&TrustServerCertificate=yes" engine = create_engine(conn_str) + class ExcelExportError(Exception): pass -def load_data(data, table_name = 'table'): + +def load_data(data, table_name="table"): try: - data.to_sql(name=table_name, con=engine, if_exists='replace') + data.to_sql(name=table_name, con=engine, if_exists="replace") except Exception as e: logger.error(f"Error {e} when populating {table_name}") -def load_to_db(data: tuple, table_names = ("DL_Surveys", "DL_Resources", "DL_Users", "DL_Members")): - try: + +def load_to_db( + data: tuple, table_names=("DL_Surveys", "DL_Resources", "DL_Users", "DL_Members") +): + try: for df, table_name in zip(data, table_names): logger.info("Loading data to database") load_data(df, table_name) @@ -35,19 +40,19 @@ def load_to_db(data: tuple, table_names = ("DL_Surveys", "DL_Resources", "DL_Use logger.error(f"Error loading data: {e}") -def save_to_excel(data: tuple, filenames = ("surveys", "resources", "users", "members")): +def save_to_excel(data: tuple, filenames=("surveys", "resources", "users", "members")): # export survey list, survey information with resources and user list as csv folder = "output" today = str(date.today()).replace("-", "_") - for df, filename in zip(data, filenames): path = f"{folder}/{today}_{filename}.csv" try: df.to_csv(path) - except Exception as e: + except Exception: logger.error(f"Error saving {filename} to excel") continue + if __name__ == "__main__": pass diff --git a/datalibrary/transform.py b/datalibrary/transform.py index 39ff114..ba739da 100644 --- a/datalibrary/transform.py +++ b/datalibrary/transform.py @@ -1,169 +1,110 @@ -<<<<<<< HEAD -import pandas as pd -import json - - -SURVEY_COLUMNS_SELECTION = ['assessment_status', 'collection_method', 'creator_user_id', 'data_collector', 'description', 'end_date', 'id', 'metadata_created', 'metadata_modified', 'month', 'name', 'num_resources', 'organization_id', 'organization_title', 'organization_description', 'organization_created', 'owner_org', 'private', 'progress_status', 'start_date', 'survey_attributes', 'survey_category', 'survey_type', 'title', 'year', 'resources'] - -SURVEY_COLUMNS_RENAMING = {"id": "survey_id", "organization_id": "container_id", - "organization_title": "container_name", - "organization_description": "container_description", - "organization_created": "container_created", - "data_collector": "organization", "owner_org": "parent_container_id", - "title": "survey_title"} - -RESOURCES_COLUMNS_TO_DROP = ["resources", "restricted", "cache_last_updated", "cache_url", "revision_id", "url_type", "state", "resource_type", "mimetype_inner", "hash", "package_id"] - -def clean_column_names(df): - """Rename columns to be more readable""" - df.columns = df.columns.str.replace('.', '_') - return df - -def flatten_response(df: pd.DataFrame, col: str, _id: str) -> pd.DataFrame: - flat_list = [] - for _, row in df.iterrows(): - for r in row[col]: - flat_dict = {_id : row[_id]} - flat_dict.update(r) - flat_list.append(flat_dict) - - df = pd.DataFrame(flat_list) - return df - -def flatten_resources(df): - resources = df[["resources", "organization_id", "survey_id"]] - flat_resources = flatten_response(resources, "resources", "survey_id") - return flat_resources - -def normalize_restrictions(df): - """Normalize restricted column""" - try: - df['restricted'] = df['restricted'].apply(json.loads) - except TypeError: - pass - - restricted = pd.json_normalize(df["restricted"]) - return restricted - -def user_data_transform(df): - # Remove unnecessary columns from users table - users_columns_to_drop = ["apikey", "display_name", "about", "state", "image_url", "image_display_url"] - df = df.drop(columns=users_columns_to_drop) - return df - -def survey_data_transform(df): - df = clean_column_names(df) - df = df[SURVEY_COLUMNS_SELECTION] - df = df.rename(columns=SURVEY_COLUMNS_RENAMING) - return df - -def member_data_transform(df): - df = df.rename(columns={0: "user_id", 1: "type", 2: "capacity"}) - df = df[df.type.isin(["user"])] - df = df[["user_id", "capacity", "container_id"]] - return df - - -def transform(data: tuple) -> tuple: - """ - Transforms the input data tuple into a new tuple. - - Args: - data (tuple): A tuple containing the data to be transformed. - - Returns: - tuple: The transformed data. - """ - surveys, users, members = data - - surveys = survey_data_transform(surveys) - - # Flatten resources - resources = surveys[["resources", "container_id", "survey_id"]] - flat_resources = flatten_response(resources, "resources", "survey_id") - - # Remove unnecessary columns from survey table - surveys.drop(columns=["resources"], inplace=True) - full_resources = pd.merge(resources, flat_resources, on="survey_id") - - # Normalize restricted datasets - restricted = normalize_restrictions(full_resources) - full_resources = full_resources.join(restricted) - - - # Remove unnecessary columns from resource table - full_resources.drop(columns=RESOURCES_COLUMNS_TO_DROP, inplace=True) - - # Rename resource columns - resources_cols_renaming = { - "restricted-level": "access_level", - 'restricted-allowed_users': "allowed_users" - } - full_resources = full_resources.rename(columns=resources_cols_renaming) - - - # User table transformations - users = user_data_transform(users) - - # Member DF - members = member_data_transform(members) - - - return (surveys, full_resources, users, members) - -if __name__ == "__main__": -======= -import pandas as pd import json +import pandas as pd -SURVEY_COLUMNS_SELECTION = ['assessment_status', 'collection_method', 'creator_user_id', 'data_collector', 'description', 'end_date', 'id', 'metadata_created', 'metadata_modified', 'month', 'name', 'num_resources', 'organization_id', 'organization_title', 'organization_description', 'organization_created', 'owner_org', 'private', 'progress_status', 'start_date', 'survey_attributes', 'survey_category', 'survey_type', 'title', 'year', 'resources'] - -SURVEY_COLUMNS_RENAMING = {"id": "survey_id", "organization_id": "container_id", - "organization_title": "container_name", - "organization_description": "container_description", - "organization_created": "container_created", - "data_collector": "organization", "owner_org": "parent_container_id", - "title": "survey_title"} +SURVEY_COLUMNS_SELECTION = [ + "assessment_status", + "collection_method", + "creator_user_id", + "data_collector", + "description", + "end_date", + "id", + "metadata_created", + "metadata_modified", + "month", + "name", + "num_resources", + "organization_id", + "organization_title", + "organization_description", + "organization_created", + "owner_org", + "private", + "progress_status", + "start_date", + "survey_attributes", + "survey_category", + "survey_type", + "title", + "year", + "resources", +] + +SURVEY_COLUMNS_RENAMING = { + "id": "survey_id", + "organization_id": "container_id", + "organization_title": "container_name", + "organization_description": "container_description", + "organization_created": "container_created", + "data_collector": "organization", + "owner_org": "parent_container_id", + "title": "survey_title", +} + +RESOURCES_COLUMNS_TO_DROP = [ + "resources", + "restricted", + "cache_last_updated", + "cache_url", + "revision_id", + "url_type", + "state", + "resource_type", + "mimetype_inner", + "hash", + "package_id", +] -RESOURCES_COLUMNS_TO_DROP = ["resources", "restricted", "cache_last_updated", "cache_url", "revision_id", "url_type", "state", "resource_type", "mimetype_inner", "hash", "package_id"] def clean_column_names(df): """Rename columns to be more readable""" - df.columns = df.columns.str.replace('.', '_') + df.columns = df.columns.str.replace(".", "_") return df + def flatten_response(df: pd.DataFrame, col: str, _id: str) -> pd.DataFrame: flat_list = [] for _, row in df.iterrows(): for r in row[col]: - flat_dict = {_id : row[_id]} + flat_dict = {_id: row[_id]} flat_dict.update(r) flat_list.append(flat_dict) - + df = pd.DataFrame(flat_list) return df + def flatten_resources(df): resources = df[["resources", "organization_id", "survey_id"]] flat_resources = flatten_response(resources, "resources", "survey_id") return flat_resources + def normalize_restrictions(df): """Normalize restricted column""" try: - df['restricted'] = df['restricted'].apply(json.loads) + df["restricted"] = df["restricted"].apply(json.loads) except TypeError: pass - + restricted = pd.json_normalize(df["restricted"]) return restricted + def user_data_transform(df): - # Remove unnecessary columns from users table - users_columns_to_drop = ["display_name", "about", "state", "image_url", "image_display_url"] + # Remove unnecessary columns from users table + users_columns_to_drop = [ + "apikey", + "display_name", + "about", + "state", + "image_url", + "image_display_url", + ] df = df.drop(columns=users_columns_to_drop) - return df + return df + def survey_data_transform(df): df = clean_column_names(df) @@ -171,6 +112,7 @@ def survey_data_transform(df): df = df.rename(columns=SURVEY_COLUMNS_RENAMING) return df + def member_data_transform(df): df = df.rename(columns={0: "user_id", 1: "type", 2: "capacity"}) df = df[df.type.isin(["user"])] @@ -197,34 +139,31 @@ def transform(data: tuple) -> tuple: flat_resources = flatten_response(resources, "resources", "survey_id") # Remove unnecessary columns from survey table - surveys.drop(columns=["resources"], inplace=True) + surveys.drop(columns=["resources"], inplace=True) full_resources = pd.merge(resources, flat_resources, on="survey_id") # Normalize restricted datasets restricted = normalize_restrictions(full_resources) full_resources = full_resources.join(restricted) - # Remove unnecessary columns from resource table full_resources.drop(columns=RESOURCES_COLUMNS_TO_DROP, inplace=True) # Rename resource columns resources_cols_renaming = { "restricted-level": "access_level", - 'restricted-allowed_users': "allowed_users" + "restricted-allowed_users": "allowed_users", } full_resources = full_resources.rename(columns=resources_cols_renaming) - - # User table transformations + # User table transformations users = user_data_transform(users) # Member DF members = member_data_transform(members) - return (surveys, full_resources, users, members) + if __name__ == "__main__": ->>>>>>> master - pass \ No newline at end of file + pass diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..fdeb910 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,19 @@ + +services: + data-library-pipeline: # you can rename this to your new pipeline name + build: + context: . + dockerfile: Dockerfile + + image: data-library-pipeline:latest # just a name for the built image + + environment: + APP_ENV: ${APP_ENV:-} + + DATALIB_API_KEY: ${DATALIB_API_KEY:-} + SERVER: ${SERVER:-} + DB_NAME: ${DB_NAME:-} + DB_USERNAME: ${DB_USERNAME:-} + DB_PASSWORD: ${DB_PASSWORD:-} + + command: ["sh", "-c", "uv run python main.py --db"] diff --git a/main.py b/main.py index 8fadd67..f26bc1a 100644 --- a/main.py +++ b/main.py @@ -1,13 +1,15 @@ -import pdb -from dotenv import load_dotenv -import os import argparse +import os + +from dotenv import load_dotenv + from datalibrary.extract import DataLibrary, get_data +from datalibrary.load import load_to_db, save_to_excel from datalibrary.transform import transform -from datalibrary.load import save_to_excel, load_to_db load_dotenv() # take environment variables from .env. + def main(): """ Executes the ETL (Extract, Transform, Load) process to fetch data from VAM Data Library, process the data, and load it into a database and/or save it to an Excel file. @@ -21,9 +23,11 @@ def main(): processed_data = transform(dl_api_data) # Parse command-line arguments - parser = argparse.ArgumentParser(description='Export Data Library data to CSV or database.') - parser.add_argument('--csv', action='store_true', help='Export data to CSV files') - parser.add_argument('--db', action='store_true', help='Upload data to a database') + parser = argparse.ArgumentParser( + description="Export Data Library data to CSV or database." + ) + parser.add_argument("--csv", action="store_true", help="Export data to CSV files") + parser.add_argument("--db", action="store_true", help="Upload data to a database") args = parser.parse_args() if args.csv: @@ -37,7 +41,6 @@ def main(): if not args.csv and not args.db: print("No action specified. 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