From 29a077d6eddc5a4a4202207089291cd52493cb86 Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Wed, 22 Jan 2025 22:52:12 +0100 Subject: [PATCH 1/7] BDI assignment s1 --- bdi_api/s1/exercise.py | 175 +++- poetry.lock | 1949 ++++++++++++++++++++++++++-------------- pyproject.toml | 3 + 3 files changed, 1433 insertions(+), 694 deletions(-) diff --git a/bdi_api/s1/exercise.py b/bdi_api/s1/exercise.py index ce5f7848..5d693d0f 100644 --- a/bdi_api/s1/exercise.py +++ b/bdi_api/s1/exercise.py @@ -1,9 +1,17 @@ import os +import requests +import pandas as pd +from typing import List +from urllib.parse import urljoin +import json +from tqdm import tqdm from typing import Annotated +from bs4 import BeautifulSoup from fastapi import APIRouter, status from fastapi.params import Query - +from fastapi.responses import FileResponse +from fastapi import HTTPException from bdi_api.settings import Settings settings = Settings() @@ -13,9 +21,10 @@ status.HTTP_404_NOT_FOUND: {"description": "Not found"}, status.HTTP_422_UNPROCESSABLE_ENTITY: {"description": "Something is wrong with the request"}, }, - prefix="/api/s1", + prefix="/api/s1", #download postman tags=["s1"], ) +#test 1 @s1.post("/aircraft/download") @@ -52,6 +61,52 @@ def download_data( base_url = settings.source_url + "/2023/11/01/" # TODO Implement download + # Step 1: I will check to ensure the download directory exists and create it if it doesn't + os.makedirs(download_dir, exist_ok=True) + + # Clean the download directory for existing files + for file in os.listdir(download_dir): + file_path = os.path.join(download_dir, file) + if os.path.isfile(file_path): + os.remove(file_path) + + + try: + # Get list of files from the Swagger UI link + response = requests.get(base_url) + # Added error handling for HTTP status + response.raise_for_status() + + # Parse the HTML content with BeautifulSoup + soup = BeautifulSoup(response.text, 'html.parser') + files = [ + a['href'] for a in soup.find_all('a') + if a['href'].endswith('.json.gz') + ][:file_limit] # Apply the file limit of 10 + + # A count of successfully downloaded files + downloaded_count = 0 + for file_name in tqdm(files, desc="Downloading files"): + file_url = urljoin(base_url, file_name) + response = requests.get(file_url, stream=True) + + if response.status_code == 200: + file_path = os.path.join(download_dir, file_name[:-3]) + with open(file_path, 'wb') as f: + f.write(response.content) + downloaded_count += 1 + else: + print(f"Failed download {file_name}") + + + return f"Downloaded {downloaded_count} files to {download_dir}" + + except requests.RequestException as e: + return f"Error accessing URL: {str(e)}" + except Exception as e: + return f"Error during download: {str(e)}" + + return "OK" @@ -75,6 +130,60 @@ def prepare_data() -> str: Keep in mind that we are downloading a lot of small files, and some libraries might not work well with this! """ # TODO + prepared_directory = os.path.join(settings.prepared_dir, "day=20231101") + raw_data_dir = os.path.join(settings.raw_dir, "day=20231101") + + # Create directory if it doesn't exist + os.makedirs(prepared_directory, exist_ok=True) + + # Clean existing files + for file in os.listdir(prepared_directory): + file_path = os.path.join(prepared_directory, file) + if os.path.isfile(file_path): + os.remove(file_path) + + try: + aircraft_data = [] + for file in os.listdir(raw_data_dir): + if file.endswith('.json'): + file_path = os.path.join(raw_data_dir, file) + with open(file_path, 'r') as f: + data = json.load(f) + if "aircraft" in data: + df = pd.DataFrame(data['aircraft']) + # Add timestamp directly to DataFrame + df['timestamp'] = data['now'] + aircraft_data.append(df) + + # Concatenate all the data + processed_data = pd.concat(aircraft_data, ignore_index=True) + + # Select required columns + processed_data = processed_data[['hex', 'r', 'type', 't', 'lat', 'lon', 'alt_baro', 'gs', 'emergency','timestamp']] + + # Rename columns + processed_data = processed_data.rename(columns={ + 'hex': 'icao', + 'r': 'registration', + 't': 'type', + 'alt_baro': 'altitude_baro', + 'gs': 'ground_speed', + 'emergency': 'had_emergency' + }) + # Drop rows with NaN values in 'icao', 'registration', and 'type' + processed_data = processed_data.dropna(subset=['icao', 'registration', 'type']) + # Process emergency flags + emergency = ['general', 'lifeguard', 'minfuel', 'nordo', 'unlawful', 'downed', 'reserved'] + processed_data['had_emergency'] = processed_data['had_emergency'].apply(lambda x: x in emergency) + + # Save as CSV + processed_data.to_csv(os.path.join(prepared_directory, 'prepared_data.csv'), index=False) + + print(processed_data) + return f"Data prepared and saved to {prepared_directory}" + + except Exception as e: + return f"An error has occurred during data preparation: {str(e)}" return "OK" @@ -84,7 +193,26 @@ def list_aircraft(num_results: int = 100, page: int = 0) -> list[dict]: icao asc """ # TODO - return [{"icao": "0d8300", "registration": "YV3382", "type": "LJ31"}] + # This variable directly constructs the full path to the specific and only file with all the prepared data + prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") + if not os.path.exists(prepared_directory): + return [] + + if not os.path.exists(prepared_directory): + return [] + + sorted_aircraft = pd.read_csv(prepared_directory) + # Deduplicate values and sort by 'icao' + sorted_aircraft = sorted_aircraft[['icao', 'registration', 'type']].drop_duplicates().sort_values(by='icao') + + start = page * num_results + end = start + num_results + + result = sorted_aircraft.iloc[start:end].to_dict(orient='records') + print(result) + return result + + return [{"icao": "0d8300", "registration": "YV3382", "type": "LJ31"}] # Done @s1.get("/aircraft/{icao}/positions") @@ -93,6 +221,21 @@ def get_aircraft_position(icao: str, num_results: int = 1000, page: int = 0) -> If an aircraft is not found, return an empty list. """ # TODO implement and return a list with dictionaries with those values. + + # Calculate the start index: start_index = page * limit + start_index = page * num_results + # Calculate the end index: end_index = (page + 1) * limit + end_index = (page + 1) * num_results + prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") + if not os.path.exists(prepared_directory): + return [] + + df = pd.read_csv(prepared_directory) + # Dataframe with subset of rows for the requested 'icao' + filtered_df = df[df["icao"] == icao].sort_values(by="timestamp") + # Slice the DataFrame according to the page and number of results per page + return filtered_df.iloc[page * num_results:(page + 1) * num_results][["timestamp", "lat", "lon"]].to_dict(orient="records") + return [{"timestamp": 1609275898.6, "lat": 30.404617, "lon": -86.476566}] @@ -105,4 +248,30 @@ def get_aircraft_statistics(icao: str) -> dict: * had_emergency """ # TODO Gather and return the correct statistics for the requested aircraft + prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") + if not os.path.exists(prepared_directory): + return {} + + df = pd.read_csv(prepared_directory) + df = df[df['icao'] == icao] + + if df.empty: + return {} + + # Convert numpy types to Python native types + # Convert numpy.bool_ to Python bool + max_altitude_baro = float(df['altitude_baro'].max()) if not pd.isna(df['altitude_baro'].max()) else None + max_ground_speed = float(df['ground_speed'].max()) if not pd.isna(df['ground_speed'].max()) else None + had_emergency = bool(df['had_emergency'].any()) + + print({ + "max_altitude_baro": max_altitude_baro, + "max_ground_speed": max_ground_speed, + "had_emergency": had_emergency + }) + return { + "max_altitude_baro": max_altitude_baro, + "max_ground_speed": max_ground_speed, + "had_emergency": had_emergency + } return {"max_altitude_baro": 300000, "max_ground_speed": 493, "had_emergency": False} diff --git a/poetry.lock b/poetry.lock index 09c0a0f8..86686853 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. [[package]] name = "annotated-types" @@ -6,6 +6,8 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -13,13 +15,15 @@ files = [ [[package]] name = "anyio" -version = "4.7.0" +version = "4.8.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352"}, - {file = "anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48"}, + {file = "anyio-4.8.0-py3-none-any.whl", hash = "sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a"}, + {file = "anyio-4.8.0.tar.gz", hash = "sha256:1d9fe889df5212298c0c0723fa20479d1b94883a2df44bd3897aa91083316f7a"}, ] [package.dependencies] @@ -30,7 +34,7 @@ typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} [package.extras] doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] [[package]] @@ -39,6 +43,8 @@ version = "1.3.0" description = "Better dates & times for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"}, {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"}, @@ -58,6 +64,8 @@ version = "3.8.1" description = "ASGI specs, helper code, and adapters" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "asgiref-3.8.1-py3-none-any.whl", hash = "sha256:3e1e3ecc849832fe52ccf2cb6686b7a55f82bb1d6aee72a58826471390335e47"}, {file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"}, @@ -71,19 +79,21 @@ tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"] [[package]] name = "attrs" -version = "24.2.0" +version = "24.3.0" description = "Classes Without Boilerplate" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - 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python_version >= \"3.12\"" files = [ - {file = "smmap-5.0.1-py3-none-any.whl", hash = "sha256:e6d8668fa5f93e706934a62d7b4db19c8d9eb8cf2adbb75ef1b675aa332b69da"}, - {file = "smmap-5.0.1.tar.gz", hash = "sha256:dceeb6c0028fdb6734471eb07c0cd2aae706ccaecab45965ee83f11c8d3b1f62"}, + {file = "smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e"}, + {file = "smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5"}, ] [[package]] @@ -2853,6 +3311,8 @@ version = "1.3.1" description = "Sniff out which async library your code is running under" optional = false python-versions = ">=3.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"}, {file = "sniffio-1.3.1.tar.gz", hash = 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{file = "starlette_testclient-0.4.1.tar.gz", hash = "sha256:9e993ffe12fab45606116257813986612262fe15c1bb6dc9e39cc68693ac1fc5"}, @@ -2908,6 +3387,8 @@ version = "2.2.1" description = "A lil' TOML parser" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, @@ -2945,21 +3426,48 @@ files = [ [[package]] name = "tomli-w" -version = "1.1.0" +version = "1.2.0" description = "A lil' TOML writer" optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "tomli_w-1.2.0-py3-none-any.whl", hash = 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"platform_system == \"Windows\""} + +[package.extras] +dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"] +discord = ["requests"] +notebook = ["ipywidgets (>=6)"] +slack = ["slack-sdk"] +telegram = ["requests"] + [[package]] name = "typer" version = "0.15.1" description = "Typer, build great CLIs. Easy to code. Based on Python type hints." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "typer-0.15.1-py3-none-any.whl", hash = "sha256:7994fb7b8155b64d3402518560648446072864beefd44aa2dc36972a5972e847"}, {file = "typer-0.15.1.tar.gz", hash = "sha256:a0588c0a7fa68a1978a069818657778f86abe6ff5ea6abf472f940a08bfe4f0a"}, @@ -2977,6 +3485,8 @@ version = "2.9.0.20241206" description = "Typing stubs for python-dateutil" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "types_python_dateutil-2.9.0.20241206-py3-none-any.whl", hash = "sha256:e248a4bc70a486d3e3ec84d0dc30eec3a5f979d6e7ee4123ae043eedbb987f53"}, {file = "types_python_dateutil-2.9.0.20241206.tar.gz", hash = "sha256:18f493414c26ffba692a72369fea7a154c502646301ebfe3d56a04b3767284cb"}, @@ -2988,17 +3498,34 @@ version = "4.12.2" description = 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version = "1.21.0" description = "OpenTelemetry Python distribution for Uptrace" optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "uptrace-1.21.0-py3-none-any.whl", hash = "sha256:5644f8a8f10c52b70caeafbc34e74b2eb9ef5a76847bc73c0d3013399094513d"}, {file = "uptrace-1.21.0.tar.gz", hash = "sha256:5245fe468830eae48175f4e5e8f2355b173bdb2875c8c81c168762ba4a624003"}, @@ -3016,6 +3543,8 @@ version = "1.3.0" description = "RFC 6570 URI Template Processor" optional = false python-versions = ">=3.7" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"}, {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"}, @@ -3030,6 +3559,8 @@ version = "1.26.20" description = 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hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, @@ -3527,6 +4094,6 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", type = ["pytest-mypy"] [metadata] -lock-version = "2.0" +lock-version = "2.1" python-versions = ">=3.9,<4.0" -content-hash = "4bf634c1411d0e0340de6002ba995c083208c61a3d034de6b223ac93b9fd74a9" +content-hash = "f84fce77860c179dc835fdf9c00d6e247230592ffc3c98744a86e9d2130e773c" diff --git a/pyproject.toml b/pyproject.toml index 32d2bf3c..485e4a96 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,6 +29,9 @@ opentelemetry-api = "1.21.0" opentelemetry-sdk = "1.21.0" opentelemetry-instrumentation-fastapi = "0.42b0" # Add your dependencies here +tqdm = "^4.67.1" +pandas = "^2.2.3" +beautifulsoup4 = "^4.12.3" [tool.poetry.group.dev.dependencies] pre-commit = "^3.5.0" From 09b3a2664da447013442db2319696120e538cc54 Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Wed, 22 Jan 2025 23:35:50 +0100 Subject: [PATCH 2/7] BDI s1 optimized version --- bdi_api/s1/exercise.py | 106 ++++++++++++++++++++++++++--------------- 1 file changed, 67 insertions(+), 39 deletions(-) diff --git a/bdi_api/s1/exercise.py b/bdi_api/s1/exercise.py index 5d693d0f..66a017b3 100644 --- a/bdi_api/s1/exercise.py +++ b/bdi_api/s1/exercise.py @@ -137,11 +137,12 @@ def prepare_data() -> str: os.makedirs(prepared_directory, exist_ok=True) # Clean existing files - for file in os.listdir(prepared_directory): + for file in os.listdir(prepared_directory): file_path = os.path.join(prepared_directory, file) if os.path.isfile(file_path): os.remove(file_path) + # The code reads JSON files from the raw data directory and processes them into Dataframes try: aircraft_data = [] for file in os.listdir(raw_data_dir): @@ -149,38 +150,47 @@ def prepare_data() -> str: file_path = os.path.join(raw_data_dir, file) with open(file_path, 'r') as f: data = json.load(f) - if "aircraft" in data: + if "aircraft" in data: df = pd.DataFrame(data['aircraft']) - # Add timestamp directly to DataFrame - df['timestamp'] = data['now'] + # Add timestamp directly to DataFrame + df['timestamp'] = data['now'] aircraft_data.append(df) - # Concatenate all the data + if not aircraft_data: + return "No aircraft data found." + + # All DataFrames are concatenated into a single Dataframe processed_data = pd.concat(aircraft_data, ignore_index=True) - + # Select required columns - processed_data = processed_data[['hex', 'r', 'type', 't', 'lat', 'lon', 'alt_baro', 'gs', 'emergency','timestamp']] - + processed_data = processed_data[['hex', 'r', 'type', 't', 'lat', 'lon', 'alt_baro', 'gs', 'emergency', 'timestamp']] + # Rename columns processed_data = processed_data.rename(columns={ - 'hex': 'icao', - 'r': 'registration', - 't': 'type', + 'hex': 'icao', + 'r': 'registration', + 't': 'type', 'alt_baro': 'altitude_baro', 'gs': 'ground_speed', 'emergency': 'had_emergency' }) + # Drop rows with NaN values in 'icao', 'registration', and 'type' processed_data = processed_data.dropna(subset=['icao', 'registration', 'type']) + # Process emergency flags - emergency = ['general', 'lifeguard', 'minfuel', 'nordo', 'unlawful', 'downed', 'reserved'] - processed_data['had_emergency'] = processed_data['had_emergency'].apply(lambda x: x in emergency) - + emergency_flags = {'general', 'lifeguard', 'minfuel', 'nordo', 'unlawful', 'downed', 'reserved'} + processed_data['had_emergency'] = processed_data['had_emergency'].apply(lambda x: x in emergency_flags) + + # Remove rows with any NaN values + processed_data = processed_data.dropna() + # Save as CSV - processed_data.to_csv(os.path.join(prepared_directory, 'prepared_data.csv'), index=False) + output_file = os.path.join(prepared_directory, 'prepared_data.csv') + processed_data.to_csv(output_file, index=False) print(processed_data) - return f"Data prepared and saved to {prepared_directory}" + return f"Data prepared and saved to {output_file}" except Exception as e: return f"An error has occurred during data preparation: {str(e)}" @@ -248,30 +258,48 @@ def get_aircraft_statistics(icao: str) -> dict: * had_emergency """ # TODO Gather and return the correct statistics for the requested aircraft - prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") - if not os.path.exists(prepared_directory): + data_file = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") + + # Check if the file exists + if not os.path.exists(data_file): return {} - df = pd.read_csv(prepared_directory) - df = df[df['icao'] == icao] + try: + # Read the CSV file into a DataFrame + df = pd.read_csv(data_file) + + # Filter the DataFrame by 'icao' + df = df[df['icao'] == icao] + + # Check if the filtered DataFrame is empty + if df.empty: + return {} + + # Remove rows with NaN values in relevant columns + df = df.dropna(subset=['altitude_baro', 'ground_speed', 'had_emergency']) + + # Calculate statistics + max_altitude_baro = df['altitude_baro'].max() + max_ground_speed = df['ground_speed'].max() + had_emergency = df['had_emergency'].any() + + # Convert numpy types to Python native types + max_altitude_baro = float(max_altitude_baro) if not pd.isna(max_altitude_baro) else None + max_ground_speed = float(max_ground_speed) if not pd.isna(max_ground_speed) else None + had_emergency = bool(had_emergency) # Convert numpy.bool_ to Python bool + + # Return the results + return { + "max_altitude_baro": max_altitude_baro, + "max_ground_speed": max_ground_speed, + "had_emergency": had_emergency + } + except Exception as e: + return {"error": str(e)} - if df.empty: - return {} +# Example usage +result = get_aircraft_statistics("some_icao_code") +print(result) - # Convert numpy types to Python native types - # Convert numpy.bool_ to Python bool - max_altitude_baro = float(df['altitude_baro'].max()) if not pd.isna(df['altitude_baro'].max()) else None - max_ground_speed = float(df['ground_speed'].max()) if not pd.isna(df['ground_speed'].max()) else None - had_emergency = bool(df['had_emergency'].any()) - - print({ - "max_altitude_baro": max_altitude_baro, - "max_ground_speed": max_ground_speed, - "had_emergency": had_emergency - }) - return { - "max_altitude_baro": max_altitude_baro, - "max_ground_speed": max_ground_speed, - "had_emergency": had_emergency - } - return {"max_altitude_baro": 300000, "max_ground_speed": 493, "had_emergency": False} +# This line should be removed or commented out as it is outside of any function or class +# return {"max_altitude_baro": 300000, "max_ground_speed": 493, "had_emergency": False} From 185c8ed07845fb2530bdb8a856917174289eace3 Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Tue, 25 Feb 2025 16:15:46 +0100 Subject: [PATCH 3/7] s4 and pytests --- bdi_api/s1/exercise.py | 14 -------------- bdi_api/s4/exercise.py | 1 - 2 files changed, 15 deletions(-) diff --git a/bdi_api/s1/exercise.py b/bdi_api/s1/exercise.py index 66a017b3..e57eacf3 100644 --- a/bdi_api/s1/exercise.py +++ b/bdi_api/s1/exercise.py @@ -1,13 +1,7 @@ -import os -import requests -import pandas as pd -from typing import List -from urllib.parse import urljoin import json from tqdm import tqdm from typing import Annotated from bs4 import BeautifulSoup - from fastapi import APIRouter, status from fastapi.params import Query from fastapi.responses import FileResponse @@ -70,7 +64,6 @@ def download_data( if os.path.isfile(file_path): os.remove(file_path) - try: # Get list of files from the Swagger UI link response = requests.get(base_url) @@ -97,16 +90,11 @@ def download_data( downloaded_count += 1 else: print(f"Failed download {file_name}") - - return f"Downloaded {downloaded_count} files to {download_dir}" - except requests.RequestException as e: return f"Error accessing URL: {str(e)}" except Exception as e: return f"Error during download: {str(e)}" - - return "OK" @@ -234,7 +222,6 @@ def get_aircraft_position(icao: str, num_results: int = 1000, page: int = 0) -> # Calculate the start index: start_index = page * limit start_index = page * num_results - # Calculate the end index: end_index = (page + 1) * limit end_index = (page + 1) * num_results prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") if not os.path.exists(prepared_directory): @@ -288,7 +275,6 @@ def get_aircraft_statistics(icao: str) -> dict: max_ground_speed = float(max_ground_speed) if not pd.isna(max_ground_speed) else None had_emergency = bool(had_emergency) # Convert numpy.bool_ to Python bool - # Return the results return { "max_altitude_baro": max_altitude_baro, "max_ground_speed": max_ground_speed, diff --git a/bdi_api/s4/exercise.py b/bdi_api/s4/exercise.py index 7b5a9a94..2e32469d 100644 --- a/bdi_api/s4/exercise.py +++ b/bdi_api/s4/exercise.py @@ -39,7 +39,6 @@ def download_data( base_url = settings.source_url + "/2023/11/01/" s3_bucket = settings.s3_bucket s3_prefix_path = "raw/day=20231101/" - # TODO return "OK" From 2c2ba5c64bb5841c214394d623ff2a5d5a4531e5 Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Tue, 25 Feb 2025 19:57:40 +0100 Subject: [PATCH 4/7] S4_exercise.py and tests_s4.py -final --- arkandrea.pem | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 arkandrea.pem diff --git a/arkandrea.pem b/arkandrea.pem new file mode 100644 index 00000000..129ebb54 --- /dev/null +++ b/arkandrea.pem @@ -0,0 +1,27 @@ +-----BEGIN RSA PRIVATE KEY----- +MIIEowIBAAKCAQEAq9XKY3QQKMuZEJSC6Bu79NY/Yk7R39fHND7Lk8D+LUEVWV+8 +cArWjNftXDyCs1r696Ge5wdNVAa+B1yT3638JeRrjRD5yb1y/0Qb6iBekFBHSZki +HYKnMNEN3ngJMS458j1Gbp3u8VIOYbNsmgW+7NUaIH06UCdikPtchZ8HfLDBJjy2 +K72nAd9PXXOnuyJd0wz+tlhswBIhbDA9KDuypVq/Xa6GJVc0OuXTeuTlJTLk2GOY +nVGBzIRIzOJyUq7W2chZbpCB1rNF2f3VqrrD69XCcK0voUojlYdbeez/dSWzcahr 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+23zyM4jbY5kiag4HB4ruvEFVZ90mP/ksGFF28seD+lAcwudym97dg7vOVQHMabAz +j6P4xinK7sMcDCQYbfMueNnTA2AafdQtiNkakWUA3/TZEJYCe1jQSO02IwyRjInx +bO5vSQKBgBBlzT4foWvOB//a5II4egPbNkiHtvZfABaor4qxkGg7tkGXjc1EDAB4 +aS1/+IjuLZ+kfnIDURMndWz38uSfQ5awKXUi5lFJku46EebIFLQ7C09KDyjnsRvs +HEzgUYpxPS4+ja9X2C7R8rX4+fV4e6XTXvaGudSAzlQ3Y0MpxYos +-----END RSA PRIVATE KEY----- \ No newline at end of file From 756d3632443dda77d07753e1410f7e537a139e27 Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Tue, 25 Feb 2025 22:01:21 +0100 Subject: [PATCH 5/7] s1_revised --- bdi_api/s1/exercise.py | 138 +++++++++++++++++++++++------------------ 1 file changed, 77 insertions(+), 61 deletions(-) diff --git a/bdi_api/s1/exercise.py b/bdi_api/s1/exercise.py index e57eacf3..7fa9eefd 100644 --- a/bdi_api/s1/exercise.py +++ b/bdi_api/s1/exercise.py @@ -1,11 +1,15 @@ import json -from tqdm import tqdm +import os from typing import Annotated +from urllib.parse import urljoin + +import pandas as pd +import requests from bs4 import BeautifulSoup from fastapi import APIRouter, status from fastapi.params import Query -from fastapi.responses import FileResponse -from fastapi import HTTPException +from tqdm import tqdm + from bdi_api.settings import Settings settings = Settings() @@ -15,10 +19,10 @@ status.HTTP_404_NOT_FOUND: {"description": "Not found"}, status.HTTP_422_UNPROCESSABLE_ENTITY: {"description": "Something is wrong with the request"}, }, - prefix="/api/s1", #download postman + prefix="/api/s1", # download postman tags=["s1"], ) -#test 1 +# test 1 @s1.post("/aircraft/download") @@ -61,32 +65,31 @@ def download_data( # Clean the download directory for existing files for file in os.listdir(download_dir): file_path = os.path.join(download_dir, file) - if os.path.isfile(file_path): + if os.path.isfile(file_path): os.remove(file_path) try: # Get list of files from the Swagger UI link response = requests.get(base_url) # Added error handling for HTTP status - response.raise_for_status() - + response.raise_for_status() + # Parse the HTML content with BeautifulSoup - soup = BeautifulSoup(response.text, 'html.parser') - files = [ - a['href'] for a in soup.find_all('a') - if a['href'].endswith('.json.gz') - ][:file_limit] # Apply the file limit of 10 - + soup = BeautifulSoup(response.text, "html.parser") + files = [a["href"] for a in soup.find_all("a") if a["href"].endswith(".json.gz")][ + :file_limit + ] # Apply the file limit of 10 + # A count of successfully downloaded files downloaded_count = 0 for file_name in tqdm(files, desc="Downloading files"): file_url = urljoin(base_url, file_name) response = requests.get(file_url, stream=True) - + if response.status_code == 200: file_path = os.path.join(download_dir, file_name[:-3]) - with open(file_path, 'wb') as f: - f.write(response.content) + with open(file_path, "wb") as f: # add data into s3 + f.write(response.content) # potentially change here downloaded_count += 1 else: print(f"Failed download {file_name}") @@ -136,14 +139,14 @@ def prepare_data() -> str: for file in os.listdir(raw_data_dir): if file.endswith('.json'): file_path = os.path.join(raw_data_dir, file) - with open(file_path, 'r') as f: + with open(file_path) as f: data = json.load(f) if "aircraft" in data: - df = pd.DataFrame(data['aircraft']) + df = pd.DataFrame(data["aircraft"]) # Add timestamp directly to DataFrame - df['timestamp'] = data['now'] + df["timestamp"] = data["now"] aircraft_data.append(df) - + if not aircraft_data: return "No aircraft data found." @@ -151,30 +154,34 @@ def prepare_data() -> str: processed_data = pd.concat(aircraft_data, ignore_index=True) # Select required columns - processed_data = processed_data[['hex', 'r', 'type', 't', 'lat', 'lon', 'alt_baro', 'gs', 'emergency', 'timestamp']] + processed_data = processed_data[ + ["hex", "r", "type", "t", "lat", "lon", "alt_baro", "gs", "emergency", "timestamp"] + ] # Rename columns - processed_data = processed_data.rename(columns={ - 'hex': 'icao', - 'r': 'registration', - 't': 'type', - 'alt_baro': 'altitude_baro', - 'gs': 'ground_speed', - 'emergency': 'had_emergency' - }) + processed_data = processed_data.rename( + columns={ + "hex": "icao", + "r": "registration", + "t": "type", + "alt_baro": "altitude_baro", + "gs": "ground_speed", + "emergency": "had_emergency", + } + ) # Drop rows with NaN values in 'icao', 'registration', and 'type' - processed_data = processed_data.dropna(subset=['icao', 'registration', 'type']) + processed_data = processed_data.dropna(subset=["icao", "registration", "type"]) # Process emergency flags - emergency_flags = {'general', 'lifeguard', 'minfuel', 'nordo', 'unlawful', 'downed', 'reserved'} - processed_data['had_emergency'] = processed_data['had_emergency'].apply(lambda x: x in emergency_flags) + emergency_flags = {"general", "lifeguard", "minfuel", "nordo", "unlawful", "downed", "reserved"} + processed_data["had_emergency"] = processed_data["had_emergency"].apply(lambda x: x in emergency_flags) # Remove rows with any NaN values processed_data = processed_data.dropna() # Save as CSV - output_file = os.path.join(prepared_directory, 'prepared_data.csv') + output_file = os.path.join(prepared_directory, "prepared_data.csv") processed_data.to_csv(output_file, index=False) print(processed_data) @@ -201,16 +208,16 @@ def list_aircraft(num_results: int = 100, page: int = 0) -> list[dict]: sorted_aircraft = pd.read_csv(prepared_directory) # Deduplicate values and sort by 'icao' - sorted_aircraft = sorted_aircraft[['icao', 'registration', 'type']].drop_duplicates().sort_values(by='icao') + sorted_aircraft = sorted_aircraft[["icao", "registration", "type"]].drop_duplicates().sort_values(by="icao") start = page * num_results end = start + num_results - result = sorted_aircraft.iloc[start:end].to_dict(orient='records') + result = sorted_aircraft.iloc[start:end].to_dict(orient="records") print(result) return result - return [{"icao": "0d8300", "registration": "YV3382", "type": "LJ31"}] # Done + return [{"icao": "0d8300", "registration": "YV3382", "type": "LJ31"}] # Done @s1.get("/aircraft/{icao}/positions") @@ -220,9 +227,10 @@ def get_aircraft_position(icao: str, num_results: int = 1000, page: int = 0) -> """ # TODO implement and return a list with dictionaries with those values. - # Calculate the start index: start_index = page * limit + # Calculate the start and end index for slicing the DataFrame start_index = page * num_results end_index = (page + 1) * num_results + prepared_directory = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") if not os.path.exists(prepared_directory): return [] @@ -231,9 +239,7 @@ def get_aircraft_position(icao: str, num_results: int = 1000, page: int = 0) -> # Dataframe with subset of rows for the requested 'icao' filtered_df = df[df["icao"] == icao].sort_values(by="timestamp") # Slice the DataFrame according to the page and number of results per page - return filtered_df.iloc[page * num_results:(page + 1) * num_results][["timestamp", "lat", "lon"]].to_dict(orient="records") - - return [{"timestamp": 1609275898.6, "lat": 30.404617, "lon": -86.476566}] + return filtered_df.iloc[start_index:end_index][["timestamp", "lat", "lon"]].to_dict(orient="records") @s1.get("/aircraft/{icao}/stats") @@ -246,7 +252,7 @@ def get_aircraft_statistics(icao: str) -> dict: """ # TODO Gather and return the correct statistics for the requested aircraft data_file = os.path.join(settings.prepared_dir, "day=20231101", "prepared_data.csv") - + # Check if the file exists if not os.path.exists(data_file): return {} @@ -254,38 +260,48 @@ def get_aircraft_statistics(icao: str) -> dict: try: # Read the CSV file into a DataFrame df = pd.read_csv(data_file) - + # Filter the DataFrame by 'icao' - df = df[df['icao'] == icao] + df = df[df["icao"] == icao] # Check if the filtered DataFrame is empty if df.empty: return {} + # Convert and clean altitude data + df["altitude_baro"] = pd.to_numeric(df["altitude_baro"], errors="coerce") + df["ground_speed"] = pd.to_numeric(df["ground_speed"], errors="coerce") # Remove rows with NaN values in relevant columns - df = df.dropna(subset=['altitude_baro', 'ground_speed', 'had_emergency']) + df = df.dropna(subset=["altitude_baro", "ground_speed", "had_emergency"]) - # Calculate statistics - max_altitude_baro = df['altitude_baro'].max() - max_ground_speed = df['ground_speed'].max() - had_emergency = df['had_emergency'].any() + # Calculate statistics while handling errors + max_altitude = df["altitude_baro"].max() + max_speed = df["ground_speed"].max() + emergency = df["had_emergency"].any() - # Convert numpy types to Python native types - max_altitude_baro = float(max_altitude_baro) if not pd.isna(max_altitude_baro) else None - max_ground_speed = float(max_ground_speed) if not pd.isna(max_ground_speed) else None - had_emergency = bool(had_emergency) # Convert numpy.bool_ to Python bool + # Ensure we have valid numeric values + if pd.isna(max_altitude) or pd.isna(max_speed): + return { + "max_altitude_baro": 0, + "max_ground_speed": 0, + "had_emergency": bool(emergency) + } return { - "max_altitude_baro": max_altitude_baro, - "max_ground_speed": max_ground_speed, - "had_emergency": had_emergency + "max_altitude_baro": float(max_altitude), + "max_ground_speed": float(max_speed), + "had_emergency": bool(emergency) } - except Exception as e: - return {"error": str(e)} -# Example usage -result = get_aircraft_statistics("some_icao_code") -print(result) + except Exception as e: + # Log the error for debugging + print(f"Error processing aircraft statistics: {str(e)}") + # Return default values instead of error message + return { + "max_altitude_baro": 0, + "max_ground_speed": 0, + "had_emergency": False + } # This line should be removed or commented out as it is outside of any function or class # return {"max_altitude_baro": 300000, "max_ground_speed": 493, "had_emergency": False} From 7dd105c0c1edde907c6173e5c85c2e8e9214f57e Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Wed, 19 Mar 2025 12:37:52 +0100 Subject: [PATCH 6/7] Resubmission of s4 exercise.py and test_s4.py --- bdi_api/s4/exercise.py | 116 ++++++++++++++++++++++++++++++++--------- tests/s4/test_s4.py | 97 ++++++++++++++++++++++++++++++++++ 2 files changed, 189 insertions(+), 24 deletions(-) create mode 100644 tests/s4/test_s4.py diff --git a/bdi_api/s4/exercise.py b/bdi_api/s4/exercise.py index 2e32469d..b763c18e 100644 --- a/bdi_api/s4/exercise.py +++ b/bdi_api/s4/exercise.py @@ -1,11 +1,19 @@ +import json +import os from typing import Annotated +from urllib.parse import urljoin -from fastapi import APIRouter, status +import boto3 +import requests +from bs4 import BeautifulSoup +from fastapi import APIRouter, status, HTTPException from fastapi.params import Query +from tqdm import tqdm from bdi_api.settings import Settings settings = Settings() +s3 = boto3.client("s3") s4 = APIRouter( responses={ @@ -19,36 +27,96 @@ @s4.post("/aircraft/download") def download_data( - file_limit: Annotated[ - int, - Query( - ..., - description=""" - Limits the number of files to download. - You must always start from the first the page returns and - go in ascending order in order to correctly obtain the results. - I'll test with increasing number of files starting from 100.""", - ), - ] = 100, + file_limit: Annotated[int, Query(..., description="Limits the number of files to download.")], ) -> str: - """Same as s1 but store to an aws s3 bucket taken from settings - and inside the path `raw/day=20231101/` - - NOTE: you can change that value via the environment variable `BDI_S3_BUCKET` - """ + """Download files from a source URL and store them in S3.""" base_url = settings.source_url + "/2023/11/01/" s3_bucket = settings.s3_bucket s3_prefix_path = "raw/day=20231101/" - return "OK" + try: + try: + response = requests.get(base_url) + response.raise_for_status() + except Exception as e: + return f"Error accessing URL: {str(e)}" + + soup = BeautifulSoup(response.text, "html.parser") + files = [a["href"] for a in soup.find_all("a") if a["href"].endswith(".json.gz")][:file_limit] + + downloaded_count = 0 + for file_name in tqdm(files, desc="Downloading files"): + file_url = urljoin(base_url, file_name) + try: + response = requests.get(file_url, stream=True) + response.raise_for_status() + except Exception as e: + return f"Error accessing URL: {str(e)}" + + s3_key = f"{s3_prefix_path}{file_name}" + s3.put_object(Bucket=s3_bucket, Key=s3_key, Body=response.content, ContentType="application/json") + downloaded_count += 1 + + return f"Downloaded {downloaded_count} files in S3." + + except Exception as e: + raise HTTPException(status_code=200, detail=f"Error accessing URL: {str(e)}") @s4.post("/aircraft/prepare") def prepare_data() -> str: - """Obtain the data from AWS s3 and store it in the local `prepared` directory - as done in s2. + """Download data from S3 and store it in the local `prepared` directory.""" + s3_bucket = settings.s3_bucket + s3_prefix_path = "raw/day=20231101/" + local_directory = settings.prepared_dir # Use the property + + try: + os.makedirs(local_directory, exist_ok=True) + + # Clear old data in prepared directory + for file in os.listdir(local_directory): + os.remove(os.path.join(local_directory, file)) + + response = s3.list_objects_v2(Bucket=s3_bucket, Prefix=s3_prefix_path) + if 'Contents' not in response: + return "No files found in S3." + + for obj in tqdm(response['Contents'], desc="Processing files"): + s3_key = obj['Key'] + file_name = os.path.basename(s3_key) + prepared_file_path = os.path.join(local_directory, file_name.replace(".gz", "")) + + try: + file_response = s3.get_object(Bucket=s3_bucket, Key=s3_key) + json_content = json.loads(file_response['Body'].read().decode('utf-8')) + + timestamp = json_content.get("now") + aircraft_data = json_content.get("aircraft", []) + + processed_aircraft_data = [ + { + "icao": record.get("hex"), + "registration": record.get("r"), + "type": record.get("t"), + "lat": record.get("lat"), + "lon": record.get("lon"), + "alt_baro": record.get("alt_baro"), + "timestamp": timestamp, + "max_altitude_baro": record.get("alt_baro"), + "max_ground_speed": record.get("gs"), + "had_emergency": record.get("alert", 0) == 1, + } + for record in aircraft_data + ] + + with open(prepared_file_path, "w", encoding="utf-8") as f: + json.dump(processed_aircraft_data, f) + + except Exception as e: + print(f"Error processing file {s3_key}: {str(e)}") + continue + + return f"Prepared data saved to {local_directory}." - All the `/api/s1/aircraft/` endpoints should work as usual - """ - # TODO - return "OK" + except Exception as e: + return f"Error during preparation: {str(e)}" \ No newline at end of file diff --git a/tests/s4/test_s4.py b/tests/s4/test_s4.py new file mode 100644 index 00000000..9b4f5e01 --- /dev/null +++ b/tests/s4/test_s4.py @@ -0,0 +1,97 @@ +# tests/s4/test_s4.py +import json +import os +from unittest import mock + +import boto3 +import pytest +from moto import mock_s3 +from fastapi.testclient import TestClient +from bdi_api import app +from bdi_api.s4.exercise import s4 +from bdi_api.settings import Settings + +client = TestClient(app) +settings = Settings() + +@pytest.fixture +def s3_bucket(): + """Create a mock S3 bucket for testing.""" + with mock_s3(): + s3 = boto3.client("s3", region_name="us-east-1") + bucket_name = settings.s3_bucket + s3.create_bucket(Bucket=bucket_name) + yield bucket_name + +def test_download_data_success(s3_bucket): + """Test successful file download and upload to S3.""" + with mock.patch("requests.get") as mock_get: # Mock requests.get directly + mock_list_response = mock.Mock() + mock_list_response.status_code = 200 + mock_list_response.text = """file1.json.gz""" + + mock_file_response = mock.Mock() + mock_file_response.status_code = 200 + mock_file_response.content = b"test content" + mock_file_response.raise_for_status = mock.Mock() + + mock_get.side_effect = [mock_list_response, mock_file_response] + + response = client.post("/api/s4/aircraft/download", params={"file_limit": 1}) + + assert response.status_code == 200 + assert "Downloaded 1 files in S3" in response.text + +def test_download_data_failure(s3_bucket): + """Test failed file download.""" + with mock.patch("requests.get", side_effect=Exception("Connection error")): # Mock requests.get directly + response = client.post("/api/s4/aircraft/download", params={"file_limit": 1}) + assert response.status_code == 200 + assert "Error accessing URL" in response.text + +def test_prepare_data_success(s3_bucket): + """Test successful data preparation from S3.""" + test_dir = settings.prepared_dir # Use the property + os.makedirs(test_dir, exist_ok=True) + + test_data = { + "now": 1635724800, + "aircraft": [{ + "hex": "abc123", + "r": "N123AB", + "t": "B738", + "lat": 40.7128, + "lon": -74.0060, + "alt_baro": 30000, + "gs": 450, + "alert": 0 + }] + } + + s3 = boto3.client("s3", region_name="us-east-1") + test_key = "raw/day=20231101/test.json.gz" + s3.put_object( + Bucket=s3_bucket, + Key=test_key, + Body=json.dumps(test_data).encode() + ) + + response = client.post("/api/s4/aircraft/prepare") + + assert response.status_code == 200 + assert "Prepared data saved" in response.text + + processed_file = os.path.join(test_dir, "test.json") + assert os.path.exists(processed_file) + + # Cleanup + os.remove(processed_file) + if not os.listdir(test_dir): # Only remove if directory is empty + os.rmdir(test_dir) + +def test_prepare_data_failure(s3_bucket): + """Test preparation when no files exist in S3.""" + response = client.post("/api/s4/aircraft/prepare") + + assert response.status_code == 200 + assert "No files found in S3" in response.text \ No newline at end of file From 301efca48edc3cfeff92fe1d026737261e18994c Mon Sep 17 00:00:00 2001 From: Andrea Barboza Date: Wed, 19 Mar 2025 13:25:58 +0100 Subject: [PATCH 7/7] Delete arkandrea.pem --- arkandrea.pem | 27 --------------------------- 1 file changed, 27 deletions(-) delete mode 100644 arkandrea.pem diff --git a/arkandrea.pem b/arkandrea.pem deleted file mode 100644 index 129ebb54..00000000 --- a/arkandrea.pem +++ /dev/null @@ -1,27 +0,0 @@ ------BEGIN RSA PRIVATE KEY----- -MIIEowIBAAKCAQEAq9XKY3QQKMuZEJSC6Bu79NY/Yk7R39fHND7Lk8D+LUEVWV+8 -cArWjNftXDyCs1r696Ge5wdNVAa+B1yT3638JeRrjRD5yb1y/0Qb6iBekFBHSZki -HYKnMNEN3ngJMS458j1Gbp3u8VIOYbNsmgW+7NUaIH06UCdikPtchZ8HfLDBJjy2 -K72nAd9PXXOnuyJd0wz+tlhswBIhbDA9KDuypVq/Xa6GJVc0OuXTeuTlJTLk2GOY -nVGBzIRIzOJyUq7W2chZbpCB1rNF2f3VqrrD69XCcK0voUojlYdbeez/dSWzcahr -kOOpqMrO02+7DaT2KacTaE+c9SYGL+phQmiZIQIDAQABAoIBAQClMOrW/y3FuizU -5qCOOJNRhWH7xSA4G70SecfFrEPuB2JZwBJsd87YKYCzKizP9YfM5Z/YI4nwXGb0 -tsglwaHkX5oRTB+GFM1nnvdi9WlTPQm7NC66xe6qnF7D3wufLvxf5w49qzCY57SR -siaWTy3Dif4K+7hCdApqrGq+vio5cDIzjt9EWETwTBD/xLjh1gStv8GN9r0jv2nL -WphJWwXNxyHCs8wsgoSqEEfK371Kz4Cg1zsDWrFm89cAXIPkBXtA2REQIfPQxAn7 -19WyItirBORtPSpNTJDz6I8QccOgBWQtlrJ4ICfL3mdI/yBvHRNUWUrCTGtUP1+L -F9txnw0dAoGBAOOUsCnl562655IIbBe6p6ilPlIrHZDubluKXmq/811OMAwKh3kr -bl5XZ5upOAc6Hz6mxo108LQe9+1rbR+5DG3lyuAgKHP7/IfH/BTcHQRJ1ef56Bqw -clam7WOQOnhzvS5409eoklCSyY5M0+ja2OIzUrzSI8BgVISj22igIq2jAoGBAMFL -BaSgmHZeHL0gJqHEtnG6p95GlVb7z3rMH8P7m759yN7Ngy+9lDNKETI+WqlelLbK -fdeUdHd7BSm/Jtv9gj9y/9nrI9f/GOJjegp1ZGAmYBc+AuP30O2vMhYTIaulJ7Ns -d+K0JYNxEhsiOzj4cCHBYdP0BlF6zm1KJ3qWokJrAoGAR7cXPFzCgTCgwJf+2Att -weswlFwZ2Q4JoLcdwa3zVrfI1EKNJlXVVc1dTOQqT7y1E90iPHlZUKlhn2N248RA -cnEzWSVJGiOSFIeknD4wtqU9zvgleCOaJEw+Cl3szwBJ4VcaCp+IW/OlqD31mS89 -oSpjLDVcJsc0Wwf3oCS2SNkCgYANRa15hF1zozqt8cs1SGCOppZoOMiAVIIGmIWF -23zyM4jbY5kiag4HB4ruvEFVZ90mP/ksGFF28seD+lAcwudym97dg7vOVQHMabAz -j6P4xinK7sMcDCQYbfMueNnTA2AafdQtiNkakWUA3/TZEJYCe1jQSO02IwyRjInx -bO5vSQKBgBBlzT4foWvOB//a5II4egPbNkiHtvZfABaor4qxkGg7tkGXjc1EDAB4 -aS1/+IjuLZ+kfnIDURMndWz38uSfQ5awKXUi5lFJku46EebIFLQ7C09KDyjnsRvs -HEzgUYpxPS4+ja9X2C7R8rX4+fV4e6XTXvaGudSAzlQ3Y0MpxYos ------END RSA PRIVATE KEY----- \ No newline at end of file