114 lines
3.9 KiB
Python
114 lines
3.9 KiB
Python
import base64
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import json
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import os
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import gspread
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import pandas as pd
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from dotenv import load_dotenv
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from oauth2client.service_account import ServiceAccountCredentials
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# Load environment variables from .env file
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load_dotenv()
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# Get the base64 string from the environment variable
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base64_creds = os.getenv("GDRIVE_BASE64")
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if base64_creds is None:
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raise ValueError("The GDRIVE_BASE64 environment variable is not set")
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# Decode the base64 string into bytes
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creds_bytes = base64.b64decode(base64_creds)
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# Convert the bytes into a string
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creds_string = creds_bytes.decode("utf-8")
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# Parse the string into a JSON object
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creds_info = json.loads(creds_string)
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# Define the base directory containing JSON files
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base_dir = "reports"
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# Create a list to store each row of data
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rows = []
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# Loop over each directory in the base directory
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for sub_dir in os.listdir(base_dir):
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# Define the subdirectory path
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sub_dir_path = os.path.join(base_dir, sub_dir)
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# Ensure the sub_dir_path is a directory
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if os.path.isdir(sub_dir_path):
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# Loop over each file in the subdirectory
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for filename in os.listdir(sub_dir_path):
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# Check if the file is a JSON file
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if filename.endswith(".json"):
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# Define the file path
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file_path = os.path.join(sub_dir_path, filename)
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# Load the JSON data from the file
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with open(file_path, "r") as f:
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data = json.load(f)
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# Loop through each test
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for test_name, test_info in data["tests"].items():
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# Create a dictionary to hold the information for this row
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row = {
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"Agent": sub_dir,
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"Command": data.get("command", ""),
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"Completion Time": data.get("completion_time", ""),
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"Total Run Time": data.get("metrics", {}).get("run_time", ""),
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"Highest Difficulty": data.get("metrics", {}).get(
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"highest_difficulty", ""
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),
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"Workspace": data.get("config", {}).get("workspace", ""),
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"Test Name": test_name,
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"Data Path": test_info.get("data_path", ""),
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"Is Regression": test_info.get("is_regression", ""),
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"Difficulty": test_info.get("metrics", {}).get(
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"difficulty", ""
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),
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"Success": test_info.get("metrics", {}).get("success", ""),
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"Success %": test_info.get("metrics", {}).get("success_%", ""),
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"Non mock success %": test_info.get("metrics", {}).get(
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"non_mock_success_%", ""
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),
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"Run Time": test_info.get("metrics", {}).get("run_time", ""),
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}
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# Add this row to the list
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rows.append(row)
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# Convert the list of rows into a DataFrame
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df = pd.DataFrame(rows)
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# Define the scope
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scope = [
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"https://spreadsheets.google.com/feeds",
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"https://www.googleapis.com/auth/drive",
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]
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# Add your service account credentials
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creds = ServiceAccountCredentials.from_json_keyfile_dict(creds_info, scope)
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# Authorize the clientsheet
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client = gspread.authorize(creds)
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# Get the instance of the Spreadsheet
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branch_name = os.getenv("GITHUB_REF_NAME")
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sheet = client.open(f"benchmark-{branch_name}")
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# Get the first sheet of the Spreadsheet
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sheet_instance = sheet.get_worksheet(0)
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# Convert dataframe to list of lists for uploading to Google Sheets
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values = df.values.tolist()
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# Prepend the header to the values list
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values.insert(0, df.columns.tolist())
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# Clear the existing values in the worksheet
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sheet_instance.clear()
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# Update the worksheet with the new values
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sheet_instance.append_rows(values)
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