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LrJugUA?W`A8`#=m From 59c612706bb5a552a02ea87ea04963f9be47e721 Mon Sep 17 00:00:00 2001 From: Fawz Mehfil <70117285+fawzmehfil@users.noreply.github.com> Date: Sat, 17 Feb 2024 01:31:41 -0500 Subject: [PATCH 2/8] Create get_model.py --- machine-learning/get_model.py | 39 +++++++++++++++++++++++++++++++++++ 1 file changed, 39 insertions(+) create mode 100644 machine-learning/get_model.py diff --git a/machine-learning/get_model.py b/machine-learning/get_model.py new file mode 100644 index 0000000..72d8030 --- /dev/null +++ b/machine-learning/get_model.py @@ -0,0 +1,39 @@ +from pycaret.classification import setup as classification_setup, compare_models as classification_compare_models, finalize_model +from pycaret.regression import setup as regression_setup, compare_models as regression_compare_models, finalize_model +import pandas as pd +import joblib + +def perform_classification(data, target_column): + + classification_setup(data = data, target = target_column) + best_model = classification_compare_models() + final_model = finalize_model(best_model) + + model_file_path = 'classification_model.pkl' + joblib.dump(final_model, model_file_path) + + return final_model, model_file_path + +def perform_regression(data, target_column): + + regression_setup(data = data, target = target_column) + best_model = regression_compare_models() + final_model = finalize_model(best_model) + + model_file_path = 'regression_model.pkl' + joblib.dump(final_model, model_file_path) + + return final_model, model_file_path + +def get_model(data, target_column, task): + + data = data # Supplied dataset + target_column = target_column + task = task.upper() # Either R or C + + if task == 'C': + final_model, model_file_path = perform_classification(data, target_column) + elif task == 'R': + final_model, model_file_path = perform_regression(data, target_column) + + return final_model, model_file_path From 8614ac0c53aff9b8537c7a5f31e94119327eb981 Mon Sep 17 00:00:00 2001 From: Austin Bennett 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http://127.0.0.1:8000/api/automl #### Upload data set -PUT http://127.0.0.1:8000/api/upload?filename=test-data -Content-Type: multipart/form-data; boundary=MyBoundary +PUT http://127.0.0.1:8000/api/upload?filename=test +Content-Type: multipart/form-data; boundary=yourBoundary ---MyBoundary +--yourBoundary Content-Disposition: form-data; name="file"; filename="data.csv" Content-Type: text/csv -< @./data.csv ---MyBoundary-- +< ../data.csv +--yourBoundary-- #### Get eda GET http://127.0.0.1:8000/api/eda?filename=data \ No newline at end of file diff --git a/backend/main.py b/backend/main.py index 5975eae..13931c3 100644 --- a/backend/main.py +++ b/backend/main.py @@ -1,3 +1,4 @@ +from http.client import HTTPException from google.cloud import storage from google.cloud import bigquery from starlette.responses import FileResponse @@ -36,8 +37,7 @@ async def refreshDataSets(): global dataSetNames try: - storage_client = storage.Client.from_service_account_json( - "./credentials.json") + storage_client = storage.Client.from_service_account_json("./credentials.json") blobs = storage_client.list_blobs(DATA_BUCKET) dataSetNames = [blob.name for blob in blobs] @@ -65,25 +65,35 @@ async def root(): async def root_py(): return {"message": "Hello from fastAPI backend"} + # add a new dataset to the bucket @app.put("/api/upload") -async def upload(file: UploadFile = File(...), fileName: str = Form(...)): +async def upload(fileName: str, file: UploadFile = File(...)): try: - storage_client = storage.Client.from_service_account_json( - "./credentials.json") + # Validate file type + if not file.filename.endswith(".csv"): + raise HTTPException( + status_code=400, + detail="Invalid file type. Only CSV files are accepted.", + ) + + storage_client = storage.Client.from_service_account_json("./credentials.json") bucket = storage_client.get_bucket(DATA_BUCKET) - # Assuming fileName includes '.csv' extension blob = bucket.blob(f"{fileName}") - content = await file.read() - blob.upload_from_string(content, content_type=file.content_type) + blob.upload_from_file(file.file, content_type="text/csv") await refreshDataSets() # Make sure this function is defined if you want to use it - return JSONResponse(status_code=200, content={"message": "Data uploaded to GCloud successfully"}) + return JSONResponse( + status_code=200, content={"message": "Data uploaded to GCloud successfully"} + ) except Exception as e: - return JSONResponse(status_code=500, content={"error": f"An error occurred: {str(e)}"}) + return JSONResponse( + status_code=500, content={"error": f"An error occurred: {str(e)}"} + ) + # list all the datasets in the bucket @app.get("/api/datasets") @@ -92,6 +102,7 @@ async def getDataSets(): return {"error": f"No DataSets in Bucket"} return {"names": dataSetNames} + # get the data from the bucket and return it as a string @app.get("/api/data") async def getData(filename): @@ -104,9 +115,9 @@ async def getData(filename): with blob.open("r") as f: dataSetLines = f.read() - + # convert dataSetLines to be of type str | None (#TODO - check if this is necessary) - dataSetLines = str(dataSetLines) if dataSetLines else None + dataSetLines = str(dataSetLines) if dataSetLines else None # convert csv string -> json (for frontend) csv_reader = csv.DictReader(StringIO(dataSetLines)) @@ -115,10 +126,7 @@ async def getData(filename): except Exception as e: return {"error": f"An error occurred: {str(e)}"} - return { - "data": dataSetLines, - "json": json_data - } + return {"data": dataSetLines, "json": json_data} # Exploratory Data Analysis @@ -147,7 +155,7 @@ async def eda(filename): except Exception as e: return {"error": f"An error occurred: {str(e)}"} - + finally: # Delete the temporary file if os.path.exists(f"tempImages/{uniqueFilename}"): @@ -155,11 +163,12 @@ async def eda(filename): return {"data": corrMatrix, "graph_url": public_url} + # return the model as a file @app.get("/api/automl") async def getModel(): try: - #From #172 rawan/pandas-read-bucket + # From #172 rawan/pandas-read-bucket # storage_client = storage.Client.from_service_account_json( # "./credentials.json") @@ -171,7 +180,6 @@ async def getModel(): # df = pd.read_csv(byte_stream) # model_path = automl(df) - # Use a placeholder file for testing download placeholder_model_path = "./download_test_random_data.pickle" @@ -179,8 +187,11 @@ async def getModel(): return {"error": f"An error occurred: {str(e)}"} # Return the placeholder file - return FileResponse(path=placeholder_model_path, filename=placeholder_model_path.split("/")[-1], media_type='application/octet-stream') - + return FileResponse( + path=placeholder_model_path, + filename=placeholder_model_path.split("/")[-1], + media_type="application/octet-stream", + ) return {"data": corrMatrix} @@ -191,15 +202,15 @@ async def bq(filename): # construct client objects (authorized with the service account json file) bq_client = bigquery.Client.from_service_account_json("./credentials.json") storage_client = storage.Client.from_service_account_json("./credentials.json") - + uri = f"gs://{DATA_BUCKET}/{filename}.csv" table_id = f"{BQ_DATASET}.{filename}_table" - + # if file does not exist in the bucket, return an error blob = storage_client.get_bucket(DATA_BUCKET).blob(filename + ".csv") if not blob.exists(): return {"error": f"File {filename}.csv does not exist in the bucket."} - + # if table does not exist, load it try: bq_client.get_table(table_id) @@ -210,18 +221,18 @@ async def bq(filename): skip_leading_rows=1, # column headers write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE, # Overwrite the table ) - + load_job = bq_client.load_table_from_uri( uri, table_id, job_config=job_config - ) # Make an API request. - + ) # Make an API request. + load_job.result() # Waits for the job to complete. - + # Query all rows from the table query = f"SELECT * FROM `{table_id}`" query_job = bq_client.query(query) rows = query_job.result() - + # display the rows data = [] for row in rows: From 52f1b6886f5ca2948a7150a3f8fe4df12f627024 Mon Sep 17 00:00:00 2001 From: abedmohammed Date: Sat, 17 Feb 2024 10:25:11 -0500 Subject: [PATCH 5/8] Using formdata instead --- backend/api-tests/requests.http | 6 +++++- backend/main.py | 2 +- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/backend/api-tests/requests.http b/backend/api-tests/requests.http index 2fa42fe..5d6db8c 100644 --- a/backend/api-tests/requests.http +++ b/backend/api-tests/requests.http @@ -20,9 +20,13 @@ GET http://127.0.0.1:8000/api/data?filename=data GET http://127.0.0.1:8000/api/automl #### Upload data set -PUT http://127.0.0.1:8000/api/upload?filename=test +PUT http://127.0.0.1:8000/api/upload Content-Type: multipart/form-data; boundary=yourBoundary +--yourBoundary +Content-Disposition: form-data; name="fileName" + +mo11.csv --yourBoundary Content-Disposition: form-data; name="file"; filename="data.csv" Content-Type: text/csv diff --git a/backend/main.py b/backend/main.py index 13931c3..d0f4cf7 100644 --- a/backend/main.py +++ b/backend/main.py @@ -68,7 +68,7 @@ async def root_py(): # add a new dataset to the bucket @app.put("/api/upload") -async def upload(fileName: str, file: UploadFile = File(...)): +async def upload(fileName: str = Form(...), file: UploadFile = File(...)): try: # Validate file type if not file.filename.endswith(".csv"): From d5008bec764a40c78fe7fd42a3ea4226aeb1e5fc Mon Sep 17 00:00:00 2001 From: rawanmahdi Date: Sat, 17 Feb 2024 10:54:04 -0500 Subject: [PATCH 6/8] Model generation library using pycaret --- .gitignore | 7 +- backend/compute/autoML.py | 43 ++++ backend/main.py | 12 +- backend/poetry.lock | 469 +++++++++++++++++++------------------- backend/pyproject.toml | 4 +- 5 files changed, 295 insertions(+), 240 deletions(-) create mode 100644 backend/compute/autoML.py diff --git a/.gitignore b/.gitignore index 6ff4b95..d81977a 100644 --- a/.gitignore +++ b/.gitignore @@ -13,4 +13,9 @@ __pycache__/ # ignore in all directories **/credentials.json -backend/big_query.py \ No newline at end of file +backend/big_query.py + +*.pkl +backend/bash.exe.stackdump +*.log +fish_data.csv \ No newline at end of file diff --git a/backend/compute/autoML.py b/backend/compute/autoML.py new file mode 100644 index 0000000..71028a8 --- /dev/null +++ b/backend/compute/autoML.py @@ -0,0 +1,43 @@ +# from pycaret.classification import setup as classification_setup, compare_models as classification_compare_models, finalize_model +# from pycaret.regression import setup as regression_setup, compare_models as regression_compare_models, finalize_model + +import pycaret.classification as pycaret_cl +import pycaret.regression as pycaret_rg + +import pandas as pd +import joblib + +def perform_classification(data, target_column): + + pycaret_cl.setup(data = data, target = target_column) + best_model = pycaret_cl.compare_models() + + model_file_path = 'classification_model.pkl' + joblib.dump(best_model, model_file_path) + + return best_model, model_file_path + +def perform_regression(data, target_column): + + pycaret_rg.setup(data = data, target = target_column) + best_model = pycaret_rg.compare_models() + + model_file_path = 'regression_model.pkl' + joblib.dump(best_model, model_file_path) + + return best_model, model_file_path + +def generate_model(data, target_column, task): + + df = pd.read_csv(data) # Supplied dataset + task = task.upper() # Either R or C + + if task == 'C': + perform_classification(df, target_column) # Call classification_setup() before classification_compare_models() + final_model, model_file_path = perform_classification(df, target_column) + elif task == 'R': + perform_regression(df, target_column) # Call regression_setup() before regression_compare_models() + final_model, model_file_path = perform_regression(df, target_column) + + return final_model, model_file_path + diff --git a/backend/main.py b/backend/main.py index 5975eae..1f0ab72 100644 --- a/backend/main.py +++ b/backend/main.py @@ -8,6 +8,8 @@ from fastapi.responses import JSONResponse from fastapi.middleware.cors import CORSMiddleware from compute.autoEDA import generate_eda +from compute.autoML import generate_model + import csv app = FastAPI() @@ -169,20 +171,18 @@ async def getModel(): # blob.download_to_file(byte_stream) # byte_stream.seek(0) # df = pd.read_csv(byte_stream) - # model_path = automl(df) - + model, model_path = generate_model("fish_data.csv","Species", "C") # Use a placeholder file for testing download - placeholder_model_path = "./download_test_random_data.pickle" + # placeholder_model_path = "./download_test_random_data.pickle" except Exception as e: return {"error": f"An error occurred: {str(e)}"} # 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"^3.11" -content-hash = "ccf3872f7fbad44539527e844eaf2bdc37b8d5257e4fdd7f2bf027fb5b0d6a6f" +python-versions = ">=3.11,<3.12" +content-hash = "9f17cb7380b84e45000922ff10a910145fbb57cb51033774790aa769a1966e1a" diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 6102862..9f065ea 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -6,14 +6,14 @@ authors = ["Andrew Bovbel "] readme = "README.md" [tool.poetry.dependencies] -python = "^3.11" +python = ">=3.11,<3.12" fastapi = "^0.104.0" uvicorn = {extras = ["standard"], version = "^0.23.2"} google-cloud-storage = "*" google-cloud-bigquery = "*" python-multipart = "*" -pandas = "^2.2.0" seaborn = "^0.13.2" +joblib = "^1.3.2" [build-system] requires = ["poetry-core"] From 1ed022b5d4189bedca82657e47decbd82d2fc490 Mon Sep 17 00:00:00 2001 From: LaeekAhmed Date: Mon, 19 Feb 2024 16:41:29 -0500 Subject: [PATCH 7/8] Implement bigQuery frontend + add redux + misc. fixes --- .gitignore | 1 + backend/Dockerfile | 2 +- backend/api-tests/requests.http | 6 +- backend/main.py | 87 +- backend/poetry.lock | 2244 +++++++- backend/pyproject.toml | 2 + cloud-infra/k8s/backend-deployment.yaml | 1 + frontend/.eslintrc.json | 4 +- frontend/package-lock.json | 4628 ++++++++++++----- frontend/package.json | 11 +- frontend/src/components/NavigationBar.js | 4 +- frontend/src/pages/automl.js | 16 + frontend/src/pages/profiling.js | 8 +- frontend/src/pages/query.js | 282 + frontend/src/pages/upload.js | 61 +- frontend/src/store/datasetSlice.js | 22 + frontend/src/store/fileSlice.js | 20 - frontend/src/store/store.js | 4 +- machine-learning/Auto_ML_CNN_Modelipynb.ipynb | 6 +- 19 files changed, 5892 insertions(+), 1517 deletions(-) create mode 100644 frontend/src/pages/query.js create mode 100644 frontend/src/store/datasetSlice.js delete mode 100644 frontend/src/store/fileSlice.js diff --git a/.gitignore b/.gitignore index d81977a..1b06b6c 100644 --- a/.gitignore +++ b/.gitignore @@ -17,5 +17,6 @@ backend/big_query.py *.pkl backend/bash.exe.stackdump +backend/.python-version *.log fish_data.csv \ No newline at end of file diff --git a/backend/Dockerfile b/backend/Dockerfile index 6e2e770..d71ccdb 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -18,7 +18,7 @@ COPY pyproject.toml poetry.lock ./ # Install the dependencies RUN poetry config virtualenvs.create false && poetry install --no-dev -# Copy the credentials.json file and compute dir into the container +# Copy the creds file and compute dir into the container COPY credentials.json ./ COPY compute ./compute diff --git a/backend/api-tests/requests.http b/backend/api-tests/requests.http index 5d6db8c..1a2d697 100644 --- a/backend/api-tests/requests.http +++ b/backend/api-tests/requests.http @@ -11,10 +11,10 @@ GET http://127.0.0.1:8000/api/python GET http://127.0.0.1:8000/api/datasets #### BigQuery test -GET http://127.0.0.1:8000/api/bq?filename=sample_contacts +GET http://127.0.0.1:8000/api/bq?fileName=sample_contacts #### Get Data -GET http://127.0.0.1:8000/api/data?filename=data +GET http://127.0.0.1:8000/api/data?fileName=data.csv #### Get AutoML GET http://127.0.0.1:8000/api/automl @@ -35,4 +35,4 @@ Content-Type: text/csv --yourBoundary-- #### Get eda -GET http://127.0.0.1:8000/api/eda?filename=data \ No newline at end of file +GET http://127.0.0.1:8000/api/eda?fileName=data \ No newline at end of file diff --git a/backend/main.py b/backend/main.py index 219da94..de861cc 100644 --- a/backend/main.py +++ b/backend/main.py @@ -100,6 +100,8 @@ async def upload(fileName: str = Form(...), file: UploadFile = File(...)): # list all the datasets in the bucket @app.get("/api/datasets") async def getDataSets(): + # have to refresh the state of the bucket since it may have changed + await refreshDataSets() if not dataSetNames: return {"error": f"No DataSets in Bucket"} return {"names": dataSetNames} @@ -107,13 +109,13 @@ async def getDataSets(): # get the data from the bucket and return it as a string @app.get("/api/data") -async def getData(filename): +async def getData(fileName): dataSetLines = "" try: storage_client = storage.Client.from_service_account_json("./credentials.json") bucket = storage_client.get_bucket(DATA_BUCKET) - blob = bucket.blob(f"{filename}.csv") + blob = bucket.blob(fileName) with blob.open("r") as f: dataSetLines = f.read() @@ -133,13 +135,13 @@ async def getData(filename): # Exploratory Data Analysis @app.get("/api/eda") -async def eda(filename): +async def eda(fileName): corrMatrix = "" try: storage_client = storage.Client.from_service_account_json("./credentials.json") bucket = storage_client.get_bucket(DATA_BUCKET) - blob = bucket.blob(f"{filename}.csv") + blob = bucket.blob(f"{fileName}.csv") byte_stream = BytesIO() blob.download_to_file(byte_stream) @@ -197,39 +199,62 @@ async def getModel(): # get file from bucket, load it to big query as a table & display the rows @app.get("/api/bq") -async def bq(filename): +async def bq(fileName, query=None): + # construct client objects (authorized with the service account json file) bq_client = bigquery.Client.from_service_account_json("./credentials.json") storage_client = storage.Client.from_service_account_json("./credentials.json") - - uri = f"gs://{DATA_BUCKET}/{filename}.csv" - table_id = f"{BQ_DATASET}.{filename}_table" - + + # check if the file name has .csv extension, if not, add it + # if not fileName.endswith('.csv'): + # fileName += '.csv' + + uri = f"gs://{DATA_BUCKET}/{fileName}" + # if file does not exist in the bucket, return an error - blob = storage_client.get_bucket(DATA_BUCKET).blob(filename + ".csv") + blob = storage_client.get_bucket(DATA_BUCKET).blob(fileName) if not blob.exists(): - return {"error": f"File {filename}.csv does not exist in the bucket."} - + return {"error": f"File {fileName} does not exist in the bucket."} + + fileName = fileName.replace('.csv', '') + table_id = f"{BQ_DATASET}.{fileName}_table" + # if table does not exist, load it - try: - bq_client.get_table(table_id) - except: - job_config = bigquery.LoadJobConfig( - autodetect=True, # Automatically infer the schema. - source_format=bigquery.SourceFormat.CSV, - skip_leading_rows=1, # column headers - write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE, # Overwrite the table - ) - - load_job = bq_client.load_table_from_uri( - uri, table_id, job_config=job_config - ) # Make an API request. - - load_job.result() # Waits for the job to complete. - - # Query all rows from the table - query = f"SELECT * FROM `{table_id}`" - query_job = bq_client.query(query) + # try: + # bq_client.get_table(table_id) + # except: + job_config = bigquery.LoadJobConfig( + autodetect=True, # Automatically infer the schema. + source_format=bigquery.SourceFormat.CSV, + skip_leading_rows=1, # column headers + write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE, # Overwrite the table + ) + # Make an API request + load_job = bq_client.load_table_from_uri( + uri, table_id, job_config=job_config + ) + # Waits for the job to complete. + load_job.result() + + #------------------------------------------ Query ops ----------------------------------------# + + query = query.upper() if query else None + + # List of potentially harmful operations + harmful_ops = ['DROP', 'DELETE', 'INSERT', 'UPDATE'] + + # Check if the query contains any harmful operations + if query and any(op in query.upper() for op in harmful_ops): + print("\nQuery contains harmful operations!\nusing default query.\n") + final_query = f"SELECT * FROM `{table_id}`" + else: + print("\nQuery is safe to be passed.\n") + # remove everything before the `SELECT` keyword from the received query + query = query[query.find("SELECT"):] if query else None + final_query = query.replace("FROM TABLE", f"FROM `{table_id}`") if query else f"SELECT * FROM `{table_id}`" + print("Final Query:\n", final_query, "\n") + + query_job = bq_client.query(final_query) rows = query_job.result() # display the rows diff --git a/backend/poetry.lock 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"is-fullwidth-code-point": "^3.0.0", + "strip-ansi": "^6.0.1" + } + } } }, "wrappy": { diff --git a/frontend/package.json b/frontend/package.json index 5926896..f3e9018 100644 --- a/frontend/package.json +++ b/frontend/package.json @@ -12,21 +12,26 @@ "@emotion/react": "^11.11.1", "@emotion/styled": "^11.11.0", "@fontsource/public-sans": "^5.0.15", + "@monaco-editor/react": "^4.6.0", "@mui/icons-material": "^5.14.14", "@mui/material": "^5.14.19", "@mui/x-data-grid": "^6.18.1", "@reduxjs/toolkit": "^2.1.0", + "monaco-editor-webpack-plugin": "^7.1.0", "mui-image": "^1.0.7", - "next": "13.5.6", + "next": "^14.1.0", + "next-transpile-modules": "^10.0.1", "react": "^18.2.0", "react-dom": "^18", + "react-monaco-editor": "^0.55.0", "react-redux": "^9.1.0", "recharts": "^2.10.1", "sass": "^1.69.4" }, "devDependencies": { - "eslint": "^8", - "eslint-config-next": "13.5.6", + "eslint": "^8.56.0", + "eslint-config-next": "^14.1.0", + "eslint-plugin-react": "^7.33.2", "prettier": "3.1.0" } } diff --git a/frontend/src/components/NavigationBar.js b/frontend/src/components/NavigationBar.js index 73a9c6a..35449be 100644 --- a/frontend/src/components/NavigationBar.js +++ b/frontend/src/components/NavigationBar.js @@ -13,9 +13,9 @@ import Image from "next/image"; import Link from "next/link"; import "@fontsource/public-sans"; -const pages = ["upload", "profiling", "automl"]; +const pages = ["upload", "profiling", "automl", "query"]; -function NavigationBar() { +const NavigationBar = () => { const [anchorElNav, setAnchorElNav] = React.useState(null); const handleOpenNavMenu = (event) => { diff --git a/frontend/src/pages/automl.js b/frontend/src/pages/automl.js index 89435e6..ab4c70c 100644 --- a/frontend/src/pages/automl.js +++ b/frontend/src/pages/automl.js @@ -1,5 +1,6 @@ // Automl.js import React, { useState, useEffect } from 'react'; +import { useSelector } from 'react-redux'; import { Checkbox, Radio, @@ -19,6 +20,7 @@ const Automl = () => { const [checkbox2, setCheckbox2] = useState(false); const [checkbox3, setCheckbox3] = useState(false); const [radioValue, setRadioValue] = useState('option1'); + const redux_dataset = useSelector((state) => state.dataset.value); const toggleChartLoading = () => { setChartLoading(!chartLoading); @@ -50,6 +52,20 @@ const Automl = () => { > {/* Left Column */}
+ + EDA and AutoML + + +

+ Current dataset: {redux_dataset} +

{ // Define your data and fetch or process it as needed const [data, setData] = useState([]); - + const redux_dataset = useSelector((state) => state.dataset.value); + useEffect(() => { // Fetch or process your data here and set it in the state // Example: const fetchData = async () => { ... } @@ -39,6 +41,10 @@ const Profiling = () => { > Data Profiling + +

+ Current dataset: {redux_dataset} +

{ + // hooks to store the datasets and the selected dataset + const [dataSets, setDataSets] = useState([]); + const [selectedDataSet, setSelectedDataSet] = useState(null); + + useEffect(() => { + // Fetch datasets from /api/datasets and update state + const fetchData = async () => { + try { + const res = await fetch("/api/datasets"); + const data = await res.json(); + setDataSets(data.names); + } catch { + console.error("API Endpoint Not Working"); + } + }; + fetchData(); + }, [uploadTrigger]); + + const handleSelectDataSet = (dataSet) => { + setSelectedDataSet(dataSet); + onSelectDataSet(dataSet); // This will pass the selected dataset to the parent component + }; + + return ( + //render the list of selectable datasets + + + {dataSets.map((dataSet, idx) => ( + handleSelectDataSet(dataSet)} + > + + + ))} + + + ); +}; + +// Component to display the selected dataset +const DataSetDisplayComponent = ({ selectedDataSet }) => { + const [data, setData] = useState([{}]); + const [csvString, setCsvString] = useState(""); + + useEffect(() => { + // Simulate fetching data + console.log("FETCHING DATA FOR", selectedDataSet) + const fetchData = async () => { + try { + const res = await fetch(`/api/data?fileName=${encodeURIComponent(selectedDataSet)}`) + if (!res.ok) { + throw new Error(`Error: ${res.status}`); + } + + const data = await res.json(); + const jsonObject = data.json; + + setCsvString(data.data) + setData(jsonObject); + + } catch (error) { + console.error('Failed to fetch data:', error); + return null; + } + }; + fetchData(); +}, [selectedDataSet]); + + const handleDownload = () => { + const blob = new Blob([csvString], { type: 'text/csv' }); + const url = URL.createObjectURL(blob); + const link = document.createElement('a'); + link.href = url; + link.download = `${selectedDataSet}`; + link.style.display = 'none'; // Hide the link + document.body.appendChild(link); // Append to the document + link.click(); // Programmatically click the link to trigger the download + URL.revokeObjectURL(url); // Free up memory by releasing the object URL + link.remove(); // Remove the link from the document + } + + const [query, setQuery] = useState("-- use `table` for table name, eg:\nSELECT * FROM table LIMIT 2"); + const [loading, setLoading] = useState(false); + const [error, setError] = useState(null); + + // calls the `/api/bq` endpoint with the `fileName` and `query` parameters + const runQuery = async (query) => { + setLoading(true); // for the loading spinner + setError(null); // clear any previous errors + + // List of potentially harmful operations + const harmfulOps = ['DROP', 'DELETE', 'INSERT', 'UPDATE']; + + // Check if the query contains any harmful operations + if (harmfulOps.some(op => query.toUpperCase().includes(op))) { + setError('Harmful operations detected'); + setLoading(false); + return; + } + + try { + const res = await fetch(`/api/bq?fileName=${encodeURIComponent(selectedDataSet)}&query=${query}`); + if (!res.ok) { + throw new Error(`Error: ${res.status}`); + } + + const response = await res.json(); + const data = response.data; + setData(data); + + } catch (error) { + console.error('Failed to fetch data:', error); + setError("something went wrong, make sure your query is valid"); // inform the user of the error + + } finally { + setLoading(false); // remove the loading spinner + } + }; + + const headers = data[0] ? Object.keys(data[0]) : []; + return ( +
+ + + + + + {headers.map((header, index) => ( + {header} + ))} + + + + {data.slice(0, 10).map((item, rowIndex) => ( + + {Object.values(item).map((value, colIndex) => ( + {value} + ))} + + ))} + +
+ + + Run Queries on the Dataset: + +
+ setQuery(value)} + /> +
+ {error &&
{error}
} + +
+ ); +}; + +// Main component to display previous components +const MainComponent = () => { + const [selectedDataSet, setSelectedDataSet] = useState(null); + const [uploadTrigger, setUploadTrigger] = useState(0); + + + const handleUpload = async (event) => { + const file = event.target.files[0]; + if (!file) { + console.error("No file selected."); + return; + } + + // Prepare FormData + const formData = new FormData(); + formData.append("file", file); + formData.append("fileName", file.name); // Adjust according to how you want to name files on the backend + + // Log FormData contents for debugging + for (let [key, value] of formData.entries()) { + console.log(`${key}:`, value); + } + + try { + // Make an asynchronous PUT request to your backend + const response = await fetch("/api/upload", { + method: "PUT", + body: formData, // FormData will be correctly interpreted by your backend + }); + + // Assuming your backend responds with JSON + const data = await response.json(); + + // Handle response + if (response.ok) { + console.log("Upload successful:", data.message); + setUploadTrigger(trigger => trigger + 1); + + } else { + console.error("Upload failed:", data.error); + } + } catch (error) { + console.error("Error during upload:", error); + } +}; + + + const handleSelectDataSet = (dataSet) => { + setSelectedDataSet(dataSet); + }; + + const triggerFileInput = () => { + // Trigger the hidden file input click event + document.getElementById('file-upload-input').click(); + }; + + return ( + + + Query Datasets + +
+
+ +
+ + +
+ +
+ + {selectedDataSet && ( +
+ +
+ )} +
+ + ); +}; + +export default MainComponent; \ No newline at end of file diff --git a/frontend/src/pages/upload.js b/frontend/src/pages/upload.js index 3896396..844b3d2 100644 --- a/frontend/src/pages/upload.js +++ b/frontend/src/pages/upload.js @@ -1,5 +1,6 @@ import React, { useState, useEffect } from 'react'; - +import { useSelector, useDispatch } from 'react-redux'; +import { setDataset } from '../store/datasetSlice'; import { Table, TableBody, TableCell, TableContainer, TableHead, TableRow, Paper, Button, ListItemText, ListItemButton, Box, Container, Typography } from "@mui/material" @@ -7,10 +8,13 @@ import { Table, TableBody, TableCell, TableContainer, TableHead, TableRow, import CloudUploadIcon from '@mui/icons-material/CloudUpload'; import CloudDownloadIcon from '@mui/icons-material/CloudDownload'; -const DataSetListComponent = ({ onSelectDataSet, uploadTrigger }) => { +const DataSetListComponent = ({ uploadTrigger }) => +{ const [dataSets, setDataSets] = useState([]); - const [selectedDataSet, setSelectedDataSet] = useState(null); - + + const redux_dataset = useSelector(state => state.dataset.value); + const dispatch = useDispatch(); + useEffect(() => { // Fetch datasets from /api/datasets and update state const fetchData = async () => { @@ -25,9 +29,9 @@ const DataSetListComponent = ({ onSelectDataSet, uploadTrigger }) => { fetchData(); }, [uploadTrigger]); - const handleSelectDataSet = (dataSet) => { - setSelectedDataSet(dataSet); - onSelectDataSet(dataSet); // This will pass the selected dataset to the parent component + const handleSelectDataSet = (dataSet) => + { + dispatch(setDataset(dataSet)); }; return ( //render the list of selectable datasets @@ -36,7 +40,7 @@ const DataSetListComponent = ({ onSelectDataSet, uploadTrigger }) => { {dataSets.map((dataSet, idx) => ( handleSelectDataSet(dataSet)} > @@ -47,16 +51,19 @@ const DataSetListComponent = ({ onSelectDataSet, uploadTrigger }) => { ); }; -const DataSetDisplayComponent = ({ selectedDataSet }) => { +const DataSetDisplayComponent = () => +{ const [data, setData] = useState([{}]); const [csvString, setCsvString] = useState(""); + + const redux_dataset = useSelector(state => state.dataset.value); useEffect(() => { // Simulate fetching data - console.log("FETCHING DATA FOR", selectedDataSet) + console.log("Fetching data for", redux_dataset) const fetchData = async () => { try { - const res = await fetch(`/api/data?fileName=${encodeURIComponent(selectedDataSet)}`) + const res = await fetch(`/api/data?fileName=${encodeURIComponent(redux_dataset)}`) if (!res.ok) { throw new Error(`Error: ${res.status}`); } @@ -73,14 +80,14 @@ const DataSetDisplayComponent = ({ selectedDataSet }) => { } }; fetchData(); -}, [selectedDataSet]); +}, [redux_dataset]); const handleDownload = () => { const blob = new Blob([csvString], { type: 'text/csv' }); const url = URL.createObjectURL(blob); const link = document.createElement('a'); link.href = url; - link.download = `${selectedDataSet}`; + link.download = `${redux_dataset}`; link.style.display = 'none'; // Hide the link document.body.appendChild(link); // Append to the document link.click(); // Programmatically click the link to trigger the download @@ -88,7 +95,7 @@ const DataSetDisplayComponent = ({ selectedDataSet }) => { link.remove(); // Remove the link from the document } - const headers = data[0] ? Object.keys(data[0]) : []; + const headers = (data && data.length > 0) ? Object.keys(data[0]) : []; return (
@@ -119,11 +126,10 @@ const DataSetDisplayComponent = ({ selectedDataSet }) => { ); }; -const MainComponent = () => { - const [selectedDataSet, setSelectedDataSet] = useState(null); +const MainComponent = () => +{ const [uploadTrigger, setUploadTrigger] = useState(0); - - + const handleUpload = async (event) => { const file = event.target.files[0]; if (!file) { @@ -164,15 +170,12 @@ const MainComponent = () => { } }; - - const handleSelectDataSet = (dataSet) => { - setSelectedDataSet(dataSet); - }; - const triggerFileInput = () => { // Trigger the hidden file input click event document.getElementById('file-upload-input').click(); }; + + const redux_dataset = useSelector(state => state.dataset.value); return ( @@ -186,9 +189,15 @@ const MainComponent = () => { > Upload Your Datasets Here! + + { redux_dataset && +

+ Current dataset: {redux_dataset} +

} +
- +
{
- {selectedDataSet && ( + {redux_dataset && (
- +
)}
diff --git a/frontend/src/store/datasetSlice.js b/frontend/src/store/datasetSlice.js new file mode 100644 index 0000000..b842a41 --- /dev/null +++ b/frontend/src/store/datasetSlice.js @@ -0,0 +1,22 @@ +import { createSlice } from '@reduxjs/toolkit'; + +export const datasetSlice = createSlice({ + name: 'dataset', + initialState: { + value: '', + }, + reducers: { + setDataset: (state, action) => { + console.log('action', action); + state.value = action.payload; + }, + clearDataset: (state) => { + state.value = ''; + }, + }, +}); + +export const { setDataset, clearDataset } = datasetSlice.actions; + +// imported as datasetReducer in store.js +export default datasetSlice.reducer; diff --git a/frontend/src/store/fileSlice.js b/frontend/src/store/fileSlice.js deleted file mode 100644 index 29c97e7..0000000 --- a/frontend/src/store/fileSlice.js +++ /dev/null @@ -1,20 +0,0 @@ -import { createSlice } from '@reduxjs/toolkit'; - -export const fileSlice = createSlice({ - name: 'file', - initialState: { - value: '', - }, - reducers: { - setFile: (state, action) => { - state.value = action.payload; - }, - clearFile: (state) => { - state.value = ''; - }, - }, -}); - -export const { setFile, clearFile } = fileSlice.actions; - -export default fileSlice.reducer; diff --git a/frontend/src/store/store.js b/frontend/src/store/store.js index eb656de..d1347f3 100644 --- a/frontend/src/store/store.js +++ b/frontend/src/store/store.js @@ -1,8 +1,8 @@ import { configureStore } from '@reduxjs/toolkit'; -import fileReducer from './fileSlice'; +import datasetReducer from './datasetSlice'; export default configureStore({ reducer: { - file: fileReducer, + dataset: datasetReducer, }, }); diff --git a/machine-learning/Auto_ML_CNN_Modelipynb.ipynb b/machine-learning/Auto_ML_CNN_Modelipynb.ipynb index 9588099..3ece621 100644 --- a/machine-learning/Auto_ML_CNN_Modelipynb.ipynb +++ b/machine-learning/Auto_ML_CNN_Modelipynb.ipynb @@ -548,13 +548,13 @@ ], "application/javascript": [ "\n", - " async function download(id, filename, size) {\n", + " async function download(id, fileName, size) {\n", " if (!google.colab.kernel.accessAllowed) {\n", " return;\n", " }\n", " const div = document.createElement('div');\n", " const label = document.createElement('label');\n", - " label.textContent = `Downloading \"${filename}\": `;\n", + " label.textContent = `Downloading \"${fileName}\": `;\n", " div.appendChild(label);\n", " const progress = document.createElement('progress');\n", " progress.max = size;\n", @@ -582,7 +582,7 @@ " const blob = new Blob(buffers, {type: 'application/binary'});\n", " const a = document.createElement('a');\n", " a.href = window.URL.createObjectURL(blob);\n", - " a.download = filename;\n", + " a.download = fileName;\n", " div.appendChild(a);\n", " a.click();\n", " div.remove();\n", From 44fcb798dc9bc178e57a409b6028f2229b4e69c8 Mon Sep 17 00:00:00 2001 From: LaeekAhmed Date: Mon, 19 Feb 2024 17:13:11 -0500 Subject: [PATCH 8/8] Update .gitignore and Dockerfiles --- .gitignore | 5 +++-- backend/.dockerignore | 1 + backend/Dockerfile | 3 +++ backend/backend/.dockerignore | 1 - frontend/Dockerfile | 4 ++-- 5 files changed, 9 insertions(+), 5 deletions(-) create mode 100644 backend/.dockerignore delete mode 100644 backend/backend/.dockerignore diff --git a/.gitignore b/.gitignore index 1b06b6c..7d7ff11 100644 --- a/.gitignore +++ b/.gitignore @@ -4,6 +4,8 @@ app/src/logs.log app/src/best_model.pkl app/src/dataset.csv +frontend/.eslintrc.json + .DS_Store __pycache__/ @@ -13,10 +15,9 @@ __pycache__/ # ignore in all directories **/credentials.json -backend/big_query.py - *.pkl backend/bash.exe.stackdump backend/.python-version +backend/big_query.py *.log fish_data.csv \ No newline at end of file diff --git a/backend/.dockerignore b/backend/.dockerignore new file mode 100644 index 0000000..917b41f --- /dev/null +++ b/backend/.dockerignore @@ -0,0 +1 @@ +# credentials.json \ No newline at end of file diff --git a/backend/Dockerfile b/backend/Dockerfile index d71ccdb..0507747 100644 --- a/backend/Dockerfile +++ b/backend/Dockerfile @@ -4,6 +4,9 @@ FROM python:3.11.6-slim # Set the working directory in the container WORKDIR /app +# Install build dependencies +RUN apt-get update && apt-get install -y gcc musl-dev python3-dev + # Install and cleanup RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential \ diff --git a/backend/backend/.dockerignore b/backend/backend/.dockerignore deleted file mode 100644 index c7c52a9..0000000 --- a/backend/backend/.dockerignore +++ /dev/null @@ -1 +0,0 @@ -credentials.json \ No newline at end of file diff --git a/frontend/Dockerfile b/frontend/Dockerfile index 213992f..11d9459 100644 --- a/frontend/Dockerfile +++ b/frontend/Dockerfile @@ -1,5 +1,5 @@ # Stage 1: Building the code -FROM node:16-alpine AS builder +FROM node:18-alpine AS builder WORKDIR /app @@ -16,7 +16,7 @@ COPY . . RUN npm run build # Stage 2: Run the app -FROM node:16-alpine AS runner +FROM node:18-alpine AS runner WORKDIR /app # Copy built assets from the builder stage