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import marimo
import pandas as pd
import io
import matplotlib.pyplot as plt
from script import getSearchResult, getClustersWithGraph, compare_clusters
app = marimo.App()
@app.cell
def _(mo):
csv_upload = mo.ui.file(label="Upload Keyword CSV (1 column)")
import os
api_key = os.environ.get("GOOGLE_API_KEY", "")
cse_id = os.environ.get("GOOGLE_CSE_ID", "")
country = mo.ui.text(label="Country Code (e.g. UK)", value="UK")
language = mo.ui.text(label="Language Code (e.g. EN)", value="EN")
database = mo.ui.text(label="SQLite DB Name", value="data.db")
serp_table = mo.ui.text(label="SERP Table", value="keywords_serps")
cluster_table = mo.ui.text(label="Cluster Table", value="keyword_clusters")
run_button = mo.ui.button(label="Run Clustering Comparison")
return csv_upload, api_key, cse_id, country, language, database, serp_table, cluster_table, run_button
@app.cell
def _(mo):
timestamp_options = [
("Latest available (max)", "max"),
("March 2024 core update (2024-04-26 00:00:00.000000)", "2024-04-26 00:00:00.000000"),
("August 2024 core update (2024-09-10 00:00:00.000000)", "2024-09-10 00:00:00.000000"),
("November 2024 core update (2024-12-11 00:00:00.000000)", "2024-12-11 00:00:00.000000"),
("December 2024 core update (2024-12-25 00:00:00.000000)", "2024-12-25 00:00:00.000000"),
("March 2025 core update (2025-04-03 00:00:00.000000)", "2025-04-03 00:00:00.000000"),
("June 2025 core update (2025-07-24 00:00:00.000000)", "2025-07-24 00:00:00.000000"),
]
timestamp_1 = mo.ui.dropdown(timestamp_options, label="Choose Timestamp 1")
timestamp_2 = mo.ui.dropdown(timestamp_options, label="Choose Timestamp 2")
return timestamp_1, timestamp_2
@app.cell
def _(csv_upload):
if csv_upload.value:
df_keywords = pd.read_csv(io.BytesIO(csv_upload.value.read()))
keywords = df_keywords.iloc[:, 0].tolist()
else:
df_keywords, keywords = None, []
return df_keywords, keywords
@app.cell
def _(keywords, api_key, cse_id, country, language, database, serp_table, timestamp_1, timestamp_2, run_button):
if run_button.clicked and keywords:
# Run search and store results
getSearchResult(keywords, language, country, api_key, cse_id, database, serp_table)
fig1, clusters1 = getClustersWithGraph(database, serp_table, timestamp_1.value)
fig2, clusters2 = getClustersWithGraph(database, serp_table, timestamp_2.value)
movement = compare_clusters(clusters1, clusters2)
return fig1, fig2, movement
return None, None, None
@app.cell
def _(fig1, fig2):
if fig1 and fig2:
display(fig1)
display(fig2)
@app.cell
def _(movement):
if movement is not None:
movement.sort_values(by="searchTerms", inplace=True)
movement.reset_index(drop=True, inplace=True)
return movement is not None:
movement.sort_values(by="searchTerms", inplace=True)
movement.reset_index(drop=True, inplace=True)
return movement is not None:
movement.sort_values(by="searchTerms", inplace=True)
movement.reset_index(drop=True, inplace=True)
return movement is not None:
movement.sort_values(by="searchTerms", inplace=True)
movement.reset_index(drop=True, inplace=True)
movement
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