From 228a6daa59fc4660f039f734866afc78f3af04b1 Mon Sep 17 00:00:00 2001 From: Luigi Maiorano Date: Tue, 16 Dec 2025 16:28:07 -0800 Subject: [PATCH] progress apply --- 02-B_Thematic-Processing.py | 40 ++++---- pyproject.toml | 8 +- utils/__init__.py | 2 +- utils/keyword_analysis.py | 13 +++ uv.lock | 194 +++++++++++++++++++++++++++++++----- 5 files changed, 212 insertions(+), 45 deletions(-) diff --git a/02-B_Thematic-Processing.py b/02-B_Thematic-Processing.py index ac687b0..f0dee91 100644 --- a/02-B_Thematic-Processing.py +++ b/02-B_Thematic-Processing.py @@ -7,8 +7,8 @@ app = marimo.App(width="medium") @app.cell def _(): import marimo as mo - # import pandas as pd - import modin.pandas as pd + import pandas as pd + import modin.pandas as mpd from tqdm import tqdm from pathlib import Path from datetime import datetime @@ -20,8 +20,7 @@ def _(): # initialize tqdm for pandas tqdm.pandas() - from modin.config import ProgressBar - ProgressBar.enable() + client, _models = connect_qumo_ollama(OLLAMA_LOCATION, print_models=False) @@ -134,6 +133,9 @@ def _(mo): @app.cell def _(mo, tag_select): mo.stop(not tag_select.value, mo.md("Select tag to continue")) + + # mdf = mpd.from_pandas(df) + start_processing_btn = mo.ui.button( label="Start Keyword Extraction", kind="warn", @@ -144,13 +146,23 @@ def _(mo, tag_select): @app.cell -def _(client, df, mo, model_select, pd, start_processing_btn): - from utils import ollama_keyword_extraction +def _( + WORKING_DIR, + client, + df, + mo, + model_select, + pd, + start_processing_btn, + tag_select, +): + from utils import ollama_keyword_extraction, worker_extraction # Wait for start processing button mo.stop(not start_processing_btn.value, "Click button above to start processing") + # Run keyword extraction - df['keywords'] = df.apply( + df['keywords'] = df.progress_apply( lambda row: pd.Series(ollama_keyword_extraction( content=row['content'], tag=row['tag'], @@ -159,17 +171,9 @@ def _(client, df, mo, model_select, pd, start_processing_btn): )), axis=1 ) - return - -@app.cell -def _(df): df['keywords_txt'] = df['keywords'].progress_apply(lambda kws: ', '.join(kws)) - return - -@app.cell -def _(WORKING_DIR, df, tag_select): df[['id', 'tag', 'content', 'keywords_txt']].to_csv( WORKING_DIR / f'keywords_{tag_select.value.replace(" ", "-")}.csv', index=False @@ -214,7 +218,7 @@ def _(df): else: keyword_freq[kw] = 1 - keyword_freq_filtered = {kw: freq for kw, freq in keyword_freq.items() if freq > MIN_FREQ} + keyword_freq_filtered = {kw: freq for kw, freq in keyword_freq.items() if freq >= MIN_FREQ} # create list of keywords sorted by their frequencies. only store the keyword sorted_keywords = sorted(keyword_freq_filtered.items(), key=lambda x: x[1], reverse=True) @@ -231,12 +235,12 @@ def _(plt): def blue_color_func(word, font_size, position, orientation, random_state=None, **kwargs): # Use the provided random_state for reproducibility if available, else use random module r = random_state if random_state else random - + # Sample from the darker end of the 'Blues' colormap (e.g., 0.4 to 1.0) # 0.0 is white/light, 1.0 is dark blue min_val, max_val = 0.4, 1.0 color_val = r.uniform(min_val, max_val) - + # Get color from matplotlib colormap rgba = plt.cm.Blues(color_val) return mcolors.to_hex(rgba) diff --git a/pyproject.toml b/pyproject.toml index 3d0dc4c..5286dbd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,7 +6,7 @@ readme = "README.md" requires-python = ">=3.12" dependencies = [ "marimo>=0.18.0", - "modin>=0.37.1", + "modin[dask]>=0.37.1", "numpy>=2.3.5", "ollama>=0.6.1", "openai>=2.9.0", @@ -14,5 +14,9 @@ dependencies = [ "pyzmq>=27.1.0", "requests>=2.32.5", "taguette>=1.5.1", - "wordcloud>=1.9.4", + "wordcloud>=1.9.5", ] + + +[tool.uv.sources] +wordcloud = { git = "https://github.com/amueller/word_cloud.git" } diff --git a/utils/__init__.py b/utils/__init__.py index c36fa01..40eea45 100644 --- a/utils/__init__.py +++ b/utils/__init__.py @@ -2,4 +2,4 @@ from 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