Make wordcloud script more generic

bin/create_wordcloud.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python
 
 import argparse
+from typing import Dict
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -9,33 +10,39 @@
 from wordcloud import WordCloud
 
 
-def get_wordcloud(community_tool_path: str, mask_figure: str, stats_column: str, wordcloud_output_path: str) -> None:
+def prepare_data(table_path: str, name_col: str, stat_col: str) -> Dict:
     """
-    Generate a wordcloud based on the counts for each Galaxy wrapper id
+    Prepare data to create dictionary with key being the name and
+    value the stat/counts
 
-    :param community_tool_path: Dataframe that must
+    :param table_path: Path TSV file with name and stats
         have the columns "Galaxy wrapper id" and `stats_column`
-    :param mask_figure: a figure that is used to render the wordcloud
-        E.g. a nice shape to highlight your community
-    :param stats_column: Column name of the
-        column with usage statistics in the table
-    :param wordcloud_output_path: Path to store the wordcloud
+    :param name_col: Name of the column with name for wordcloud
+    :param stat_col: Name of columns with usage/count
     """
+    table = pd.read_csv(table_path, sep="\t")
 
-    community_tool_stats = pd.read_csv(community_tool_path, sep="\t")
-
-    assert (
-        stats_column in community_tool_stats
-    ), f"Stats column: {stats_column} not found in table!"  # check if the stats column is there
+    assert stat_col in table, f"Stat column: {stat_col} not found in table!"
+    assert name_col in table, f"Name column: {name_col} not found in table!"
 
     # some tools are not used at all
-    community_tool_stats[stats_column] = community_tool_stats[stats_column].fillna(value=0)
+    table[stat_col] = table[stat_col].fillna(value=0)
+
+    # create dictionary with key being the name and value the stat/counts
+    freq = pd.Series(table[stat_col].values, index=table[name_col]).to_dict()
+
+    return freq
 
-    # create the word cloud
-    frec = pd.Series(
-        community_tool_stats[stats_column].values, index=community_tool_stats["Galaxy wrapper id"]
-    ).to_dict()
 
+def generate_wordcloud(freq: dict, mask_figure: str) -> WordCloud:
+    """
+    Generate a wordcloud based on counts
+
+    :param freq: Dictionary with key being the name and
+    value the stat/counts
+    :param mask_figure: a figure that is used to render the wordcloud
+        E.g. a nice shape to highlight your community
+    """
     mask = np.array(Image.open(mask_figure))
     mask[mask == 0] = 255  # set 0 in array to 255 to work with wordcloud
 
@@ -44,43 +51,52 @@ def get_wordcloud(community_tool_path: str, mask_figure: str, stats_column: str,
         background_color="rgba(255, 255, 255, 0)",
         random_state=42,
     )
+    wc.generate_from_frequencies(freq)
+    return wc
 
-    wc.generate_from_frequencies(frec)
 
+def export_wordcloud(wc: WordCloud, wordcloud_output_path: str) -> None:
+    """
+    Export wordcloud to file
+
+    :param wordcloud_output_path: Path to store the wordcloud
+    """
     fig, ax = plt.subplots(figsize=(13, 5))
     ax.imshow(wc)
-
     plt.axis("off")
     plt.tight_layout(pad=0)
-
     plt.savefig(wordcloud_output_path)
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Create wordcloud from \
-            TSV file based on Galaxy usage statistics"
-    )
+    parser = argparse.ArgumentParser(description="Create wordcloud from TSV file")
     parser.add_argument(
         "--table",
         "-ta",
         required=True,
-        help="Path to TSV file with tools and stats",
+        help="Path to TSV file with name and stats",
     )
     parser.add_argument(
-        "--stats_column",
+        "--name_col",
+        "-nc",
+        required=True,
+        help="Name of the column with name to use in wordcloud",
+    )
+    parser.add_argument(
+        "--stat_col",
         "-sc",
         required=True,
-        help="Name of the column with usage statistics",
+        help="Name of the column with statistic to build the wordcloud",
     )
     parser.add_argument(
         "--output",
         "-out",
         required=True,
         help="Path to HTML output",
     )
-
     parser.add_argument("--wordcloud_mask", "-wcm", required=False, help="Mask figure to generate the wordcloud")
 
     args = parser.parse_args()
-    get_wordcloud(args.table, args.wordcloud_mask, args.stats_column, args.output)
+    frec = prepare_data(args.table, args.name_col, args.stat_col)
+    wc = generate_wordcloud(frec, args.wordcloud_mask)
+    export_wordcloud(wc, args.output)

bin/format_tools.sh

@@ -9,6 +9,7 @@ python bin/create_interactive_table.py \
 
 python bin/create_wordcloud.py \
         --table "results/all_tools.tsv" \
+        --name_col "Galaxy wrapper id" \
+        --stat_col "No. of tool users (2022-2023) (usegalaxy.eu)" \
         --wordcloud_mask "data/usage_stats/wordcloud_mask.png" \
-        --output "results/all_tools_wordcloud.png" \
-        --stats_column "No. of tool users (2022-2023) (usegalaxy.eu)"
+        --output "results/all_tools_wordcloud.png" \