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311 lines
15 KiB
Python
311 lines
15 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import seaborn as sns
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from matplotlib.gridspec import GridSpec
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from matplotlib.patches import Patch
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sns.set_theme(style="darkgrid")
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plt.rcParams.update({
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'figure.facecolor': '#0d1117',
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'axes.facecolor': '#161b22',
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'text.color': '#e6edf3',
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'axes.labelcolor': '#e6edf3',
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'xtick.color': '#8b949e',
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'ytick.color': '#8b949e',
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'grid.color': '#21262d',
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'axes.edgecolor': '#30363d',
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'font.family': 'sans-serif',
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'font.size': 11,
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})
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# === ALL SUBREDDITS (consistent across every chart) ===
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data = {
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'r/ClaudeAI': {'subs': 509, 'avg_up': 8, 'avg_com': 5.2, 'max_up': 113, 'relevance': 10, 'tier': 1},
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'r/ChatGPTCoding': {'subs': 357, 'avg_up': 46, 'avg_com': 25.0, 'max_up': 883, 'relevance': 9, 'tier': 1},
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'r/LocalLLaMA': {'subs': 628, 'avg_up': 3, 'avg_com': 4.2, 'max_up': 29, 'relevance': 9, 'tier': 1},
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'r/cursor': {'subs': 122, 'avg_up': 12, 'avg_com': 13.1, 'max_up': 129, 'relevance': 8, 'tier': 2},
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'r/rust': {'subs': 388, 'avg_up': 19, 'avg_com': 8.7, 'max_up': 133, 'relevance': 8, 'tier': 2},
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'r/commandline': {'subs': 115, 'avg_up': 13, 'avg_com': 4.4, 'max_up': 230, 'relevance': 8, 'tier': 2},
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'r/opensource': {'subs': 326, 'avg_up': 18, 'avg_com': 6.1, 'max_up': 185, 'relevance': 7, 'tier': 3},
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'r/neovim': {'subs': 148, 'avg_up': 28, 'avg_com': 11.9, 'max_up': 278, 'relevance': 7, 'tier': 3},
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'r/selfhosted': {'subs': 698, 'avg_up': 18, 'avg_com': 9.0, 'max_up': 248, 'relevance': 6, 'tier': 3},
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'r/ollama': {'subs': 101, 'avg_up': 9, 'avg_com': 5.3, 'max_up': 84, 'relevance': 6, 'tier': 3},
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'r/programming': {'subs': 6841,'avg_up': 125, 'avg_com': 26.4, 'max_up': 2566, 'relevance': 5, 'tier': 4},
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'r/linux': {'subs': 1821,'avg_up': 161, 'avg_com': 32.0, 'max_up': 890, 'relevance': 5, 'tier': 4},
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'r/artificial': {'subs': 1224,'avg_up': 60, 'avg_com': 24.0, 'max_up': 569, 'relevance': 5, 'tier': 4},
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'r/MachineLearning':{'subs':3024,'avg_up': 23, 'avg_com': 11.7, 'max_up': 208, 'relevance': 5, 'tier': 4},
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'r/SideProject': {'subs': 629, 'avg_up': 1, 'avg_com': 0.6, 'max_up': 4, 'relevance': 4, 'tier': 5},
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}
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tier_palette = {1: '#58a6ff', 2: '#3fb950', 3: '#d2a8ff', 4: '#f0883e', 5: '#f85149'}
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tier_names = {1: 'Tier 1: Perfect Fit', 2: 'Tier 2: Strong Fit', 3: 'Tier 3: Good Fit',
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4: 'Tier 4: Broad Reach', 5: 'Tier 5: Skip'}
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subs_list = list(data.keys())
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colors = [tier_palette[data[s]['tier']] for s in subs_list]
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# Hour data (Pacific) — ALL subs
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hour_data = {
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'r/ClaudeAI': [4,5,8,8,5,11,13,11,12,10,11,2,0,0,0,0,0,0,0,0,0,0,0,0],
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'r/ChatGPTCoding': [1,4,9,4,4,3,3,5,4,5,8,7,7,5,4,2,7,4,4,2,2,1,2,3],
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'r/LocalLLaMA': [0,3,2,5,6,6,5,12,11,6,7,8,0,0,0,0,3,6,7,0,6,4,3,0],
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'r/cursor': [2,1,5,1,5,5,8,8,8,7,9,4,9,2,5,2,2,4,3,1,4,2,2,1],
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'r/rust': [4,5,8,6,5,7,6,9,8,7,8,4,5,2,2,2,3,2,2,1,1,2,1,0],
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'r/commandline': [1,3,6,3,7,9,8,3,4,6,3,4,4,8,6,5,1,3,2,4,4,2,1,3],
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'r/opensource': [1,3,7,3,6,1,4,4,9,5,6,3,7,10,5,7,6,3,1,0,3,2,2,2],
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'r/neovim': [4,5,5,3,3,6,8,1,4,3,8,8,3,4,7,2,4,7,2,1,3,4,3,2],
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'r/selfhosted': [3,3,5,4,7,5,4,6,8,11,8,7,3,3,2,5,2,2,2,2,3,3,1,1],
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'r/ollama': [2,6,6,6,3,2,4,7,10,6,5,5,8,5,2,3,6,3,2,2,2,1,2,2],
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'r/programming': [3,3,4,7,7,11,8,6,6,6,2,10,4,1,1,2,5,1,2,0,2,4,3,2],
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'r/linux': [3,4,6,2,4,3,3,1,4,7,7,10,6,7,5,6,5,5,5,1,1,2,2,1],
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'r/artificial': [2,4,8,5,5,0,5,7,7,5,4,6,3,8,3,3,2,3,6,2,4,3,3,2],
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'r/MachineLearning':[7,3,2,3,4,4,7,1,11,6,3,7,4,5,6,3,3,6,3,1,2,2,4,3],
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'r/SideProject': [0,0,0,0,0,0,0,0,13,11,18,13,11,8,10,11,5,0,0,0,0,0,0,0],
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}
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# Day data
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day_names = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
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day_data = {
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'r/ChatGPTCoding': [19,17,15,12,12,9,16],
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'r/cursor': [26,21,12,0,0,21,20],
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'r/commandline': [19,13,15,12,13,11,17],
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'r/opensource': [14,20,11,11,17,13,14],
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'r/neovim': [19,17,16,9,7,9,23],
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'r/rust': [23,39,20,0,0,0,18],
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'r/ollama': [11,20,18,15,16,8,12],
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'r/linux': [8,24,25,11,13,11,8],
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'r/artificial': [18,22,16,10,13,11,10],
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'r/MachineLearning':[21,23,11,7,14,12,12],
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}
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# ======================== FIGURE ========================
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fig = plt.figure(figsize=(24, 36))
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fig.suptitle('jcode Reddit Strategy Dashboard', fontsize=28, fontweight='bold',
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color='#58a6ff', y=0.985)
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fig.text(0.5, 0.979, 'Complete analysis of 15 subreddits for promoting jcode (Rust AI coding agent CLI) | All times Pacific',
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ha='center', fontsize=13, color='#8b949e')
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gs = GridSpec(6, 2, figure=fig, hspace=0.32, wspace=0.28,
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top=0.965, bottom=0.02, left=0.09, right=0.95)
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# ---- LEGEND (shared) ----
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legend_elements = [Patch(facecolor=tier_palette[t], label=tier_names[t]) for t in [1,2,3,4,5]]
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# ========== 1. COMPOSITE RANKING ==========
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ax1 = fig.add_subplot(gs[0, :])
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composite = []
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for s in subs_list:
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d = data[s]
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composite.append(d['relevance'] * (d['avg_up'] + d['avg_com'] * 2))
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sort_idx = np.argsort(composite)[::-1]
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sorted_subs = [subs_list[i] for i in sort_idx]
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sorted_composite = [composite[i] for i in sort_idx]
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sorted_colors = [colors[i] for i in sort_idx]
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bars = ax1.barh(range(len(sorted_subs)), sorted_composite, color=sorted_colors, edgecolor='none', height=0.7)
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ax1.set_yticks(range(len(sorted_subs)))
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ax1.set_yticklabels(sorted_subs, fontsize=11, fontweight='bold')
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ax1.invert_yaxis()
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ax1.set_xlabel('Composite Score = Relevance x (Avg Upvotes + 2 x Avg Comments)', fontsize=11)
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ax1.set_title('OVERALL RANKING', fontsize=18, fontweight='bold', pad=15)
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for i, (bar, val) in enumerate(zip(bars, sorted_composite)):
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ax1.text(val + max(sorted_composite)*0.01, i, f'{val:.0f}', va='center', fontsize=10, color='#e6edf3')
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ax1.legend(handles=legend_elements, loc='lower right', fontsize=9, facecolor='#161b22', edgecolor='#30363d')
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# ========== 2. SUBSCRIBERS vs ENGAGEMENT ==========
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ax2 = fig.add_subplot(gs[1, 0])
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subs_k = [data[s]['subs'] for s in subs_list]
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avg_up = [data[s]['avg_up'] for s in subs_list]
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relevances = [data[s]['relevance'] for s in subs_list]
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sizes = [r*35 for r in relevances]
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ax2.scatter(subs_k, avg_up, s=sizes, c=colors, alpha=0.85, edgecolors='white', linewidth=0.5, zorder=5)
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for i, s in enumerate(subs_list):
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ax2.annotate(s.replace('r/', ''), (subs_k[i], avg_up[i]), fontsize=7.5, color='#c9d1d9',
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xytext=(6, 4), textcoords='offset points')
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ax2.set_xlabel('Subscribers (K)', fontsize=11)
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ax2.set_ylabel('Avg Upvotes per Post', fontsize=11)
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ax2.set_title('SUBSCRIBERS vs ENGAGEMENT', fontsize=14, fontweight='bold')
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ax2.set_xscale('log')
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# ========== 3. AVG COMMENTS ==========
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ax3 = fig.add_subplot(gs[1, 1])
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avg_com = [data[s]['avg_com'] for s in subs_list]
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sort_c = np.argsort(avg_com)[::-1]
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ax3.barh(range(len(subs_list)), [avg_com[i] for i in sort_c],
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color=[colors[i] for i in sort_c], edgecolor='none', height=0.65)
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ax3.set_yticks(range(len(subs_list)))
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ax3.set_yticklabels([subs_list[i] for i in sort_c], fontsize=10)
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ax3.invert_yaxis()
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ax3.set_xlabel('Avg Comments per Post', fontsize=11)
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ax3.set_title('DISCUSSION DEPTH', fontsize=14, fontweight='bold')
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for i, idx in enumerate(sort_c):
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ax3.text(avg_com[idx] + 0.3, i, f'{avg_com[idx]:.1f}', va='center', fontsize=9, color='#8b949e')
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# ========== 4. HEATMAP — ALL SUBS ==========
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ax4 = fig.add_subplot(gs[2, :])
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heat_subs = list(hour_data.keys())
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heat_matrix = np.array([hour_data[s] for s in heat_subs], dtype=float)
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# Normalize each row
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row_sums = heat_matrix.sum(axis=1, keepdims=True)
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row_sums[row_sums == 0] = 1
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heat_norm = heat_matrix / row_sums * 100
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im = ax4.imshow(heat_norm, cmap='YlOrRd', aspect='auto', interpolation='nearest')
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ax4.set_yticks(range(len(heat_subs)))
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ax4.set_yticklabels(heat_subs, fontsize=10)
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ax4.set_xticks(range(24))
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ax4.set_xticklabels([f'{h}' for h in range(24)], fontsize=9)
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ax4.set_xlabel('Hour of Day (Pacific Time)', fontsize=12)
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ax4.set_title('POSTING ACTIVITY HEATMAP BY HOUR', fontsize=16, fontweight='bold', pad=12)
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cbar = plt.colorbar(im, ax=ax4, shrink=0.5, pad=0.02)
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cbar.set_label('% of posts in that hour', color='#8b949e', fontsize=10)
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cbar.ax.yaxis.set_tick_params(color='#8b949e')
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plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#8b949e')
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# Mark peak hour per sub
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for i in range(len(heat_subs)):
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row = heat_norm[i]
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if row.max() > 0:
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peak_h = np.argmax(row)
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ax4.text(peak_h, i, '*', ha='center', va='center', fontsize=16, color='black', fontweight='bold')
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# Add morning/afternoon/evening labels
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ax4.axvline(x=5.5, color='#58a6ff', linewidth=0.5, alpha=0.4, linestyle='--')
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ax4.axvline(x=11.5, color='#f0883e', linewidth=0.5, alpha=0.4, linestyle='--')
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ax4.axvline(x=17.5, color='#d2a8ff', linewidth=0.5, alpha=0.4, linestyle='--')
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ax4.text(2.5, -0.8, 'Late Night', ha='center', fontsize=8, color='#8b949e')
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ax4.text(8.5, -0.8, 'Morning', ha='center', fontsize=8, color='#58a6ff')
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ax4.text(14.5, -0.8, 'Afternoon', ha='center', fontsize=8, color='#f0883e')
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ax4.text(20.5, -0.8, 'Evening', ha='center', fontsize=8, color='#d2a8ff')
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# ========== 5. DAY OF WEEK ==========
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ax5 = fig.add_subplot(gs[3, 0])
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day_subs_list = list(day_data.keys())
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x = np.arange(7)
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n = len(day_subs_list)
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width = 0.8 / n
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cmap_day = plt.cm.Set2
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for i, sub in enumerate(day_subs_list):
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vals = day_data[sub]
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total = sum(vals)
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if total == 0: continue
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pcts = [v/total*100 for v in vals]
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c = tier_palette[data[sub]['tier']]
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ax5.bar(x + i*width - n*width/2, pcts, width, label=sub.replace('r/', ''), color=c, alpha=0.7, edgecolor='none')
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ax5.set_xticks(x)
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ax5.set_xticklabels(day_names, fontsize=11, fontweight='bold')
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ax5.set_ylabel('% of posts', fontsize=11)
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ax5.set_title('DAY OF WEEK DISTRIBUTION', fontsize=14, fontweight='bold')
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ax5.legend(fontsize=6.5, facecolor='#161b22', edgecolor='#30363d', loc='upper right', ncol=2)
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# ========== 6. VIRAL POTENTIAL ==========
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ax6 = fig.add_subplot(gs[3, 1])
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max_up = [data[s]['max_up'] for s in subs_list]
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sort_m = np.argsort(max_up)[::-1]
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ax6.barh(range(len(subs_list)), [max_up[i] for i in sort_m],
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color=[colors[i] for i in sort_m], edgecolor='none', height=0.65)
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ax6.set_yticks(range(len(subs_list)))
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ax6.set_yticklabels([subs_list[i] for i in sort_m], fontsize=10)
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ax6.invert_yaxis()
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ax6.set_xlabel('Max Upvotes (Recent Posts)', fontsize=11)
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ax6.set_title('VIRAL POTENTIAL', fontsize=14, fontweight='bold')
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for i, idx in enumerate(sort_m):
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ax6.text(max_up[idx] + 20, i, f'{max_up[idx]:,}', va='center', fontsize=9, color='#8b949e')
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# ========== 7. BEST TIME TO POST (visual timeline) ==========
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ax_time = fig.add_subplot(gs[4, :])
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best_times = {
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'r/ClaudeAI': (6, 9, 'Tue-Wed'),
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'r/ChatGPTCoding': (10, 12, 'Monday'),
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'r/LocalLLaMA': (7, 9, 'Tue-Wed'),
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'r/cursor': (10, 12, 'Monday'),
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'r/rust': (7, 10, 'Tuesday'),
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'r/commandline': (5, 6, 'Mon/Sun'),
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'r/opensource': (8, 13, 'Tue/Fri'),
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'r/neovim': (6, 11, 'Sun/Mon'),
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'r/selfhosted': (8, 10, 'Tuesday'),
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'r/ollama': (8, 12, 'Tuesday'),
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'r/programming': (5, 8, 'Monday'),
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'r/linux': (9, 12, 'Tue-Wed'),
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'r/artificial': (7, 9, 'Tuesday'),
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'r/MachineLearning':(8, 11, 'Tuesday'),
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'r/SideProject': (9, 12, 'Wed'),
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}
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y_positions = list(range(len(best_times)))
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for i, (sub, (start, end, day)) in enumerate(best_times.items()):
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c = tier_palette[data[sub]['tier']]
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ax_time.barh(i, end - start, left=start, height=0.6, color=c, alpha=0.85, edgecolor='white', linewidth=0.5)
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ax_time.text(end + 0.3, i, f'{start}am-{end}{"pm" if end >= 12 else "am"} ({day})',
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va='center', fontsize=9, color='#c9d1d9')
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ax_time.set_yticks(y_positions)
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ax_time.set_yticklabels(list(best_times.keys()), fontsize=10)
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ax_time.invert_yaxis()
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ax_time.set_xlim(0, 24)
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ax_time.set_xticks(range(0, 25, 2))
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ax_time.set_xticklabels([f'{h}:00' for h in range(0, 25, 2)], fontsize=9)
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ax_time.set_xlabel('Pacific Time', fontsize=12)
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ax_time.set_title('BEST TIME TO POST (Pacific)', fontsize=16, fontweight='bold', pad=12)
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ax_time.axvline(x=8, color='#3fb950', linewidth=1, alpha=0.3, linestyle='--')
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ax_time.axvline(x=12, color='#f0883e', linewidth=1, alpha=0.3, linestyle='--')
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ax_time.legend(handles=legend_elements, loc='upper right', fontsize=8, facecolor='#161b22', edgecolor='#30363d')
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# ========== 8. STRATEGY TABLE ==========
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ax7 = fig.add_subplot(gs[5, :])
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ax7.axis('off')
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schedule = [
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['Subreddit', 'Subs', 'Best Day', 'Best Time', 'Approach', 'Score'],
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['r/ClaudeAI', '509K', 'Tue-Wed', '6-9am', '"Built with Claude" flair', '675'],
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['r/ChatGPTCoding', '357K', 'Monday', '10am-12pm','Demo video, compare to Cursor', '675'],
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['r/LocalLLaMA', '628K', 'Tue-Wed', '7-9am', 'Technical deep-dive, OSS angle', '103'],
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['r/cursor', '122K', 'Monday', '10am-12pm','CLI alternative to Cursor', '305'],
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['r/rust', '388K', 'Tuesday', '7-10am', 'Project flair, Rust internals', '297'],
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['r/commandline', '115K', 'Mon/Sun', '5am / 1pm','GIF demo, CLI showcase', '174'],
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['r/neovim', '148K', 'Sunday', '6am/10am', 'Terminal-first, vim integration', '363'],
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['r/opensource', '326K', 'Tue/Fri', '8am / 1pm','OSS launch announcement', '212'],
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['r/selfhosted', '698K', 'Tuesday', '8-10am', 'Self-hostable AI coding agent', '216'],
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['r/ollama', '101K', 'Tuesday', '8am-12pm', 'Local model integration angle', '95'],
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['r/programming', '6.8M', 'Monday', '5-8am', 'Blog post / deep technical', '888'],
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['r/linux', '1.8M', 'Tue-Wed', '9am-12pm', 'Linux-native CLI tool angle', '1125'],
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['r/artificial', '1.2M', 'Tuesday', '7-9am', 'AI agent capabilities showcase', '540'],
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['r/MachineLearning','3M', 'Tuesday', '8-11am', 'Technical architecture post', '233'],
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['r/SideProject', '629K', 'Any', '9am-3pm', 'SKIP - zero engagement', '9'],
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]
|
|
|
|
table = ax7.table(cellText=schedule[1:], colLabels=schedule[0],
|
|
cellLoc='center', loc='center',
|
|
colColours=['#21262d']*6)
|
|
table.auto_set_font_size(False)
|
|
table.set_fontsize(10)
|
|
table.scale(1, 1.6)
|
|
|
|
# Color the table
|
|
tier_for_sub = {s: data[s]['tier'] for s in data}
|
|
for key, cell in table.get_celld().items():
|
|
row, col = key
|
|
cell.set_edgecolor('#30363d')
|
|
if row == 0:
|
|
cell.set_facecolor('#21262d')
|
|
cell.set_text_props(color='#58a6ff', fontweight='bold', fontsize=11)
|
|
else:
|
|
sub_name = schedule[row][0]
|
|
if sub_name in tier_for_sub:
|
|
tier = tier_for_sub[sub_name]
|
|
cell.set_facecolor('#0d1117')
|
|
if col == 0:
|
|
cell.set_text_props(color=tier_palette[tier], fontweight='bold')
|
|
else:
|
|
cell.set_text_props(color='#e6edf3')
|
|
else:
|
|
cell.set_facecolor('#0d1117')
|
|
cell.set_text_props(color='#e6edf3')
|
|
|
|
ax7.set_title('COMPLETE POSTING STRATEGY', fontsize=18, fontweight='bold', pad=20, color='#58a6ff')
|
|
|
|
plt.savefig('/tmp/jcode_reddit_dashboard.png', dpi=150, bbox_inches='tight',
|
|
facecolor='#0d1117', edgecolor='none')
|
|
print("Saved to /tmp/jcode_reddit_dashboard.png")
|