Exclude non-campaign posts from format/day/traction breakdowns
Added NON_CAMPAIGN_DATES (starting with 02/09), excluded the same way REPOST_DATES already is — a real TXproducts post, but not part of the 24-post branding campaign, so it shouldn't skew "what worked" findings that are specifically about the campaign's own content. Also closed out July's "end-of-week boss report" outstanding item per Mckinley: discarded, no longer tracked. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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@@ -46,6 +46,13 @@ MANUAL_POST_TITLES = {
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# who reposts TXproducts' own content, so that direction isn't tracked at all.
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REPOST_DATES = {"2026-07-10"}
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# Posts that exist in the LinkedIn export but aren't part of the 24-post branding
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# campaign (confirmed by Mckinley 2026-09-14, starting with 02/09) — excluded from
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# every format/day/traction breakdown and the Audience/Team audit the same way
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# REPOST_DATES is, so a one-off non-campaign post can't skew "what worked" findings
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# that are specifically about the campaign's own content.
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NON_CAMPAIGN_DATES = {"2026-09-02"}
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# LinkedIn's export doesn't distinguish carousel/document posts from generic Image — override by hand.
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MANUAL_CONTENT_TYPES = {
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"2026-07-09": "Carousel",
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@@ -2945,12 +2952,14 @@ _real_eng_pct = engagement_audit.real_eng_pct
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def _reports_posts_f(month_value="2026-07"):
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"""Shared by every Roadmap-family insights page — the selected month's posts with
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Shares/Weekday columns added, so each page computes from the identical base
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instead of drifting. Excludes REPOST_DATES: a reshare of someone else's post, not
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TXproducts' own content, so it doesn't belong in a format/day/traction breakdown
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of what TXproducts published."""
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instead of drifting. Excludes REPOST_DATES (a reshare of someone else's post, not
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TXproducts' own content) and NON_CAMPAIGN_DATES (a real TXproducts post, but not
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part of the 24-post branding campaign) — neither belongs in a format/day/traction
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breakdown of what the campaign itself published."""
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stats = report.compute_period_stats(_build_report_ctx(), month_value)
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posts_f = stats["posts_f"].copy()
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posts_f = posts_f[~posts_f["Created date"].dt.strftime("%Y-%m-%d").isin(REPOST_DATES)]
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excluded_dates = REPOST_DATES | NON_CAMPAIGN_DATES
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posts_f = posts_f[~posts_f["Created date"].dt.strftime("%Y-%m-%d").isin(excluded_dates)]
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posts_f["Shares"] = posts_f["Comments"].fillna(0) + posts_f["Reposts"].fillna(0)
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posts_f["Weekday"] = posts_f["Created date"].dt.day_name()
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return posts_f
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@@ -96,9 +96,6 @@ NOTES = {
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"Aug 3 and falls outside this report.",
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],
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"outstanding": [
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"The end-of-week report explaining every dashboard chart to the bosses was "
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"due Fri Jul 31, status needs confirming with the user before marking this "
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"done.",
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"The conversion-rate weekly-bucket and 3 to 7 day match-window widening "
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"discussed Jul 28, to make the follow-attribution pattern more convincing "
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"across multiple weeks, is still conceptual, not implemented.",
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