Getting started
pip install pulp-sdk
Docs
sample.txt2 paras · 160 chars
Sections
§1 Introduction
Paras
¶1: first paragraph block
¶2: second paragraph block
Sentences
S1S2S3S4
Clauses
C1C2C3C4C5C6
Claims
Claim 1Claim 2Claim 3
Phrases
NPVPNPVPPPNP
Named Entities
Pulp [ORG]
Words
ifwewaitforcertaintywewillbe+20 more
Characters
0 → 159
Special Characters
spaces × 27punct × 8nbsp × 0
Special Patterns
0 patterns detected
RootCause
Ethos
—
Pathos
—
Logos
—
Kairos
—
Style
—
Clarity
—
Focus
—
Awareness
—
Persuasive Velocity—
StemReferences
CensusFECCongressFed. Reg.RegulationsLegiScanGovInfoGDELTCivicWikimediaData.govPodcast Idx
AdCanopy
rank
Demographics
life_stageyoung_adult
education_levelbachelors
locationurban
occupationtech
Psychographics
Impelling
Compelling
Repelling
Mindstate
alpha 10 Hzcalm
Environment
vision onhearing onsmell offtouch offtaste off
Memory
purchases 12content 48brands 5
Vision
motivationdesirefear
NectarRewards
define
PoisonIvy
apply
GrapeVine
post
WebSoil
heatmap
DomainCrust
price
CodeMantle
trace
ServerCore
uptimeresize
WarpDisplays
q3-report.pdf
chart.png
keynote.mp4
WeftConversations
ThreadsChatInlineSide panels
DyeMedia
TextToday
ImageToday
SoundSoon
VideoSoon
BightInteractions
MouseKeyboardVoice · soonCombos · soon
Production
Coming soon
Demographics
Who they are on paper: age, role, tenure, geography, and affiliations. The census layer. Necessary, and famously insufficient, which is why it is one space out of six and not six out of six like everyone else’s model.
createreadupdatedelete
| Verb | Signature | Description |
|---|---|---|
create | create(spec) | Initialize this class of state for a persona |
read | read() | Return the current state snapshot |
update | update(patch) | Apply a typed, domain-checked patch to the state |
delete | delete() | Remove this class of state from the persona |
from pulp import windfall
p = windfall.trueaura.persona(frame="urban_parents")
state = p.demographics.read()
print(state.role)
p.demographics.update(# typed patch, domain-checked)