Trendflow

A type-safe Python library for querying, streaming, and exporting Google Trends data

• GitHub: https://github.com/dariomory/trendflow/
• PyPI package: https://pypi.org/project/trendflow-py/ (install name trendflow-py; import as trendflow)
• Created by: Dario Mory | GitHub https://github.com/dariomory | PyPI https://pypi.org/user/dariomory/
• Free software: MIT License

Features

• Type-safe API: regions, timeframes, resolutions, and export formats use enums instead of raw strings.
• Rich queries: interest over time, regional breakdown, live trending searches, and related queries, with dataclass results.
• Exports: JSON, CSV, or load results into a pandas DataFrame.

Usage

import trendflow
from trendflow import Region, Timeframe, Resolution, ExportFormat

# Initialize client (optional API config)
tf = trendflow.Client(language="en", timeout=10)

# --- Enums for type safety ---
# Region.US, Region.GB, Region.DE ...
# Timeframe.PAST_DAY, Timeframe.PAST_WEEK, Timeframe.PAST_YEAR, Timeframe.PAST_5_YEARS
# Resolution.COUNTRY, Resolution.REGION, Resolution.CITY

# Fetch interest over time
data = tf.interest_over_time(
    keywords=["Python", "JavaScript", "Rust"],
    timeframe=Timeframe.PAST_YEAR,
    region=Region.US,
)

# Dataclass-backed results
print(data.keywords)        # ["Python", "JavaScript", "Rust"]
print(data.granularity)     # "weekly"
print(data.points)          # list of TrendPoint(date, scores: dict)

# Get regional breakdown (region defaults to Region.US)
regional = tf.interest_by_region(
    keyword="Python",
    resolution=Resolution.COUNTRY,
)

# Trending searches right now
trending = tf.trending_now(region=Region.US)
for item in trending.results:
    print(item.title, item.traffic, item.articles)  # TrendingItem dataclass

# Related queries — returns RelatedResult dataclass
related = tf.related_queries("machine learning")
for query in related.top:
    print(query.term, query.value)    # RelatedQuery(term, value)
for query in related.rising:
    print(query.term, query.breakout) # RelatedQuery(term, breakout%)

# --- Exports ---
data.export(ExportFormat.CSV,  path="trends.csv")
data.export(ExportFormat.JSON, path="trends.json")
data.to_dataframe()  # pandas DataFrame

Documentation

Documentation is built with Zensical and deployed to GitHub Pages.

• Live site: https://dariomory.github.io/trendflow/
• Preview locally: just docs-serve (serves at http://localhost:8000)
• Build: just docs-build

API documentation is auto-generated from docstrings using mkdocstrings.

Docs deploy automatically on push to master or main via GitHub Actions.

Development

To set up for local development:

# Clone your fork
git clone git@github.com:dariomory/trendflow.git
cd trendflow

# Install in editable mode with live updates
uv tool install --editable .

This installs the CLI globally but with live updates - any changes you make to the source code are immediately available when you run trendflow.

Run tests:

uv run pytest

Run quality checks (format, lint, type check, test):

just qa

Author

Trendflow was created in 2026 by Dario Mory