RRepoGEO

REPOGEO REPORT · LITE

eakmanrq/sqlframe

Default branch main · commit 7ed017c4 · scanned 6/9/2026, 8:57:12 PM

GitHub: 510 stars · 25 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface eakmanrq/sqlframe, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant repository topics

    Why:

    COPY-PASTE FIX
    ["pyspark", "dataframe", "sql", "database", "data-transformation", "etl", "bigquery", "snowflake", "duckdb", "postgres", "databricks", "redshift"]
  • mediumreadme#2
    Refine README's opening paragraph for problem-solution clarity

    Why:

    CURRENT
    SQLFrame implements the PySpark DataFrame API in order to enable running transformation pipelines directly on database engines - no Spark clusters or dependencies required.
    COPY-PASTE FIX
    SQLFrame solves the challenge of running PySpark DataFrame transformations directly on your database engine, eliminating the need for Spark clusters and dependencies. It provides a universal DataFrame API for efficient, native SQL execution across BigQuery, Snowflake, DuckDB, Postgres, and other popular databases.
  • lowcomparison#3
    Add a 'Comparison to Alternatives' section

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

(Add content here explaining how SQLFrame's PySpark-compatible DataFrame API for direct database execution differs from tools like Ibis (general Pythonic DataFrame API), dbt (SQL-first transformations), SQLAlchemy (low-level SQL toolkit), and PandaSQL (pandas to SQL conversion).)

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface eakmanrq/sqlframe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
dbt
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. dbt · recommended 1×
  2. Ibis · recommended 1×
  3. Spark SQL · recommended 1×
  4. SQLAlchemy Core · recommended 1×
  5. DuckDB · recommended 1×
  • CATEGORY QUERY
    How can I run DataFrame-style data transformations directly on my database engine?
    you: not recommended
    AI recommended (in order):
    1. dbt
    2. Ibis
    3. Spark SQL
    4. SQLAlchemy Core
    5. DuckDB
    6. Polars

    AI recommended 6 alternatives but never named eakmanrq/sqlframe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help convert Python data manipulation code into optimized SQL for various databases?
    you: not recommended
    AI recommended (in order):
    1. PandaSQL (yhat/pandasql)
    2. SQLAlchemy (sqlalchemy/sqlalchemy)
    3. Ibis (ibis-project/ibis)
    4. dbt (dbt-labs/dbt-core)
    5. Polars (pola-rs/polars)
    6. PySpark (apache/spark)

    AI recommended 6 alternatives but never named eakmanrq/sqlframe. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of eakmanrq/sqlframe?
    pass
    AI named eakmanrq/sqlframe explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts eakmanrq/sqlframe in production, what risks or prerequisites should they evaluate first?
    pass
    AI named eakmanrq/sqlframe explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo eakmanrq/sqlframe solve, and who is the primary audience?
    pass
    AI named eakmanrq/sqlframe explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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eakmanrq/sqlframe — RepoGEO report