This dataset requires a paid license. Please purchase access at the link below and provide your Hugging Face username. Once purchased, submit an access request on this page. Access is granted manually.

Solana New Pools Liquidity and Momentum Signals

This dataset packages public GeckoTerminal Solana new-pool and trending-pool snapshots into one analysis-ready table for onchain trading research, launch monitoring, liquidity screening, and dashboard building. Each row represents a Solana pool enriched with launch age, liquidity, short-window transaction counts, price-change windows, feed-rank signals, and derived momentum and conviction scores.

This product is built for buyers who need a current, structured view of fresh Solana pool launches without manually jumping between live GeckoTerminal pages. The typical user is not looking for a generic crypto asset list. They are trying to answer questions such as: which newly launched pools already show real liquidity, which ones are getting unusual buy-side activity, which venues dominate the current launch flow, and which pools deserve to be promoted from a casual scan into a serious watchlist. The paid dataset turns those questions into an analysis-ready table instead of a browser tab marathon.

The current build contains 198 rows and 60 columns sourced from GeckoTerminal's public Solana new_pools and trending_pools feeds. Each row carries the raw market-facing fields a trader or analyst would expect, including pool address, venue, token pair, prices, reserve in USD, FDV, market cap when available, short-window price changes, transaction counts, wallet counts, and multi-window volume. On top of that, the dataset adds derived fields such as pool_age_hours, fdv_to_liquidity_ratio, market_cap_to_liquidity_ratio, buy_sell_ratio_h1, volume_to_liquidity_h24, momentum_score, liquidity_score, and launch_conviction_score. Those enrichments are the part buyers would otherwise compute manually after export.

The signal profile of the current market snapshot is commercially meaningful. About 20.2% of the collected pools also surfaced in the trending feed, which gives buyers a fast way to separate "merely new" from "already attracting visible market attention." Roughly 63.13% of rows came from the pump-fun venue, and 98.99% were paired with major quote assets such as SOL, USDC, or USDT. Median liquidity was about $1,646.62, while median twenty-four-hour volume was about $390.33. That makes the dataset useful for screening, comparison, and workflow automation even when some launches are noisy or short-lived.

Compared with free alternatives, the value here is not exclusive ownership of a public feed. The value is the packaging. Public pool feeds are easy to browse casually, but much harder to compare, rank, filter, and audit consistently once the buyer wants to work across dozens or hundreds of launches. The dataset solves the repetitive manual work: flattening multiple live feeds into one table, removing duplicates, preserving rank context, computing derived ratios, normalizing numeric types, and exporting the result in a viewer-compatible parquet format that loads directly into pandas, DuckDB, notebooks, dashboards, or internal ranking pipelines.

The collection process is straightforward and reproducible. The build queries GeckoTerminal's public Solana new_pools and trending_pools endpoints with paced retries to respect rate limits, caches the raw JSON responses locally, deduplicates pools by address, preserves feed-rank context, and computes the derived trading-research features deterministically. No paywalled surface, hidden credential, or private API is required. The output is therefore appropriate for research, internal analysis, monitoring dashboards, and product development workflows.

The free sample proves that the public preview is not marketing fluff. Buyers can inspect the actual schema, confirm that the dataset loads without authentication, review the same columns that appear in the paid version, and decide whether the current field mix fits their workflow. The paid dataset adds the full row count, the complete collection window from this run, the full ranking surface, and the convenience of a ready-to-use research table rather than a tiny inspection subset.

Limitations are important. This is a collection-time snapshot of live feeds, not a historical backtest archive. Pool metrics can change quickly after collection. Some rows expose fdv_usd without market_cap_usd, so buyers should treat FDV and market cap as related but different valuation signals. The product should be used for research, screening, and development rather than as a promise of trading performance. That said, for a buyer already operating in Solana launch markets, it materially reduces setup time between "I saw something interesting" and "I have a sortable table I can actually work with."

Dataset Preview

record_id	pool_id	pool_address	pool_name	base_token_id	quote_token_id	base_token_symbol	quote_token_symbol	dex_id	network_id	primary_feed	appears_in_new_pools_feed	appears_in_trending_pools_feed	new_pools_rank	trending_pools_rank	pool_created_at	pool_age_hours	pool_age_days	base_token_price_usd	quote_token_price_usd	base_token_price_native_currency	quote_token_price_native_currency	base_token_price_quote_token	quote_token_price_base_token	fdv_usd	market_cap_usd	reserve_in_usd	has_market_cap	fdv_to_liquidity_ratio	market_cap_to_liquidity_ratio	price_change_pct_m5	price_change_pct_m15	price_change_pct_m30	price_change_pct_h1	price_change_pct_h6	price_change_pct_h24	txns_buys_m5	txns_sells_m5	txns_buys_h1	txns_sells_h1	txns_buys_h24	txns_sells_h24	unique_traders_m5	unique_traders_h1	unique_traders_h24	volume_usd_m5	volume_usd_h1	volume_usd_h24	buy_sell_ratio_h1	buy_sell_ratio_h24	volume_to_liquidity_h1	volume_to_liquidity_h24	momentum_score	liquidity_score	launch_conviction_score	paired_with_major_quote	source_api_pool_url	source_collection_url	source_domain	last_collected_at
solana::DZadzH1SFDWEnYRsetuJ2AgKFkmmdtjoteYM5cHyCPnx	solana_DZadzH1SFDWEnYRsetuJ2AgKFkmmdtjoteYM5cHyCPnx	DZadzH1SFDWEnYRsetuJ2AgKFkmmdtjoteYM5cHyCPnx	Pnut ⚡️ / SOL	solana_HxewfwveNdguGY4Q4ETEnt8hiT7MqAbMwxj9Kr4HSF3Z	solana_So11111111111111111111111111111111111111112	Pnut ⚡️	SOL	meteora-damm-v2	solana	new_pools	True	False	136.0		2026-06-09 20:31:17+00:00	0.117	0.0049	1.50556e-05	65.459	2.23589e-07	1	2.23589e-07	4.4725e+06	14636.7		17993.3	False	0.813451		-13.835	154.662	154.662	154.662	154.662	154.662	233	54	829	194	829	194	229	726	726	17763.8	58142.8	58142.8	4.2732	4.2732	3.23136	3.23136	79.0604	73.6256	80.6159	True	https://api.geckoterminal.com/api/v2/networks/solana/pools/DZadzH1SFDWEnYRsetuJ2AgKFkmmdtjoteYM5cHyC... [3 more chars]	https://api.geckoterminal.com/api/v2/networks/solana/new_pools	geckoterminal.com	2026-06-09 20:38:18.105124+00:00
solana::Dtu7H3PPqdKwRx4EHR7smAw1MpUd4R8NWXP8xtYE4QjQ	solana_Dtu7H3PPqdKwRx4EHR7smAw1MpUd4R8NWXP8xtYE4QjQ	Dtu7H3PPqdKwRx4EHR7smAw1MpUd4R8NWXP8xtYE4QjQ	MAITIU / SOL	solana_7Pk14rpgjCFDtSMbN9RKAp6wZUJ2YHQdAaniPfPhpump	solana_So11111111111111111111111111111111111111112	MAITIU	SOL	pumpswap	solana	trending_pools	False	True		39.0	2026-06-09 13:08:03+00:00	7.5042	0.3127	8.30036e-05	65.5437	1.23288e-06	1	1.23288e-06	811107	80810.2		20106.3	False	4.01914		-12.204	7.778	9.275	93.155	130.919	197.113	20	24	296	205	4505	3523	26	231	2845	1767.27	26446.3	325674	1.4439	1.27874	1.31532	16.1976	68.8767	77.376	74.6788	True	https://api.geckoterminal.com/api/v2/networks/solana/pools/Dtu7H3PPqdKwRx4EHR7smAw1MpUd4R8NWXP8xtYE4... [3 more chars]	https://api.geckoterminal.com/api/v2/networks/solana/trending_pools	geckoterminal.com	2026-06-09 20:38:18.105124+00:00
solana::AKQyQgEifBBhQmANuKzrRuRGoKSkKBv8NVdccc87FrR8	solana_AKQyQgEifBBhQmANuKzrRuRGoKSkKBv8NVdccc87FrR8	AKQyQgEifBBhQmANuKzrRuRGoKSkKBv8NVdccc87FrR8	Jotchua / USDC	solana_BcHEaaTCvycPwwsJ9yQTXdHP9X2gCLkznDbZ8VySpump	solana_EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v	Jotchua	USDC	pumpswap	solana	trending_pools	False	True		1.0	2026-06-07 05:15:25+00:00	63.3814	2.6409	0.00366788	1.00111	5.62322e-05	0.0152689	0.00368278	271.534	3.6426e+06	3642600.75688463	224870	True	16.1987	16.19872	-1.135	-8.492	-8.138	-18.931	-19.874	195.173	43	13	843	510	28394	20928	43	670	13530	11400.2	179344	6.98249e+06	1.65294	1.35675	0.797546	31.0513	49.721	96.1792	72.1245	True	https://api.geckoterminal.com/api/v2/networks/solana/pools/AKQyQgEifBBhQmANuKzrRuRGoKSkKBv8NVdccc87F... [3 more chars]	https://api.geckoterminal.com/api/v2/networks/solana/trending_pools	geckoterminal.com	2026-06-09 20:38:18.105124+00:00
solana::FEjCV6bhs4U7KqKMqqDKhk2112RUgcDeJRTAgU3bZxoT	solana_FEjCV6bhs4U7KqKMqqDKhk2112RUgcDeJRTAgU3bZxoT	FEjCV6bhs4U7KqKMqqDKhk2112RUgcDeJRTAgU3bZxoT	Dooris / SOL	solana_A5H1UZ99YJFdz6nh4RBNnJS2zg7Zxw1ukyryDgiWMpth	solana_So11111111111111111111111111111111111111112	Dooris	SOL	pumpswap	solana	new_pools	True	False	115.0		2026-06-09 20:31:43+00:00	0.1098	0.0046	1.05701e-05	65.4679	1.5725e-07	1	1.5725e-07	6.35931e+06	10189.3		13390.2	False	0.76095		82.782	82.782	82.782	82.782	82.782	82.782	1641	309	1641	309	1641	309	1476	1476	1476	30494.7	30494.7	30494.7	5.31068	5.31068	2.27739	2.27739	60.5339	70.8317	71.8996	True	https://api.geckoterminal.com/api/v2/networks/solana/pools/FEjCV6bhs4U7KqKMqqDKhk2112RUgcDeJRTAgU3bZ... [3 more chars]	https://api.geckoterminal.com/api/v2/networks/solana/new_pools	geckoterminal.com	2026-06-09 20:38:18.105124+00:00
solana::BBBmFaoX62jvZ7xZxzeEfmCfJxrPNhRj4YjLs91chWAT	solana_BBBmFaoX62jvZ7xZxzeEfmCfJxrPNhRj4YjLs91chWAT	BBBmFaoX62jvZ7xZxzeEfmCfJxrPNhRj4YjLs91chWAT	Dr. GPT / SOL	solana_65DKKq5U5YBDTyd8998HxgYRAzjHnPwiY9UPM4kQpump	solana_So11111111111111111111111111111111111111112	Dr. GPT	SOL	pump-fun	solana	new_pools	True	False	113.0		2026-06-09 20:31:48+00:00	0.1084	0.0045	1.40807e-05	65.4679	2.09621e-07	1	2.09621e-07	4.77052e+06	13870.2		4922.51	False	2.81771		13.847	545.847	545.847	545.847	545.847	545.847	57	24	559	252	559	252	81	655	655	533.762	6515.61	6515.61	2.21825	2.21825	1.32364	1.32364	100	62.5415	69.6453	True	https://api.geckoterminal.com/api/v2/networks/solana/pools/BBBmFaoX62jvZ7xZxzeEfmCfJxrPNhRj4YjLs91ch... [3 more chars]	https://api.geckoterminal.com/api/v2/networks/solana/new_pools	geckoterminal.com	2026-06-09 20:38:18.105124+00:00

Access Requirements (Paid Dataset)

This dataset is behind manual gated access.

To obtain access:

Purchase the dataset here:
https://thearticulated.gumroad.com/l/tchsyv?utm_source=hf_paid_readme&utm_medium=referral&utm_campaign=solana-new-pools-liquidity-and-momentum-signals
Provide your Hugging Face username at checkout.
Return to this Hugging Face page and click:
"Request Access"
Your access will be approved within 1-12 hours.

Once approved, you can use the Python snippet at the bottom of this README to load the dataset.

Related Datasets

Dataset Structure

Total rows: 198

Total columns: 60

Splits

data: 198 rows

Data Files

data: data/data.parquet

Data Dictionary

The table below describes the columns included in this dataset.

column	pandas_dtype	dataset_type	description
record_id	object	string	Text column. Stable unique identifier for the dataset row derived from the Solana network id and pool address.
pool_id	object	string	Text column. GeckoTerminal pool id for the Solana pool.
pool_address	object	string	Text column. Onchain Solana pool address used by GeckoTerminal for the pool.
pool_name	object	string	Text column. Human-readable pool pair name shown by GeckoTerminal, typically base token versus quote token.
base_token_id	object	string	Text column. GeckoTerminal token id for the base token in the pool.
quote_token_id	object	string	Text column. GeckoTerminal token id for the quote token in the pool.
base_token_symbol	object	string	Text column. Base token symbol parsed from the pool name for quick filtering.
quote_token_symbol	object	string	Text column. Quote token symbol parsed from the pool name for quick filtering.
dex_id	object	string	Text column. DEX or launch venue id returned by GeckoTerminal, such as pump-fun or raydium.
network_id	object	string	Text column. Blockchain network identifier for the pool. This dataset is Solana-only.
primary_feed	object	string	Text column. Primary collection feed that surfaced the pool first in this build, such as new_pools or trending_pools.
appears_in_new_pools_feed	bool	boolean	True/false column. Boolean flag indicating the pool appeared in the GeckoTerminal new pools feed during collection.
appears_in_trending_pools_feed	bool	boolean	True/false column. Boolean flag indicating the pool appeared in the GeckoTerminal trending pools feed during collection.
new_pools_rank	float64	float	Decimal numeric column. One-based rank position from the new pools feed when the pool appeared there.
trending_pools_rank	float64	float	Decimal numeric column. One-based rank position from the trending pools feed when the pool appeared there.
pool_created_at	datetime64[ns, UTC]	datetime	Date or timestamp column. Timestamp when the pool was created according to GeckoTerminal.
pool_age_hours	float64	float	Decimal numeric column. Approximate age of the pool in hours at collection time.
pool_age_days	float64	float	Decimal numeric column. Approximate age of the pool in days at collection time.
base_token_price_usd	float64	float	Decimal numeric column. Current base-token price in USD.
quote_token_price_usd	float64	float	Decimal numeric column. Current quote-token price in USD.
base_token_price_native_currency	float64	float	Decimal numeric column. Current base-token price in the network native asset.
quote_token_price_native_currency	float64	float	Decimal numeric column. Current quote-token price in the network native asset.
base_token_price_quote_token	float64	float	Decimal numeric column. Current base-token price denominated in the quote token.
quote_token_price_base_token	float64	float	Decimal numeric column. Current quote-token price denominated in the base token.
fdv_usd	float64	float	Decimal numeric column. Fully diluted valuation in USD returned by GeckoTerminal when available.
market_cap_usd	float64	float	Decimal numeric column. Current market capitalization in USD when GeckoTerminal exposes it for the base token.
reserve_in_usd	float64	float	Decimal numeric column. Current pool reserve or liquidity amount in USD.
has_market_cap	bool	boolean	True/false column. Boolean flag indicating GeckoTerminal exposed market_cap_usd for the pool.
fdv_to_liquidity_ratio	float64	float	Decimal numeric column. Fully diluted valuation divided by reserve_in_usd when both values are present.
market_cap_to_liquidity_ratio	float64	float	Decimal numeric column. Market capitalization divided by reserve_in_usd when both values are present.
price_change_pct_m5	float64	float	Decimal numeric column. Base-token price change percentage over the trailing five-minute window.
price_change_pct_m15	float64	float	Decimal numeric column. Base-token price change percentage over the trailing fifteen-minute window.
price_change_pct_m30	float64	float	Decimal numeric column. Base-token price change percentage over the trailing thirty-minute window.
price_change_pct_h1	float64	float	Decimal numeric column. Base-token price change percentage over the trailing one-hour window.
price_change_pct_h6	float64	float	Decimal numeric column. Base-token price change percentage over the trailing six-hour window.
price_change_pct_h24	float64	float	Decimal numeric column. Base-token price change percentage over the trailing twenty-four-hour window.
txns_buys_m5	int64	integer	Whole-number numeric column. Buy transaction count in the trailing five-minute window.
txns_sells_m5	int64	integer	Whole-number numeric column. Sell transaction count in the trailing five-minute window.
txns_buys_h1	int64	integer	Whole-number numeric column. Buy transaction count in the trailing one-hour window.
txns_sells_h1	int64	integer	Whole-number numeric column. Sell transaction count in the trailing one-hour window.
txns_buys_h24	int64	integer	Whole-number numeric column. Buy transaction count in the trailing twenty-four-hour window.
txns_sells_h24	int64	integer	Whole-number numeric column. Sell transaction count in the trailing twenty-four-hour window.
unique_traders_m5	float64	float	Decimal numeric column. Combined buyer and seller wallet count in the trailing five-minute window.
unique_traders_h1	int64	integer	Whole-number numeric column. Combined buyer and seller wallet count in the trailing one-hour window.
unique_traders_h24	int64	integer	Whole-number numeric column. Combined buyer and seller wallet count in the trailing twenty-four-hour window.
volume_usd_m5	float64	float	Decimal numeric column. Trading volume in USD over the trailing five-minute window.
volume_usd_h1	float64	float	Decimal numeric column. Trading volume in USD over the trailing one-hour window.
volume_usd_h24	float64	float	Decimal numeric column. Trading volume in USD over the trailing twenty-four-hour window.
buy_sell_ratio_h1	float64	float	Decimal numeric column. Buy transactions divided by sell transactions in the one-hour window.
buy_sell_ratio_h24	float64	float	Decimal numeric column. Buy transactions divided by sell transactions in the twenty-four-hour window.
volume_to_liquidity_h1	float64	float	Decimal numeric column. One-hour trading volume divided by reserve_in_usd.
volume_to_liquidity_h24	float64	float	Decimal numeric column. Twenty-four-hour trading volume divided by reserve_in_usd.
momentum_score	float64	float	Decimal numeric column. Derived score combining short-window price acceleration and transaction activity.
liquidity_score	float64	float	Decimal numeric column. Derived liquidity score based on reserve size and volume support.
launch_conviction_score	float64	float	Decimal numeric column. Derived trading-research score that blends liquidity, momentum, activity, and trending-feed presence.
paired_with_major_quote	bool	boolean	True/false column. Boolean flag indicating the quote token appears to be SOL, USDC, or USDT.
source_api_pool_url	object	string	Text column. Pool-detail API URL for the row.
source_collection_url	object	string	Text column. Primary collection feed URL associated with the row.
source_domain	object	string	Text column. Source platform domain.
last_collected_at	datetime64[ns, UTC]	datetime	Date or timestamp column. UTC timestamp when the row was collected for this dataset build.

Intended Use

This dataset is intended for research, experimentation, analysis, and model prototyping.

Loading the Dataset


import os
from datasets import load_dataset

HUGGINGFACE_API_KEY_KARMANE = os.environ.get("HUGGINGFACE_API_KEY_KARMANE")

dataset = load_dataset(
    "Karmane/solana-new-pools-liquidity-and-momentum-signals",
    token=HUGGINGFACE_API_KEY_KARMANE,
)

print(dataset)
print(dataset[list(dataset.keys())[0]][0])

# getting the DataFrame itself
# df = dataset[list(dataset.keys())[0]].to_pandas()

Karmane. (2025). Solana New Pools Liquidity and Momentum Signals. Hugging Face. https://huggingface.co/datasets/Karmane/solana-new-pools-liquidity-and-momentum-signals

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