Package for Santiment API access with python

Project description

sanpy

Santiment API python client.

sanpy

Installation

pip install sanpy

Upgrade to latest version

pip install --upgrade sanpy

Install extra packages

There are few scripts under extras directory. To install their dependencies use:

pip install sanpy[extras]

Restricted metrics

In order to access real-time data or historical data for some of the metrics, you'll need to set the API key, generated from an account with a paid API plan.

All restricted metrics are free for "santiment" token.

Configuration

Optionally you can provide an api key which gives access to some restricted metrics:

import san
san.ApiConfig.api_key = 'api-key-provided-by-sanbase'

To obtain an api key you should log in to sanbase and go to the account page - https://app.santiment.net/account. There is an API Keys section and a Generate new api key button.

If the account used for generating the api key has enough SAN tokens, the api key will give you access to the data that requires SAN token staking. The api key can only be used to fetch data and not to execute graphql mutations.

Retrieving data from the API

The data is fetched by providing a string in the format query/slug and additional parameters.

query: Available queries can be found in section: Available metrics
slug: A list of projects with their slugs, names, etc. can be fetched like this:

import san
san.get("projects/all")

                name             slug ticker   totalSupply
0             0chain           0chain    ZCN     400000000
1                 0x               0x    ZRX    1000000000
2          0xBitcoin            0xbtc  0xBTC      20999984
...

Parameters:

from_date, to_date - A date or datetime in iso8601 format specifying the start and end datetime for the returned data or the string for ex: 2018-06-01, or a string, representing the relative datetime utc_now-<interval>
interval - The interval of the returned data - an integer followed by one of: s, m, h, d or w

Default values for parameters:

from_date: datetime.now() - 365 days
to_date: datetime.now()
interval: '1d'

The returned value for time-series data is in pandas DataFrame format indexed by datetime.

Fetch single metric

import san

san.get(
    "daily_active_addresses/santiment",
    from_date="2018-06-01",
    to_date="2018-06-05",
    interval="1d"
)

san.get(
    "prices/santiment",
    from_date="2018-06-01",
    to_date="2018-06-05",
    interval="1d"
)

Using the defaults params (last 1 year of data with 1 day interval):

san.get("daily_active_addresses/santiment")
san.get("prices/santiment")

Fetching metadata for a metric

Fetching the metadata for an on-chain metric.

san.metadata(
    "nvt",
    arr=['availableSlugs', 'defaultAggregation', 'humanReadableName', 'isAccessible', 'isRestricted', 'restrictedFrom', 'restrictedTo']
)

Example result:

{'availableSlugs': ['0chain', '0x', '0xbtc', '0xcert', '1sg', ...],
'defaultAggregation': 'AVG', 'humanReadableName': 'NVT (Using Circulation)', 'isAccessible': True, 'isRestricted': True, 'restrictedFrom': '2020-03-21T08:44:14Z', 'restrictedTo': '2020-06-17T08:44:14Z'}

availableSlugs - A list of all slugs available for this metric.
defaultAggregation - If big interval are queried, all values that fall into this interval will be aggregated with this aggregation.
humanReadableName - A name of the metric suitable for showing to users.
isAccessible - True if the metric is accessible. If API key is configured, c hecks the API plan subscriptions. False if the metric is not accessbile. For example circulation_1d requires PRO plan subscription in order to be accessbile at all.
isRestricted - True if time restrictions apply to the metric and your current plan (Free if no API key is configured). Check restrictedFrom and restrictedTo.
restrictedFrom - The first datetime available of that metric for your current plan.
restrictedTo - The last datetime available of that metric and your current plan.

Batching multiple queries

from san import Batch

batch = Batch()

batch.get(
    "daily_active_addresses/santiment",
    from_date="2018-06-01",
    to_date="2018-06-05",
    interval="1d"
)

batch.get(
    "transaction_volume/santiment",
    from_date="2018-06-01",
    to_date="2018-06-05",
    interval="1d"
)

[daa, trx_volume] = batch.execute()

Making a custom graphql query to the API

from san.graphql import execute_gql
import pandas as pd

res = execute_gql("""{
  projectBySlug(slug: "santiment") {
    slug
    name
    ticker
    infrastructure
    mainContractAddress
    twitterLink
  }
}""")

pd.DataFrame(res['projectBySlug'], index=[0])

  infrastructure                         mainContractAddress       name       slug ticker                        twitterLink
0            ETH  0x7c5a0ce9267ed19b22f8cae653f198e3e8daf098  Santiment  santiment    SAN  https://twitter.com/santimentfeed

Rate Limit Tools

There are two functions, which can help you in handling the rate limits:

is_rate_limit_exception - Returns whether the exception caught is because of rate limitation
rate_limit_time_left - Returns the time left before the rate limit expires
api_calls_made - Returns the API calls for each day in which it was used
api_calls_remaining - Returns the API calls remaining for the month, hour and minute

Example:

import time
import san

try:
  san.get(
    "price_usd/santiment",
    from_date="utc_now-30d",
    to_date="utc_now",
    interval="1d"
  )
except Exception as e:
  if san.is_rate_limit_exception(e):
    rate_limit_seconds = san.rate_limit_time_left(e)
    print(f"Will sleep for {rate_limit_seconds}")
    time.sleep(rate_limit_seconds)

...

calls_by_day = san.api_calls_made()
calls_remaining = san.api_calls_remaining()

Available metrics

Getting all of the metrics as a list is done using the following code:

san.available_metrics()

Available Metrics for Slug

Getting all of the metrics for a given slug is achieved with the following code:

san.available_metrics_for_slug('santiment')

Metric Complexity

Fetch the complexity of a metric. The complexity depends on the from/to/interval parameters, as well as the metric and the subscription plan. A request might have a maximum complexity of 20000. If a request has a higher complexity there are a few ways to solve the issue:

Break down the request into multiple requests with smaller from-to ranges.
Upgrade to a higher subscription plan.

san.metric_complexity(
    metric='price_usd',
    from_date='2020-01-01',
    to_date='2020-02-20',
    interval='1d'
)

Include Incomplete Data Flag

Daily metrics have one value per day. For the current day, the latest computed value will not include a full day of data. For example, computing daily_active_addresses at 08:00 includes data for one third of the day. To reduce confusion, the current day value for metrics that have this behaviour is excluded. To force fetching the current day value, the includeIncompleteData flag must be used.

san.get(
  "daily_active_addresses/bitcoin",
  from_date="utc_now-3d",
  to_date="utc_now",
  interval="1d",
  include_incomplete_data=True
)

Available Since

Fetch the first datetime for which a metric is available for a given slug.

san.available_metric_for_slug_since(metric='daily_active_addresses', slug='santiment')

Below are described the available metrics and are given examples for fetching them.

Full list of metrics for a single project

NOTE: When a new metric is added to the API, san.available_metrics() will automatically pick it up and it will be accessible with sanpy, but it might take some time to be added to this documentation. The list below might not be full at times.

The suffixes _<number>y and _<number>d means that the metric is calculated only by taken into account the tokens and coins that have moved in the past number of years or days.

All these metrics are returned as a Pandas dataframe with two columns - datetime and float value.

All metrics that do not follow the same format are explicitly listed after that.

Example usage:

san.get(
  "price_usd/santiment",
  from_date="2020-06-01",
  to_date="2021-06-05",
  interval="1d",
  transform={"type": "moving_average", "moving_average_base": 100},
  aggregation="LAST"
)

Where the parameters, that are not mentioned, are optional:

transform - Apply a transformation on the data. The supported transformations are:

"moving_average" - Replace every value V_i with the average of the last "moving_average_base" values.
"consecutive_differences" - Replace every value V_i with the value V_i - V_i-1 where i is the position in the list. Automatically fetches some extra data needed in order to compute the first value.
"percent_change" - Replace every value V_i with the percent change of V_i-1 and V_i ( (V_i / V_i-1 - 1) * 100) where i is the position in the list. Automatically fetches some extra data needed in order to compute the first value.

aggregation - the aggregation which is used for the query results.

Holder Metrics

amount_in_top_holders
amount_in_exchange_top_holders
amount_in_non_exchange_top_holders
holders_distribution_combined_balance_100k_to_1M
holders_distribution_0.1_to_1
holders_distribution_0_to_0.001
holders_distribution_1_to_10
holders_distribution_1k_to_10k
holders_distribution_combined_balance_0.01_to_0.1
holders_distribution_combined_balance_0.1_to_1
holders_distribution_combined_balance_1k_to_10k
holders_distribution_100_to_1k
holders_distribution_combined_balance_10k_to_100k
holders_distribution_10_to_100
holders_distribution_10k_to_100k
holders_distribution_total
holders_distribution_combined_balance_1M_to_10M
holders_distribution_combined_balance_10_to_100
holders_distribution_1M_to_10M
holders_distribution_0.01_to_0.1
holders_distribution_0.001_to_0.01
holders_distribution_combined_balance_1_to_10
holders_distribution_combined_balance_100_to_1k
holders_distribution_combined_balance_0_to_0.001
holders_distribution_combined_balance_0.001_to_0.01
holders_distribution_combined_balance_10M_to_inf
holders_distribution_100k_to_1M
holders_distribution_10M_to_inf
percent_of_total_supply_on_exchanges
supply_on_exchanges
supply_outside_exchanges

Social Metrics

twitter_followers
social_dominance_telegram
social_dominance_reddit
social_dominance_total
social_volume_telegram
social_volume_reddit
social_volume_twitter
social_volume_bitcointalk
social_volume_total
community_messages_count_telegram
community_messages_count_total
sentiment_positive_total
sentiment_positive_telegram
sentiment_positive_reddit
sentiment_positive_twitter
sentiment_positive_bitcointalk
sentiment_negative_total
sentiment_negative_telegram
sentiment_negative_reddit
sentiment_negative_twitter
sentiment_negative_bitcointalk
sentiment_balance_total
sentiment_balance_telegram
sentiment_balance_reddit
sentiment_balance_twitter
sentiment_balance_bitcointalk
sentiment_volume_consumed_total
sentiment_volume_consumed_telegram
sentiment_volume_consumed_reddit
sentiment_volume_consumed_twitter
sentiment_volume_consumed_bitcointalk

Price Metrics

price_usd
price_btc
price_eth
volume_usd
marketcap_usd
daily_avg_marketcap_usd
daily_avg_price_usd
daily_closing_marketcap_usd
daily_closing_price_usd
daily_high_price_usd
daily_low_price_usd
daily_opening_price_usd
daily_trading_volume_usd
volume_usd_change_1d
volume_usd_change_30d
volume_usd_change_7d
price_usd_change_1d
price_usd_change_30d
price_usd_change_7d

Development Metrics

dev_activity
dev_activity_change_30d
dev_activity_contributors_count
github_activity
github_activity_contributors_count

Derivatives

bitmex_perpetual_basis
bitmex_perpetual_funding_rate
bitmex_perpetual_open_interest
bitmex_perpetual_open_value

MakerDAO Metrics

dai_created
dai_repaid
mcd_collat_ratio
mcd_collat_ratio_sai
mcd_collat_ratio_weth
mcd_dsr
mcd_erc20_supply
mcd_locked_token
mcd_stability_fee
mcd_supply
scd_collat_ratio
scd_locked_token

On-Chain Metrics

active_addresses_24h
active_addresses_24h_change_1d
active_addresses_24h_change_30d
active_addresses_24h_change_7d
active_deposits
active_withdrawals
age_destroyed
circulation
circulation_10y
circulation_180d
circulation_1d
circulation_2y
circulation_30d
circulation_365d
circulation_3y
circulation_5y
circulation_60d
circulation_7d
circulation_90d
daily_active_addresses
deposit_transactions
exchange_balance
exchange_inflow
exchange_outflow
mean_age
mean_dollar_invested_age
mean_realized_price_usd
mean_realized_price_usd_10y
mean_realized_price_usd_180d
mean_realized_price_usd_1d
mean_realized_price_usd_2y
mean_realized_price_usd_30d
mean_realized_price_usd_365d
mean_realized_price_usd_3y
mean_realized_price_usd_5y
mean_realized_price_usd_60d
mean_realized_price_usd_7d
mean_realized_price_usd_90d
mvrv_long_short_diff_usd
mvrv_usd
mvrv_usd_10y
mvrv_usd_180d
mvrv_usd_1d
mvrv_usd_2y
mvrv_usd_30d
mvrv_usd_365d
mvrv_usd_3y
mvrv_usd_5y
mvrv_usd_60d
mvrv_usd_7d
mvrv_usd_90d
mvrv_usd_intraday
mvrv_usd_intraday_10y
mvrv_usd_intraday_180d
mvrv_usd_intraday_1d
mvrv_usd_intraday_2y
mvrv_usd_intraday_30d
mvrv_usd_intraday_365d
mvrv_usd_intraday_3y
mvrv_usd_intraday_5y
mvrv_usd_intraday_60d
mvrv_usd_intraday_7d
mvrv_usd_intraday_90d
network_growth
nvt
nvt_transaction_volume
realized_value_usd
realized_value_usd_10y
realized_value_usd_180d
realized_value_usd_1d
realized_value_usd_2y
realized_value_usd_30d
realized_value_usd_365d
realized_value_usd_3y
realized_value_usd_5y
realized_value_usd_60d
realized_value_usd_7d
realized_value_usd_90d
stock_to_flow
transaction_volume
velocity
withdrawal_transactions

Fetching lists of projects

All Projects

Returns a DataFrame with all the projects available in the Santiment API. Not all metrics will be available for each of the projects.

slug is the unique identifier of a project, used in the metrics fetching.

san.get("projects/all")

Example result:

                 name             slug ticker   totalSupply
0              0chain           0chain    ZCN     400000000
1                  0x               0x    ZRX    1000000000
2           0xBitcoin            0xbtc  0xBTC      20999984
3     0xcert Protocol           0xcert    ZXC     500000000
4              1World           1world    1WO      37219453
5        AB-Chain RTB     ab-chain-rtb    RTB      27857813
6             Abulaba          abulaba    AAA     397000000
7                 AC3              ac3    AC3    80235326.0
...

ERC20 Projects

Returns a DataFrame with all the ERC20 projects available in the Santiment API. Not all metrics will be available for all the projects. The slug is a unique identifier which can be used to retrieve most of the metrics.

san.get("projects/erc20")

Example result:

                      name                   slug ticker   totalSupply
0                   0chain                 0chain    ZCN     400000000
1                       0x                     0x    ZRX    1000000000
2                0xBitcoin                  0xbtc  0xBTC      20999984
3          0xcert Protocol                 0xcert    ZXC     500000000
4                   1World                 1world    1WO      37219453
5             AB-Chain RTB           ab-chain-rtb    RTB      27857813
6                  Abulaba                abulaba    AAA     397000000
7                   adbank                 adbank    ADB    1000000000
...

Other Price metrics

Open, High, Close, Low Prices, Volume, Marketcap

Note: this query cannot be batched!

san.get(
    "ohlcv/santiment",
    from_date="2018-06-01",
    to_date="2018-06-05",
    interval="1d"
)

Example result:

datetime                        openPriceUsd  closePriceUsd  highPriceUsd  lowPriceUsd   volume  marketcap
2018-06-01 00:00:00+00:00       1.24380        1.27668       1.26599       1.19099       852857  7.736268e+07
2018-06-02 00:00:00+00:00       1.26136        1.30779       1.27612       1.20958      1242520  7.864724e+07
2018-06-03 00:00:00+00:00       1.28270        1.28357       1.24625       1.21872      1032910  7.844339e+07
2018-06-04 00:00:00+00:00       1.23276        1.24910       1.18528       1.18010       617451  7.604326e+07

Gas Used

Returns used Gas by a blockchain. When you send tokens, interact with a contract or do anything else on the blockchain, you must pay for that computation. That payment is calculated in Gas. Currently only ETH is supported.

Premium metric

san.get(
    "gas_used/ethereum",
    from_date="2019-06-01",
    to_date="2019-06-05",
    interval="1d"
)

Example result:

datetime                       gasUsed
2019-06-01 00:00:00+00:00  47405557702
2019-06-02 00:00:00+00:00  44769162038
2019-06-03 00:00:00+00:00  46415901420
2019-06-04 00:00:00+00:00  46907686393
2019-06-05 00:00:00+00:00  45925073341

Miners Balance

Returns miner balances over time. Currently only ETH is supported.

Premium metric

san.get(
    "miners_balance/ethereum",
    from_date="2019-06-01",
    to_date="2019-06-05",
    interval="1d"
)

Example result:

datetime                        balance
2019-06-01 00:00:00+00:00  1.529488e+06
2019-06-02 00:00:00+00:00  1.533494e+06
2019-06-03 00:00:00+00:00  1.527438e+06
2019-06-04 00:00:00+00:00  1.525666e+06
2019-06-05 00:00:00+00:00  1.527563e+06

Mining Pools Distribution

Returns distribution of miners between mining pools. What part of the miners are using top3, top10 and all the other pools. Currently only ETH is supported.

Premium metric

san.get(
    "mining_pools_distribution/ethereum",
    from_date="2019-06-01",
    to_date="2019-06-05",
    interval="1d"
)

Example result:

datetime                      other     top10      top3
2019-06-01 00:00:00+00:00  0.129237  0.249906  0.620857
2019-06-02 00:00:00+00:00  0.127432  0.251903  0.620666
2019-06-03 00:00:00+00:00  0.122058  0.249603  0.628339
2019-06-04 00:00:00+00:00  0.127726  0.254982  0.617293
2019-06-05 00:00:00+00:00  0.120436  0.265842  0.613722

Historical Balance

Historical balance for erc20 token or eth address. Returns the historical balance for a given address in the given interval.

san.get(
    "historical_balance/santiment",
    address="0x1f3df0b8390bb8e9e322972c5e75583e87608ec2",
    from_date="2019-04-18",
    to_date="2019-04-23",
    interval="1d"
)

Example result:

datetime                     balance
2019-04-18 00:00:00+00:00  382338.33
2019-04-19 00:00:00+00:00  382338.33
2019-04-20 00:00:00+00:00  382338.33
2019-04-21 00:00:00+00:00  215664.33
2019-04-22 00:00:00+00:00  215664.33

Price Volume Difference

Fetch the price-volume difference technical indicator for a given slug, display currency and time period. This indicator measures the difference in trend between price and volume, specifically when price goes up as volume goes down.

san.get(
    "price_volume_difference/santiment",
    from_date="2019-04-18",
    to_date="2019-04-23",
    interval="1d",
    currency="USD"
)

Example result:

datetime                   priceChange  priceVolumeDiff  volumeChange
2019-04-18 00:00:00+00:00     0.017779         0.013606 -39908.007476
2019-04-19 00:00:00+00:00     0.012587         0.007332 -31195.568878
2019-04-20 00:00:00+00:00     0.009062         0.004169 -24550.100411
2019-04-21 00:00:00+00:00     0.002573         0.001035 -19307.845911
2019-04-22 00:00:00+00:00     0.001527         0.000703 -20317.934666

Ethereum Top Transactions

Top ETH transactions for project's team wallets.

Available transaction types:

san.get(
    "eth_top_transactions/santiment",
    from_date="2019-04-18",
    to_date="2019-04-30",
    limit=5,
    transaction_type="ALL"
)

Example result:

The result is shortened for convenience

datetime                           fromAddress  fromAddressInExchange           toAddress  toAddressInExchange              trxHash      trxValue
2019-04-29 21:33:31+00:00  0xe76fe52a251c8f...                  False  0x45d6275d9496b...                False  0x776cd57382456a...        100.00
2019-04-29 21:21:18+00:00  0xe76fe52a251c8f...                  False  0x468bdccdc334f...                False  0x848414fb5c382f...         40.95
2019-04-19 14:14:52+00:00  0x1f3df0b8390bb8...                  False  0xd69bc0585e05e...                False  0x590512e1f1fbcf...         19.48
2019-04-19 14:09:58+00:00  0x1f3df0b8390bb8...                  False  0x723fb5c14eaff...                False  0x78e0720b9e72d1...         15.15

Ethereum Spent Over Time

ETH spent for each interval from the project's team wallet and time period

san.get(
    "eth_spent_over_time/santiment",
    from_date="2019-04-18",
    to_date="2019-04-23",
    interval="1d"
)

Example result:

datetime                    ethSpent
2019-04-18 00:00:00+00:00   0.000000
2019-04-19 00:00:00+00:00  34.630284
2019-04-20 00:00:00+00:00   0.000000
2019-04-21 00:00:00+00:00   0.000158
2019-04-22 00:00:00+00:00   0.000000

Token Top Transactions

Top transactions for the token of a given project

san.get(
    "token_top_transactions/santiment",
    from_date="2019-04-18",
    to_date="2019-04-30",
    limit=5
)

Example result:

The result is shortened for convenience

datetime                           fromAddress  fromAddressInExchange           toAddress  toAddressInExchange              trxHash      trxValue
2019-04-21 13:51:59+00:00  0x1f3df0b8390bb8...                  False  0x5eaae5e949952...                False  0xdbced935b09dd0...  166674.00000
2019-04-28 07:43:38+00:00  0x0a920bfdf7f977...                  False  0x868074aab18ea...                False  0x5f2214d34bcdc3...   33181.82279
2019-04-28 07:53:32+00:00  0x868074aab18ea3...                  False  0x876eabf441b2e...                 True  0x90bd286da38a2b...   33181.82279
2019-04-26 14:38:45+00:00  0x876eabf441b2ee...                   True  0x76af586d041d6...                False  0xe45b86f415e930...   28999.64023
2019-04-30 15:17:28+00:00  0x876eabf441b2ee...                   True  0x1f4a90043cf2d...                False  0xc85892b9ef8c64...   20544.42975

Top Transfers

Top transfers for the token of a given project, address and transaction_type arguments can be added as well, in the form of a key-value pair. The transaction_type parameter can have one of these three values: ALL, OUT, IN.

san.get(
    "top_transfers/santiment",
    from_date="utc_now-30d",
    to_date="utc_now",
)

The result is shortened for convenience

Example result:

                          fromAddress   toAddress     trxHash       trxValue
datetime                                                                                                                                                                                                                          
2021-06-17 00:16:26+00:00  0xa48df...  0x876ea...  0x62a56...  136114.069733
2021-06-17 00:10:05+00:00  0xbd3c2...  0x876ea...  0x732a5...  117339.779890
2021-06-19 21:36:03+00:00  0x59646...  0x0d45b...  0x5de31...  112336.882707
...

san.get(
    "top_transfers/santiment",
    address="0x26e068650ae54b6c1b149e1b926634b07e137b9f",
    transaction_type="ALL",
    from_date="utc_now-30d",
    to_date="utc_now",
)

Example result:

                          fromAddress  toAddress    trxHash   trxValue
datetime                                                                                                                                                                                        
2021-06-13 09:14:01+00:00  0x26e06...  0xfd3d...  0x4af6...  69854.528
2021-06-13 09:13:01+00:00  0x876ea...  0x26e0...  0x18c1...  69854.528
2021-06-14 08:54:52+00:00  0x876ea...  0x26e0...  0xdceb...  59920.591
...

Emerging Trends

Emerging trends for a given period of time

san.get(
    "emerging_trends",
    from_date="2019-07-01",
    to_date="2019-07-02",
    interval="1d",
    size=5
)

Example result:

datetime                        score    word
2019-07-01 00:00:00+00:00  375.160034    lnbc
2019-07-01 00:00:00+00:00  355.323281    dent
2019-07-01 00:00:00+00:00  268.653820    link
2019-07-01 00:00:00+00:00  231.721809  shorts
2019-07-01 00:00:00+00:00  206.812798     btt
2019-07-02 00:00:00+00:00  209.343752  bounce
2019-07-02 00:00:00+00:00  135.412811    vidt
2019-07-02 00:00:00+00:00  116.842801     bat
2019-07-02 00:00:00+00:00   98.517600  bottom
2019-07-02 00:00:00+00:00   89.309975   haiku

Top Social Gainers Losers

Top social gainers/losers returns the social volume changes for crypto projects.

san.get(
    "top_social_gainers_losers",
    from_date="2019-07-18",
    to_date="2019-07-30",
    size=5,
    time_window="2d",
    status="ALL"
)

Example result:

The result is shortened for convenience

datetime                              slug     change    status
2019-07-28 01:00:00+00:00     libra-credit  21.000000    GAINER
2019-07-28 01:00:00+00:00             aeon  -1.000000     LOSER
2019-07-28 01:00:00+00:00    thunder-token   5.000000  NEWCOMER
2019-07-28 02:00:00+00:00     libra-credit  43.000000    GAINER
...                                    ...        ...       ...
2019-07-30 07:00:00+00:00            storj  12.000000  NEWCOMER
2019-07-30 11:00:00+00:00            storj  21.000000    GAINER
2019-07-30 11:00:00+00:00            aergo  -1.000000     LOSER
2019-07-30 11:00:00+00:00            litex   8.000000  NEWCOMER

Extras

Take a look at the examples folder.

Development

It is recommended to use pipenv for managing your local environment.

Setup project:

pipenv install

Install main dependencies:

pipenv run pip install -e .

Install extra dependencies:

pipenv run pip install -e '.[extras]'

Running tests

python setup.py test

Running integration tests

python setup.py nosetests -a integration

Project details

Release history Release notifications | RSS feed

0.12.0

Mar 21, 2024

0.11.8

Dec 15, 2023

0.11.6

Mar 29, 2023

0.11.5

Feb 1, 2023

0.11.4

Jan 28, 2023

0.11.3

Nov 4, 2022

0.11.2

Oct 27, 2022

0.11.1

Oct 27, 2022

0.11.0

Oct 27, 2022

0.10.2

Sep 29, 2022

This version

0.10.1

Aug 30, 2022

0.10.0

Jun 15, 2022

0.9.1

Jan 13, 2022

0.8.12

Nov 26, 2021

0.8.11

Aug 24, 2021

0.8.10

Aug 24, 2021

0.8.9

Jul 15, 2021

0.8.8

Jul 7, 2021

0.8.7

May 7, 2021

0.8.6

Nov 23, 2020

0.8.5

Aug 24, 2020

0.8.4

Jul 24, 2020

0.8.3

Jul 9, 2020

0.8.2

Jul 2, 2020

0.8.0

Jun 25, 2020

0.7.19

Jun 18, 2020

0.7.18

Mar 25, 2020

0.7.16

Feb 20, 2020

0.7.15

Feb 4, 2020

0.7.14

Jan 27, 2020

0.7.13

Jan 21, 2020

0.7.11

Jan 7, 2020

0.7.10

Dec 19, 2019

0.7.9

Dec 10, 2019

0.7.8

Nov 29, 2019

0.7.5

Nov 4, 2019

0.7.4

Nov 1, 2019

0.7.1

Oct 7, 2019

0.7.0

Sep 18, 2019

0.6.1

Jul 22, 2019

0.6.0

Jul 22, 2019

0.5.3

Jul 9, 2019

0.5.2

Jun 28, 2019

0.5.1

Jun 20, 2019

0.5.0

May 7, 2019

0.4.2

May 2, 2019

0.4.1

Apr 8, 2019

0.3.4

Feb 11, 2019

0.3.3

Feb 7, 2019

0.3.2

Jan 25, 2019

0.3.1

Jan 14, 2019

0.3.0

Dec 20, 2018

0.2.1

Dec 11, 2018

0.2.0

Dec 4, 2018

0.1.6

Nov 13, 2018

0.1.5

Oct 26, 2018

0.1.4

Oct 25, 2018

0.1.2

Oct 19, 2018

0.1.1

Oct 18, 2018

0.1.0

Oct 11, 2018

0.0.20

Oct 10, 2018

0.0.19

Oct 9, 2018

0.0.18

Sep 21, 2018

0.0.17

Sep 20, 2018

0.0.16

Sep 19, 2018

0.0.13

Sep 11, 2018

0.0.12

Aug 15, 2018

0.0.9

Aug 15, 2018

0.0.6

Jul 6, 2018

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sanpy 0.10.1

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sanpy

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