Package: sanpy
sanpyPython client for cryptocurrency data fromSantiment API.
This library provides utilities for accessing the GraphQL Santiment API endpoint
and convert the result to pandas dataframe.More documentation regarding the API and definitions of metrics can be found onSantiment AcademyTable of contentssanpyTable of contentsInstallationUpgrade to latest versionInstall extra packagesRestricted metricsConfigurationRead the API key from the environmentManually configure an API keyHow to obtain an API keyGetting the dataUsing the provided functionsExecute an arbitrary GraphQL requestExecute SQL queries and get the resultAvailable metricsAvailable Metrics for SlugFetch timeseries metricFetching metadata for a metricBatching multiple queriesRate Limit ToolsMetric ComplexityInclude Incomplete Data FlagMetric/Asset pair available cinceTransform the resultAvailable projectsNon-standard metricsOther Price metricsMarketcap, Price USD, Price BTC and Trading VolumeOpen, High, Close, Low Prices, Volume, MarketcapHistorical BalanceEthereum Top TransactionsEthereum Spent Over TimeToken Top TransactionsTop TransfersEmerging TrendsTop Social Gainers LosersExtrasDevelopmentRunning testsRunning integration testsInstallationTo install the latestsanpy from PyPI:pipinstallsanpyUpgrade to latest versionpipinstall--upgradesanpyInstall extra packagesThere are few scripts underextrasdirectory related to backtesting and event studies. To install their dependencies use:pipinstallsanpy[extras]Restricted metricsIn order to access real-time data or historical data for some of the metrics,
you'll need to set theAPI key, generated from an account with
a paid API plan.ConfigurationYou can provide an API key which gives access to the restricted metrics in two different ways:Read the API key from the environmentDuring loading of thesanmodule, if theSANPY_APIKEYexists, its content
is read and set as the API key.exportSANPY_APIKEY="my_apikey"importsan>>>san.ApiConfig.api_key'my_apikey'Manually configure an API keyimportsansan.ApiConfig.api_key="my_apikey"How to obtain an API keyTo obtain an API key you shouldlog in to sanbaseand go to theAccountpage -https://app.santiment.net/account.
There is anAPI Keyssection and aGenerate new api keybutton.Getting the dataUsing the provided functionsThe library provides thegetandget_manyfunctions that are used to fetch data.getis used to fetch timeseries data for a single metric/asset pair.get_manyis used to fetch timeseries data for a single metric, but many assets. This is counted as 1 API call.The first argument to the functions is the metric name.The rest of the parameters are::slug- (forget) The project identificator, as seen inthe Available projects sectionslugs- (forget_many) A list of projects' identificators, as seen inthe Available projects sectionselector- Allow for more flexible selection of the target. Some metrics are
computed on blockchain addresses, for others you can provide a list of slugs,
labels, amount of top holders. etc.from_date- A date or datetime in ISO8601 format specifying the start of the queried period. Defaults todatetime.utcnow() - 365 daysto_date- A date or datetime in ISO86091 format specifying the end of the queried period. Defaults todatetime.utcnow()interval- The interval between the data points in the timeseries. Defaults to'1d'It is represented in two different ways:a fixed range:  an integer followed by one of:s,m,h,dorwa function, providing some semantic or a dynamic range:toStartOfMonth,toStartOfDay,toStartOfWeek,toMonday..The returned result for time-series data is transformed intopandas DataFrameand is indexed bydatetime.
Forget, the value column is namedvalue.
Forget_many, there is one column per asset queried. The asset slugs are used for the column names.For backwards compatibility, fetching the metric by providing"metric/slug"as
the first instead of using a separate'slug'/'selector'continues to work,
but it is not the recommended approach.For non-metric related data like getting the list of available assets, the data
is fetched by providing a string in the formatquery/argumentand additional
parameters.The examples below contain some of the described scenarios.Fetch metric by providingmetricas first argument andslugas named parameter:importsansan.get("price_usd",slug="bitcoin",from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                   value
2022-01-01 00:00:00+00:00  47686.811509
2022-01-02 00:00:00+00:00  47345.220564
2022-01-03 00:00:00+00:00  46458.116959
2022-01-04 00:00:00+00:00  45928.661063
2022-01-05 00:00:00+00:00  43569.003348Fetch prices for multiple assets:importsansan.get_many("price_usd",slugs=["bitcoin","ethereum","tether"],from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                   bitcoin       ethereum     tether                                            
2022-01-01 00:00:00+00:00  47686.811509  3769.696916  1.000500
2022-01-02 00:00:00+00:00  47345.220564  3829.565045  1.000460
2022-01-03 00:00:00+00:00  46458.116959  3761.380274  1.000165
2022-01-04 00:00:00+00:00  45928.661063  3795.890130  1.000208
2022-01-05 00:00:00+00:00  43569.003348  3550.386882  1.000122Fetch development activity of a specific Github organization:importsansan.get("dev_activity",selector={"organization":"google"},from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                    value     
2022-01-01 00:00:00+00:00   176.0
2022-01-02 00:00:00+00:00   129.0
2022-01-03 00:00:00+00:00   562.0
2022-01-04 00:00:00+00:00  1381.0
2022-01-05 00:00:00+00:00  1334.0Fetch a metric for a contract address, not a slug:importsansan.get("contract_transactions_count",selector={"contractAddress":"0x00000000219ab540356cBB839Cbe05303d7705Fa"},from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                   value     
2022-01-01 00:00:00+00:00   90.0
2022-01-02 00:00:00+00:00  339.0
2022-01-03 00:00:00+00:00  486.0
2022-01-04 00:00:00+00:00  314.0
2022-01-05 00:00:00+00:00  328.0Fetch top holders metric and specify the number of top holders to be counted:importsansan.get("amount_in_top_holders",selector={"slug":"santiment","holdersCount":10},from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                   value
2022-01-01 00:00:00+00:00  7.391186e+07
2022-01-02 00:00:00+00:00  7.391438e+07
2022-01-03 00:00:00+00:00  7.391984e+07
2022-01-04 00:00:00+00:00  7.391984e+07
2022-01-05 00:00:00+00:00  7.391984e+07Fetch trade volume of a given DEX for a given slugimportsan# This requires Santiment API PRO apikey configuredsan.get("total_trade_volume_by_dex",selector={"slug":"ethereum","label":"decentralized_exchange","owner":"UniswapV2"},from_date="2022-01-01",to_date="2022-01-05",interval="1d")datetime                    value
2022-01-01 00:00:00+00:00   96882.176846
2022-01-02 00:00:00+00:00   85184.970249
2022-01-03 00:00:00+00:00  107489.846163
2022-01-04 00:00:00+00:00  105204.677503
2022-01-05 00:00:00+00:00  174178.848916Fetch metric by providingmetric/slugas first argument and noslugas named parameter:importsansan.get("daily_active_addresses/bitcoin",from_date="2018-06-01",to_date="2018-06-05",interval="1d")datetime                   value      
2018-06-01 00:00:00+00:00  692508.0
2018-06-02 00:00:00+00:00  521887.0
2018-06-03 00:00:00+00:00  531464.0
2018-06-04 00:00:00+00:00  702902.0
2018-06-05 00:00:00+00:00  655695.0Fetch non-timeseries data:importsansan.get("projects/all")name             slug ticker   totalSupply
0             0chain           0chain    ZCN     400000000
1                 0x               0x    ZRX    1000000000
2          0xBitcoin            0xbtc  0xBTC      20999984
...Execute an arbitrary GraphQL requestSome of the available queries in theSantiment APIdo not have a
dedicated sanpy function. Alternatively, if the returned format needs to be parsed differently, this approach
can be used, too. They can be fetched by providing the raw GraphQL query.Fetching data for many slugs at the same time. Note that this is also available assan.get_manyimportsanimportpandasaspdresult=san.graphql.execute_gql("""{getMetric(metric: "price_usd") {timeseriesDataPerSlug(selector: {slugs: ["ethereum", "bitcoin"]}from: "2022-05-05T00:00:00Z"to: "2022-05-08T00:00:00Z"interval: "1d") {datetimedata{valueslug}}}}""")data=result['getMetric']['timeseriesDataPerSlug']rows=[]fordatetime_pointindata:row={'datetime':datetime_point['datetime']}forslug_dataindatetime_point['data']:row[slug_data['slug']]=slug_data['value']rows.append(row)df=pd.DataFrame(rows)df.set_index('datetime',inplace=True)datetime              bitcoin       ethereum                
2022-05-05T00:00:00Z  36575.142133  2749.213042
2022-05-06T00:00:00Z  36040.922350  2694.979684
2022-05-07T00:00:00Z  35501.954144  2636.092958Fetching a specific set of fields for a project:importsanimportpandasaspdresult=san.graphql.execute_gql("""{projectBySlug(slug: "santiment") {slugnametickerinfrastructuremainContractAddresstwitterLink}}""")pd.DataFrame(result["projectBySlug"],index=[0])infrastructure                         mainContractAddress       name       slug ticker                        twitterLink
0            ETH  0x7c5a0ce9267ed19b22f8cae653f198e3e8daf098  Santiment  santiment    SAN  https://twitter.com/santimentfeedExecute SQL queries and get the resultOne of the Santiment products isSantiment Queries. It allows you to execute SQL queries on a database hosted by Santiment. Explore the documentation in order to get familiar with the available data and how to write SQL queries.In order to execute a query you need to provide your API key.Executing a query and getting the result as a pandas DataFrame:importsansan.execute_sql(query="SELECT * FROM daily_metrics_v2 LIMIT 5")metric_id  asset_id                    dt  value           computed_at
0         10      1369  2015-07-17T00:00:00Z    0.0  2020-10-21T08:48:42Z
1         10      1369  2015-07-18T00:00:00Z    0.0  2020-10-21T08:48:42Z
2         10      1369  2015-07-19T00:00:00Z    0.0  2020-10-21T08:48:42Z
3         10      1369  2015-07-20T00:00:00Z    0.0  2020-10-21T08:48:42Z
4         10      1369  2015-07-21T00:00:00Z    0.0  2020-10-21T08:48:42ZIn order to change the index to one of the columns, provide theset_indexparameter:importsansan.execute_sql(query="SELECT * FROM daily_metrics_v2 LIMIT 5",set_index="dt")dt                    metric_id  asset_id  value           computed_at
2015-07-17T00:00:00Z         10      1369    0.0  2020-10-21T08:48:42Z
2015-07-18T00:00:00Z         10      1369    0.0  2020-10-21T08:48:42Z
2015-07-19T00:00:00Z         10      1369    0.0  2020-10-21T08:48:42Z
2015-07-20T00:00:00Z         10      1369    0.0  2020-10-21T08:48:42Z
2015-07-21T00:00:00Z         10      1369    0.0  2020-10-21T08:48:42ZThe queries can be parametrized. In the query the parameters are named parameters,
surrounded by two curly brackets{{key}}. The parameters is a dictionary. The query
can be a multiline string:san.execute_sql(query="""SELECTget_metric_name(metric_id) AS metric,get_asset_name(asset_id) AS asset,dt,argMax(value, computed_at)FROM daily_metrics_v2WHEREasset_id = get_asset_id({{slug}}) ANDmetric_id = get_metric_id({{metric}}) ANDdt >= now() - INTERVAL {{last_n_days}} DAYGROUP BY dt, metric_id, asset_idORDER BY dt ASC""",parameters={'slug':'bitcoin','metric':'daily_active_addresses','last_n_days':7},set_index="dt")dt                                    metric    asset        value                     
2023-03-22T00:00:00Z  daily_active_addresses  bitcoin     941446.0
2023-03-23T00:00:00Z  daily_active_addresses  bitcoin     913215.0
2023-03-24T00:00:00Z  daily_active_addresses  bitcoin     884271.0
2023-03-25T00:00:00Z  daily_active_addresses  bitcoin     906851.0
2023-03-26T00:00:00Z  daily_active_addresses  bitcoin     835596.0
2023-03-27T00:00:00Z  daily_active_addresses  bitcoin    1052637.0
2023-03-28T00:00:00Z  daily_active_addresses  bitcoin     311566.0Available metricsGetting all of the metrics as a list is done using the following code:san.available_metrics()Available Metrics for SlugGetting all of the metrics for a given slug is achieved with the following code:san.available_metrics_for_slug("santiment")Fetch timeseries metricimportsansan.get("daily_active_addresses",slug="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",slug="santiment")san.get("price_usd",slug="santiment")Fetching metadata for a metricFetching 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-Trueif the metric is accessible. If API key is configured, c
hecks the API plan subscriptions.Falseif the metric is not accessible. For examplecirculation_1drequiresPROplan subscription in order to be accessible at
all.isRestricted-Trueif time restrictions apply to the metric and your
current plan (Freeif no API key is configured). CheckrestrictedFromandrestrictedTo.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 queriesMultiple queries can be executed in a batch to speed up the performance.There are two batch classes provided -BatchandAsyncBatch.Note: Batching improves the performance and the developer experience, but every
query put inside the batch is still counted as one separate API call.
To fetch a metric for multiple assets at a time take a look atsan.get_manyAsyncBatchis the recommended batch class. It executes all the queries in
separate HTTP requests. The benefit of usingAsyncBatchover looping and
executing every API call is that the queries can be executed concurrently.
Putting multiple API calls in separate HTTP calls also allows to fetch more
data, otherwise you might run intoComplexityissues.
The concurrency is controlled by themax_workersoptional parameter to theexecutefunction. By default themax_workersvalue is 10.
It also supportsget_manyfunction to fetch data for many assets.Batchcombines all the provided queries in a single GraphQL document and
executes them in a single HTTP request. This batching technique should be used
when lightweight queries that don't fetch a lot of data are used. The reason is
that thecomplexityof each query
is accumulated and the batch can be rejected.Note: If you have been usingBatch()and want to switch to the newerAsyncBatch()you only need to
change the batch initialization. The functions for adding queries and executing the batch, as well as the
format of the response, are the same.fromsanimportBatchbatch=Batch()batch.get("daily_active_addresses",slug="santiment",from_date="2018-06-01",to_date="2018-06-05",interval="1d")batch.get("transaction_volume",slug="santiment",from_date="2018-06-01",to_date="2018-06-05",interval="1d")[daa,trx_volume]=batch.execute()fromsanimportAsyncBatchbatch=AsyncBatch()batch.get("daily_active_addresses",slug="santiment",from_date="2018-06-01",to_date="2018-06-05",interval="1d")batch.get_many("daily_active_addresses",slugs=["bitcoin","ethereum"],from_date="2018-06-01",to_date="2018-06-05",interval="1d")[daa,daa_many]=batch.execute(max_workers=10)Rate Limit ToolsThere 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 limitationrate_limit_time_left- Returns the time left before the rate limit expiresapi_calls_made- Returns the API calls for each day in which it was usedapi_calls_remaining- Returns the API calls remaining for the month, hour and minuteExample:importtimeimportsantry:san.get("price_usd",slug="santiment",from_date="utc_now-30d",to_date="utc_now",interval="1d")exceptExceptionase:ifsan.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()Metric ComplexityFetch 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 50000. 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.More about the complexity can be found onSantiment Academysan.metric_complexity(metric="price_usd",from_date="2020-01-01",to_date="2020-02-20",interval="1d")Include Incomplete Data FlagDaily metrics have one value per day. For the current day, the latest computed
value will not include a full day of data. For example, computingdaily_active_addressesat 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, theincludeIncompleteDataflag must be used.san.get("daily_active_addresses/bitcoin",from_date="utc_now-3d",to_date="utc_now",interval="1d",include_incomplete_data=True)Metric/Asset pair available cinceFetch 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")Transform the resultExample usage:san.get("price_usd",slug="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 Viwith the average of the last "moving_average_base" values."consecutive_differences" - Replace every value Viwith the value Vi- Vi-1where 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 Viwith the percent change of Vi-1and Vi( (Vi/ Vi-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.Available projectsReturns a DataFrame with all the projects available in the Santiment API. Not all
metrics will be available for each of the projects.slugis 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
...Non-standard metricsHere is a list of metrics that are not part of the returned list of metrics found above.
This is due to having different response format and semantics.Other Price metricsMarketcap, Price USD, Price BTC and Trading Volumesan.get("prices",slug="santiment",from_date="2018-06-01",to_date="2018-06-05",interval="1d")Open, High, Close, Low Prices, Volume, MarketcapNotes:This query cannot be batched.The format with separateslug/selectorargument is not supportedsan.get("ohlcv/santiment",from_date="2018-06-01",to_date="2018-06-05",interval="1d")Example result:datetimeopenPriceUsdclosePriceUsdhighPriceUsdlowPriceUsdvolumemarketcap2018-06-0100:00:00+00:001.243801.276681.265991.190998528577.736268e+072018-06-0200:00:00+00:001.261361.307791.276121.2095812425207.864724e+072018-06-0300:00:00+00:001.282701.283571.246251.2187210329107.844339e+072018-06-0400:00:00+00:001.232761.249101.185281.180106174517.604326e+07Historical BalanceHistorical balance for erc20 token or eth address. Returns the historical balance for a given address in the given interval.san.get("historical_balance",slug="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  215664.33Ethereum Top TransactionsTop ETH transactions for project's team wallets.Available transaction types:ALLINOUTsan.get("eth_top_transactions",slug="santiment",from_date="2019-04-18",to_date="2019-04-30",limit=5,transaction_type="ALL")Example result:The result is shortened for conveniencedatetime                           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...         15.15Ethereum Spent Over TimeETH spent for each interval from the project's team wallet and time periodsan.get("eth_spent_over_time",slug="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   0.000000Token Top TransactionsTop transactions for the token of a given projectsan.get("token_top_transactions",slug="santiment",from_date="2019-04-18",to_date="2019-04-30",limit=5)Example result:The result is shortened for conveniencedatetime                           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...   20544.42975Top TransfersTop transfers for the token of a given project,addressandtransaction_typearguments can be added as well, in the form of a key-value pair. Thetransaction_typeparameter can have one of these three values:ALL,OUT,IN.san.get("top_transfers",slug="santiment",from_date="utc_now-30d",to_date="utc_now",)The result is shortened for convenienceExample 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",slug="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 TrendsEmerging 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   haikuTop Social Gainers LosersTop 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 conveniencedatetime                              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  NEWCOMERExtrasTake a look at theexamplesfolder.DevelopmentIt is recommended to usepipenvfor managing your local environment.Setup project:pipenvinstallInstall main dependencies:pipenvrunpipinstall-e.Install extra dependencies:pipenvrunpipinstall-e'.[extras]'Running testspythonsetup.pytestRunning integration testspythonsetup.pynosetests-aintegration