https://github.com/hellonico/jquants-api-jvm
https://github.com/hellonico/jquants-api-jvm
Last synced: 9 months ago
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- Host: GitHub
- URL: https://github.com/hellonico/jquants-api-jvm
- Owner: hellonico
- License: epl-1.0
- Created: 2022-09-14T03:03:31.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-10-14T04:41:49.000Z (over 3 years ago)
- Last Synced: 2025-06-11T03:12:39.671Z (11 months ago)
- Language: Clojure
- Size: 942 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# hellonico/jquants-api-jvm
[](https://clojars.org/net.clojars.hellonico/jquants-api-jvm)
[](https://dl.circleci.com/status-badge/redirect/gh/hellonico/jquants-api-jvm/tree/master)
# Goal
jquants-api is a Clojure/JVM Wrapper around the [jquants api](https://jpx-jquants.com/).
The http based [jquants-api](https://jpx.gitbook.io/j-quants-api-en/api-reference/) propose a diverse set of daily financial data, like:
- [Listed Issue](https://jpx.gitbook.io/j-quants-api-en/api-reference/listed-api) Information
- [Stock Price](https://jpx.gitbook.io/j-quants-api-en/api-reference/prices-api) Information
- [Market](https://jpx.gitbook.io/j-quants-api-en/api-reference/markets-api) Information
To use the jquants api, You first need to [register and create an account](https://application.jpx-jquants.com/register).
Once you are registered, to setup your credentials for API access, you either need to:
- use the login function with your username and password, or
- create a login file as shown below:
```clojure
; In $HOME/.config/digima/login.edn
{:mailaddress "youremail@address.com" :password "yourpassword"}
```
Note that the login function simply outputs a file at the needed location.
__The jquants-api specifies a refresh token and an id token to get and refresh but this wrapper will refresh those tokens as needed without the user having to do anything.__
# Usage
For each function call, the returned data structure is according the jquants api, turned into Clojure data structures / maps with keywords as keys based on the json data.
```clojure
(daily {:code 86970 :date 20220118})
;; {:daily_quotes [{:AdjustmentVolume 498800.0
;; :TurnoverValue 1.2302805E9
;; :AdjustmentOpen 2482.0
;; :Low 2440.5
;; :AdjustmentClose 2465.0
;; :Volume 498800.0
;; :High 2489.0
;; :Date "20220118"
;; :AdjustmentHigh 2489.0
;; :Code "86970"
;; :Close 2465.0
;; :AdjustmentFactor 1.0
;; :AdjustmentLow 2440.5
;; :Open 2482.0}]}
```
```clojure
(statements {:code 869701 :date 20220727})
;; {:statements [{:ForecastDividendPerShareAnnual "52.0"
;; :ForecastOperatingProfit "65500000000"
;; :ForecastDividendPerShare2ndQuarter "26.0"
;; :ForecastOrdinaryProfit "65500000000"
;; :Profit "12089000000"
;; :TypeOfDocument "1QFinancialStatements_Consolidated_IFRS"
;; :ResultDividendPerShareFiscalYearEnd ""
;; :DisclosedUnixTime "1658923200.0"
;; :ChangesInAccountingEstimates "false"
;; :DisclosureNumber "20220726504583"
;; :ResultDividendPerShare3rdQuarter ""
;; :MaterialChangesInSubsidiaries "false"
;; :ApplyingOfSpecificAccountingOfTheQuarterlyFinancialStatements ""
;; :NumberOfTreasuryStockAtTheEndOfFiscalYear "1938843"
;; :EarningsPerShare "22.93"
;; :OperatingProfit "17777000000"
;; :NetSales "33576000000"
;; :LocalCode "86970"
;; :DisclosedDate "2022-07-27"
;; :ResultDividendPerShare1stQuarter "－"
;; :Equity "310098000000"
;; :BookValuePerShare ""
;; :CurrentPeriodEndDate "2022-06-30"
;; :DisclosedTime "12:00:00"
;; :ResultDividendPerShareAnnual ""
;; :ChangesOtherThanOnesBasedOnRevisionsOfAccountingStandard "false"
;; :OrdinaryProfit "17790000000"
;; :RetrospectiveRestatement ""
;; :ForecastProfit "45000000000"
;; :EquityToAssetRatio "0.004"
;; :AverageNumberOfShares "527204054"
;; :CurrentFiscalYearEndDate "2023-03-31"
;; :ForecastNetSales "132500000000"
;; :TotalAssets "76048180000000"
;; :ResultDividendPerShare2ndQuarter ""
;; :ChangesBasedOnRevisionsOfAccountingStandard "false"
;; :CurrentFiscalYearStartDate "2022-04-01"
;; :ForecastDividendPerShare1stQuarter ""
;; :ForecastEarningsPerShare "85.42"
;; :ForecastDividendPerShareFiscalYearEnd "26.0"
;; :ForecastDividendPerShare3rdQuarter "－"
;; :NumberOfIssuedAndOutstandingSharesAtTheEndOfFiscalYearIncludingTreasuryStock "528578441"
;; :TypeOfCurrentPeriod "1Q"}]}
```
```clojure
(listed-info {:code 10000})
;; {:info [{:Code "86970"
;; :UpdateDate "20220927"
;; :CompanyNameFull "（株）日本取引所グループ"
;; :MarketCode "A"
;; :CompanyName "ＪＰＸ"
;; :CompanyNameEnglish "Japan Exchange Group,Inc."
;; :SectorCode "7200"}]}
```
# Extra Code for the Wrapper
The wrapper can also create a local cache to get daily quotes based on fuzzy search for the name of the entity to get the quotes from.
Meaning, instead of :
```clojure
(daily {:Code 86970 :date 20220118})
;; {:daily_quotes [{:AdjustmentVolume 498800.0
;; :TurnoverValue 1.2302805E9
;; :AdjustmentOpen 2482.0
;; :Low 2440.5
;; :AdjustmentClose 2465.0
;; :Volume 498800.0
;; :High 2489.0
;; :Date "20220118"
;; :AdjustmentHigh 2489.0
;; :Code "86970"
;; :Close 2465.0
;; :AdjustmentFactor 1.0
;; :AdjustmentLow 2440.5
;; :Open 2482.0}]}
```
You can do:
```clojure
(daily-fuzzy {:CompanyNameEnglish "Japan Exchange" :date 20220118})
;; Same as above
;; {:daily_quotes [{:AdjustmentVolume 498800.0
;; :TurnoverValue 1.2302805E9
;; :AdjustmentOpen 2482.0
;; :Low 2440.5
;; :AdjustmentClose 2465.0
;; :Volume 498800.0
;; :High 2489.0
;; :Date "20220118"
;; :AdjustmentHigh 2489.0
;; :Code "86970"
;; :Close 2465.0
;; :AdjustmentFactor 1.0
;; :AdjustmentLow 2440.5
;; :Open 2482.0}]}
```
# Charting
There is a [charting example](examples/charting-with-oz/src/hellonico/charting.clj) based on the [Ox](https://github.com/metasoarous/oz)
Which would open a browser window and show the following graph:
# Jupyter Notebook example
There is a notebook example for usage with Clojure within Jupyter and Charting jquants data with oz.
# Java Integration
This JQuants wrapper can also be called natively from Java code, with Maps as returned object from API calls.
Maps in Java can be accessed using query using [JXPath](https://commons.apache.org/proper/commons-jxpath/), as shown in the [java example](./examples/JavaSample/src/main/java/info/hellonico/jquantsapi/JQuantsApiSample.java) below:
```java
Map,?> result = api.daily("24130", "20220301");
JXPathContext context = JXPathContext.newContext(result);
Double open = (Double) context.getValue("/daily_quotes[1]/Open");
System.out.printf("Quote for %s on day %s is %f\n", code, date, open);
// Outputs:
// Quote for 24130 on day 20220301 is 4315.000000
```
Another example shows how to chart using [quickchart.io](https://quickchart.io/):
```java
String from = "20220301", to = "20220505";
Map,?> result = api.daily(code, from, to);
JXPathContext context = JXPathContext.newContext(result);
QuickChart chart = new QuickChart();
chart.setWidth(500);
chart.setHeight(300);
String config =
format("{type: 'line',data: {labels: %s , datasets: [{label: 'Open', data:%s ,fill: false}, {label: 'Close', data:%s ,fill: false}]}}",
context.selectNodes("//Date"),
context.selectNodes("//Open"),
context.selectNodes("//Close"));
chart.setConfig(config);
System.out.println(chart.getUrl());
```
Which outputs the following graph:
## License
Copyright © 2022 hellonico
Distributed under the Eclipse Public License version 1.0.