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View Code? Open in Web Editor NEWPython API and command line interface for the numer.ai machine learning competition
Home Page: http://numerapi.readthedocs.io
License: MIT License
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parrondo kogamiyabi30 dhj-io prithvinambiar mattliston edoffagne numerai selvamshan nunofernandes-plight afcarl strategist922 rydeen7 jparyani pschork orazaro michael-phillips-data gerstej9 lawali-hub vivanvatsa talhaasmal jeethu bouweceunen liamhz danreia ddyuewang wintellisys adityang joerenner benschreyer stoyandimov alirezamdv kwan-yau jos1977 cshanes wtvr-ai brunodoamaral ndharasz restrading habakan npezolano rdeggau jkom329 ledmaster jpmcd12 yogesh-bansal imbikramsaha anhmike thomaswong2022 uditgupta10 faridafradi andrewbezold nbarbosa-git yarimiz peterhamfelt imacoduh evoandronumerapi's Issues
napi.download_dataset() corrupts previously existing parquet files
According to @jaqume on the Numerai forum, https://forum.numer.ai/t/v4-train-parquet-changed-from-311-to-312/5277 , napi.download_dataset() sometimes corrupts previously existing parquet files. I'm submitting an issue here so that the problem/discussion does not go unnoticed.
Signals API not showing TC score
Hi,
for the classic numerai tournament I can get the true contribution (TC) results for each model via numerapi. But for signals I can not get TC. It would be great if this could be added.
Is the tournament name in daily_submission_performances still correct?
It returns kazutsugi. Shouldn't it be nomi?
seeking ways to modify profile information (image, bio) via numerapi
Hi there.
I'm finally using more of the model slots afforded to us tourney participants and I'm running into some things that would be great to automate. I didn't see a way to adjust profile images or bios via numerapi and wanted to log that as an enhancement request.
Thanks!
- chris
download_dataset() defaults to non v4.2 live data file
V4.2 dataset does not contain numerai_live_data.csv file, which is default value for NumerAPI.download_dataset function. It downloads the file, but it is not default latest live_data file. Last version with numerai_live_data.csv was v3, which will be discontinued. So, I believe the default value should be changed or not allowed.
parse_float_string should use Decimal instead of float
Hi,
thanks for the great work! I have one remark:
I think the parse_float_string should parse the string and return Decimal instead of float, especially for staking confidences and NMR values. Using floats here leads to awful rounding errors (confidences like 0.04 is turned to 0.040000000000000000832667268468867405317723751068115234375).
As a best practice, floats should never be used for financial data or fixed point decimals which need to guarantee the precision (confidence here).
Thanks :)
interactive console usage / download progress bar
Hello,
the numerapi uses tqdm to display progress bar while downloading dataset. This completely messes up the output if numerapi is used in application which redirects output to a file (non-interactive mode).
Please do not assume that the software using numerapi runs in console and make the interactive output / features configurable.
ValueError: Cannot query field "phoneVerificationBonus" on type "User"
This exception has started happening today for me
2019-07-30 20:55:36,696 ERROR numerapi.utils: Http Error: 400 Client Error: Bad Request for url: https://api-tournament.numer.ai/
2019-07-30 20:55:36,699 ERROR numerapi.numerapi: Cannot query field "phoneVerificationBonus" on type "User". Did you mean "phoneNumber"?
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-8-9211763ede81> in <module>()
----> 1 payments = napi.get_payments()
2 stakes = napi.get_stakes()
~/venvs/python3/lib/python3.6/site-packages/numerapi/numerapi.py in get_payments(self)
1047 }
1048 """
-> 1049 data = self.raw_query(query, authorization=True)['data']
1050 payments = data['user']
1051 # convert strings to python objects
~/venvs/python3/lib/python3.6/site-packages/numerapi/numerapi.py in raw_query(self, query, variables, authorization)
220 err = self._handle_call_error(result['errors'])
221 # fail!
--> 222 raise ValueError(err)
223 return result
224
ValueError: Cannot query field "phoneVerificationBonus" on type "User". Did you mean "phoneNumber"?
allow downloading the new dataset via the cli interface
add a possibility to get historical daily scores
it would be helpful to have something like this:
get_daily_scores(model_id, round_num = None, day_num = None)
which would return daily scores for that model (eventually filtered for specific round or even a day) (CORR20V2, CORR20, CORJ60, FNCV3, TC)
Handle api errors better
Not sure what the underlying error here is. I am pretty sure it is a time out error. I would recommend adding a simple retry mechanism or at least wrap in a try-catch and print the response
2019-01-22 12:12:51,741 INFO numerapi.numerapi: uploading predictions...
Traceback (most recent call last):
File "numerai_tools/integration_test.py", line 78, in <module>
main()
File "numerai_tools/integration_test.py", line 38, in main
file_path=file_path, tournament=tournament_number)
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/numerapi/numerapi.py", line 1242, in upload_predictions
create = self.raw_query(create_query, arguments, authorization=True)
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/numerapi/numerapi.py", line 214, in raw_query
result = r.json()
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/requests-2.21.0-py3.7.egg/requests/models.py", line 897, in json
return complexjson.loads(self.text, **kwargs)
File "/usr/local/Cellar/python/3.7.1/Frameworks/Python.framework/Versions/3.7/lib/python3.7/json/__init__.py", line 348, in loads
return _default_decoder.decode(s)
File "/usr/local/Cellar/python/3.7.1/Frameworks/Python.framework/Versions/3.7/lib/python3.7/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/local/Cellar/python/3.7.1/Frameworks/Python.framework/Versions/3.7/lib/python3.7/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
Directory check in download_dataset in the last update (2.12.2) is broken
The code to get the directory from the dest_path seems wrong because for example:
dest_path="/storage/NUMERAI/v4/validation_int8.parquet"
dest_path.rsplit("/")[0]
# returns:
''
# because
dest_path.rsplit("/")
# returns this list:
['', 'storage', 'NUMERAI', 'v4', 'validation_int8.parquet']
# the intention was probably this (1 for maxsplit)
dest_path.rsplit("/",1)[0]
# which returns:
'/storage/NUMERAI/v4'
# but that would be still wrong in edge caseses
# (like '/validation_int8.parquet' would return empty string and os.makedirs in the next line would fail)
# so the better solution to get the directory from the path would be:
os.path.dirname(dest_path)add an option to stake_get to include pending payouts
query {
v3UserProfile(modelName: $modelName) {
roundModelPerformances {
roundNumber
payout
selectedStakeValue
}
}
}
UnicodeEncodeError on SignalsAPI.get_models()
While trying to submit predictions to Signals, I get the following exception when trying to run SignalsAPI.get_models()
Exception has occurred: UnicodeEncodeError
'latin-1' codec can't encode character '\u05d7' in position 33: ordinal not in range(256)
My code for reference
public_id = XXX
secret_key = YYY
napi = numerapi.SignalsAPI(public_id, secret_key)
model_id = napi.get_models()
Environment details:
Python 3.9.6 on Windows 10
requests==2.26.0
requests-oauthlib==1.3.0
numerapi==2.6.0
Reproducing with numerai==2.4.5 also, and with requests==2.23.0
Methods throw: "ValueError: Your session is invalid or has expired."
The following NumerAPI functions throw "ValueError: Your session is invalid or has expired.". I suspect it is due to outdated GraphQL queries to the Numerai endpoint (or it is a problem on my end, though I've tried to exhaust this possibility):
get_user()
get_payments()
get_transactions()
get_stakes()
Timeout Error: HTTPSConnectionPool(host='api-tournament.numer.ai', port=443)
When using upload prediction, keep getting timeout error.
napi.upload_predictions('./xxx.csv', model_id = 'xxx' )
ERROR numerapi.utils: Timeout Error: HTTPSConnectionPool(host='api-tournament.numer.ai', port=443): Read timed out. (read timeout=3)
New tournament round ??
Is there a way to check that the new round has began before downloading the tournament file ?
stake discrepancy in world of remove vs compound
I was a quick adopter of the "remove stakes" option as soon as they made it available.
But it appears numerapi still assumes that compounding is part of the actual stakes even with models that have it set to remove.
The model "ashitaka" for example has an actual stake of 10 NMR but here's what numerapi returns:
> numerapi stake-get ashitaka
10.138241189551394000
Would be cool to have an option that would allow for including vs not including any pending earnings. Such as:
> numerapi stake-get -stakeOnly ashitaka
10.0
and/or something just to capture the earnings:
> numerapi stake-get -earningsOnly ashitaka
0.1382411
The default behavior could remain the same.
Anyway, thx for listening!
upload_diagnostics not working
I am trying to get diagnostics. This is a code snippet I am using:
publicid = ...
secretkey = ...
api = NumerAPI(publicid, secretkey)
submission_path = ...
model_id = ...
api.upload_diagnostics(submission_path, model_id=model_id)I am getting the following error:
2021-12-30 00:35:19,570 INFO numerapi.base_api: uploading diagnostics...
+2021-12-30 00:36:20,845 ERROR numerapi.utils: Http Error: 504 Server Error: Gateway Time-out for url: https://api-tournament.numer.ai/
2021-12-30 00:36:20,845 ERROR numerapi.utils: Did not receive a valid JSON: Expecting value: line 1 column 1 (char 0)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-13-d72ad6279651> in <module>
----> 1 api.upload_diagnostics("...", model_id="...")
/nix/store/3cb4vw75i6ranmzqwznaazhdf4wihzxq-python3-3.9.6-env/lib/python3.9/site-packages/numerapi/base_api.py in upload_diagnostics(self, file_path, tournament, model_id, df)
448 'modelId': model_id}
449 create = self.raw_query(create_query, arguments, authorization=True)
--> 450 self.diagnostics_id = create['data']['createDiagnostics']['id']
451 return self.diagnostics_id
452
KeyError: 'data'Is this because of the timeout error? If so, is there a way to increase the timeout?
add era2round and round2era functionality.
afaik, this information is not provided in the API. should be straight-forward to compute
Add multi-model stake_set support for NumerAPI
I left the default behavior when a username isn't passed e.g.:
def stake_set(self, nmr, username: str = None) -> Dict:
See:
#71
tqdm exceptions
Not sure what is going on here. Why would TQDM throw this exception? I don't believe tqdm is even invoked during the submission flow, so the exception must be from downloading the file, which already hit 100%???
Probably tqdm's fault: tqdm/tqdm#613
/tmp/numerai_dataset_143.zip: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌| 160M/161M [00:24<00:00, 6.82MB/s]2019-01-19 10:00:27,212 INFO numerapi.numerapi: unzipping file...
2019-01-19 10:00:30,052 INFO numerapi.numerapi: uploading predictions...
/tmp/numerai_dataset_143.zip: 161MB [00:40, 6.82MB/s] 2019-01-19 10:00:58,339 INFO numerapi.numerapi: uploading predictions...
2019-01-19 10:01:23,726 INFO numerapi.numerapi: uploading predictions...
2019-01-19 10:01:55,983 INFO numerapi.numerapi: uploading predictions...
2019-01-19 10:02:25,782 INFO numerapi.numerapi: uploading predictions...
2019-01-19 10:02:52,202 INFO numerapi.numerapi: uploading predictions...
2019-01-19 10:03:17,700 INFO numerapi.numerapi: uploading predictions...
Exception ignored in: <function tqdm.__del__ at 0x106b53950>
Traceback (most recent call last):
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/tqdm-4.28.1-py3.7.egg/tqdm/_tqdm.py", line 931, in __del__
self.close()
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/tqdm-4.28.1-py3.7.egg/tqdm/_tqdm.py", line 1133, in close
self._decr_instances(self)
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/tqdm-4.28.1-py3.7.egg/tqdm/_tqdm.py", line 496, in _decr_instances
cls.monitor.exit()
File "/Users/anson/numerai/database-scripts/env/lib/python3.7/site-packages/tqdm-4.28.1-py3.7.egg/tqdm/_monitor.py", line 52, in exit
self.join()
File "/usr/local/Cellar/python/3.7.1/Frameworks/Python.framework/Versions/3.7/lib/python3.7/threading.py", line 1029, in join
raise RuntimeError("cannot join current thread")
RuntimeError: cannot join current thread
Help Me
Hello, i am new in numerai and i have checked your example. on the example you have csv file called "preds.csv", how can i generate "preds.csv" file?
Thanks,
API for submitting and getting numbers from Newly introduced "Diagnostics Tool"
Previously user can submit prediction and get expected Sharp Ratio, Corr, MMC information . Now that Numerai introduced new tool "Diagnostics Tool" - Can we have API for the same.
Internal server error on predictions upload
I'm having problems uploading predictions using the tool, I get this traceback
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-14-efa78b5ed793> in <module>
46 outputFile = "%s_submission.csv" % target
47 joined.to_csv(outputFile, index=False)
---> 48 napi.upload_predictions(outputFile, tournament=tournamentRound)
49 break
/opt/conda/lib/python3.6/site-packages/numerapi/numerapi.py in upload_predictions(self, file_path, tournament)
1288 'tournament': tournament}
1289 submission_resp = self.raw_query(auth_query, arguments,
-> 1290 authorization=True)
1291 submission_auth = submission_resp['data']['submission_upload_auth']
1292 with open(file_path, 'rb') as fh:
/opt/conda/lib/python3.6/site-packages/numerapi/numerapi.py in raw_query(self, query, variables, authorization)
217 err = self._handle_call_error(result['errors'])
218 # fail!
--> 219 raise ValueError(err)
220 return result
221
ValueError: Internal server errorOther calls work correctly e.g. napi.get_payments()
logging
I find it kind of weird to pass a verbosity level on NumerAPI constructor, usually for a lib is recommended to attach a NullHandler [1] and let the consumer configure it.
[1] https://docs.python.org/3.6/howto/logging.html#configuring-logging-for-a-library
example.py fail with missing "originality" entry on type "LeaderboardEntry"
Seems that the interfact to numberapi has changed to the server...
`/usr/bin/python3.6 /home/tensor/docker/numerai/NumerAPI/example.py
2019-12-31 13:05:33,043 INFO numerapi.numerapi: downloading current dataset...
2019-12-31 13:05:33,044 INFO numerapi.numerapi: target file already exists
2019-12-31 13:05:33,044 INFO numerapi.numerapi: getting rounds...
[{'datasetId': 'NULL', 'number': 192, 'openTime': '2019-12-28T18:00:00Z', 'resolveTime': '2020-01-28T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 191, 'openTime': '2019-12-21T18:00:00Z', 'resolveTime': '2020-01-21T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 190, 'openTime': '2019-12-14T18:00:00Z', 'resolveTime': '2020-01-14T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 189, 'openTime': '2019-12-07T18:00:00Z', 'resolveTime': '2020-01-07T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 188, 'openTime': '2019-11-30T18:00:00Z', 'resolveTime': '2019-12-31T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 187, 'openTime': '2019-11-23T18:00:00Z', 'resolveTime': '2019-12-24T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 186, 'openTime': '2019-11-16T18:00:00Z', 'resolveTime': '2019-12-17T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 185, 'openTime': '2019-11-09T18:00:00Z', 'resolveTime': '2019-12-10T20:00:00Z', 'resolvedGeneral': False, 'resolvedStaking': False}, {'datasetId': 'NULL', 'number': 184, 'openTime': '2019-11-02T18:00:00Z', 'resolveTime': '2019-12-03T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 183, 'openTime': '2019-10-26T18:00:00Z', 'resolveTime': '2019-11-26T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 182, 'openTime': '2019-10-19T18:00:00Z', 'resolveTime': '2019-11-19T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 181, 'openTime': '2019-10-12T18:00:00Z', 'resolveTime': '2019-11-12T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 180, 'openTime': '2019-10-05T18:00:00Z', 'resolveTime': '2019-11-05T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 179, 'openTime': '2019-09-28T18:00:00Z', 'resolveTime': '2019-10-29T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 178, 'openTime': '2019-09-21T18:00:00Z', 'resolveTime': '2019-10-22T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 177, 'openTime': '2019-09-14T18:00:00Z', 'resolveTime': '2019-10-15T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 176, 'openTime': '2019-09-07T18:00:00Z', 'resolveTime': '2019-10-08T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 175, 'openTime': '2019-08-31T18:00:00Z', 'resolveTime': '2019-10-01T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 174, 'openTime': '2019-08-24T18:00:00Z', 'resolveTime': '2019-09-24T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 173, 'openTime': '2019-08-17T18:00:00Z', 'resolveTime': '2019-09-17T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 172, 'openTime': '2019-08-10T18:00:00Z', 'resolveTime': '2019-09-10T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 171, 'openTime': '2019-08-03T18:00:00Z', 'resolveTime': '2019-09-03T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 170, 'openTime': '2019-07-27T18:00:00Z', 'resolveTime': '2019-08-27T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 169, 'openTime': '2019-07-20T18:00:00Z', 'resolveTime': '2019-08-20T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 168, 'openTime': '2019-07-13T18:00:00Z', 'resolveTime': '2019-08-13T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 167, 'openTime': '2019-07-06T18:00:00Z', 'resolveTime': '2019-08-06T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 167, 'openTime': '2019-07-06T18:00:00Z', 'resolveTime': '2019-08-06T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 167, 'openTime': '2019-07-06T18:00:00Z', 'resolveTime': '2019-08-06T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 167, 'openTime': '2019-07-06T18:00:00Z', 'resolveTime': '2019-08-06T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 167, 'openTime': '2019-07-06T18:00:00Z', 'resolveTime': '2019-08-06T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 166, 'openTime': '2019-06-29T18:00:00Z', 'resolveTime': '2019-07-30T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 166, 'openTime': '2019-06-29T18:00:00Z', 'resolveTime': '2019-07-30T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 166, 'openTime': '2019-06-29T18:00:00Z', 'resolveTime': '2019-07-30T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 166, 'openTime': '2019-06-29T18:00:00Z', 'resolveTime': '2019-07-30T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 166, 'openTime': '2019-06-29T18:00:00Z', 'resolveTime': '2019-07-30T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 165, 'openTime': '2019-06-22T18:00:00Z', 'resolveTime': '2019-07-23T20:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': 'NULL', 'number': 165, 'openTime': 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{'datasetId': '591cb525e14d1c6178315ab4', 'number': 56, 'openTime': '2017-05-17T21:00:00Z', 'resolveTime': '2017-06-14T21:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '59136468b2f5ff13723deee0', 'number': 55, 'openTime': '2017-05-10T21:00:00Z', 'resolveTime': '2017-06-07T21:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '590a2588b2f5ff4570a045a2', 'number': 54, 'openTime': '2017-05-03T21:00:00Z', 'resolveTime': '2017-05-31T21:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '59011e91fd74047e5d9e29cd', 'number': 53, 'openTime': '2017-04-26T21:00:00Z', 'resolveTime': '2017-05-24T21:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58f90dd3fd7404850d09f4f3', 'number': 52, 'openTime': '2017-04-20T21:00:00Z', 'resolveTime': '2017-05-17T21:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58efe94afd7404241ba2c735', 'number': 51, 'openTime': 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'resolvedStaking': True}, {'datasetId': '58b73d141cbccb280d126033', 'number': 45, 'openTime': '2017-03-01T22:00:00Z', 'resolveTime': '2017-03-29T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58abc58449fe352636b470f9', 'number': 44, 'openTime': '2017-02-21T06:00:00Z', 'resolveTime': '2017-03-22T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58a680214af58d92cc1b6653', 'number': 43, 'openTime': '2017-02-17T05:20:00Z', 'resolveTime': '2017-03-14T06:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58a4c684dd8f7f4806d704ec', 'number': 42, 'openTime': '2017-02-15T22:00:00Z', 'resolveTime': '2017-03-10T05:20:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '589b897b1aed925a126572cb', 'number': 41, 'openTime': '2017-02-08T22:00:00Z', 'resolveTime': '2017-03-08T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58923a49610562f30668e498', 'number': 40, 'openTime': '2017-02-01T22:00:00Z', 'resolveTime': '2017-03-01T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58891435c88b5f1c17073cdd', 'number': 39, 'openTime': '2017-01-25T22:00:00Z', 'resolveTime': '2017-02-22T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '587fda87509453d7088f49e8', 'number': 38, 'openTime': '2017-01-18T22:00:00Z', 'resolveTime': '2017-02-15T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5876a4c24acc174313695b22', 'number': 37, 'openTime': '2017-01-11T22:00:00Z', 'resolveTime': '2017-02-08T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '586d4cacfb86a8de03a53c50', 'number': 36, 'openTime': '2017-01-04T22:00:00Z', 'resolveTime': '2017-02-01T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58642a66c469bafd0569ca9f', 'number': 35, 'openTime': '2016-12-29T01:00:00Z', 'resolveTime': '2017-01-25T22:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '585adcf59f29b12803971524', 'number': 34, 'openTime': '2016-12-22T01:00:00Z', 'resolveTime': '2017-01-19T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '585265f07d4d5f1a0863e7b1', 'number': 33, 'openTime': '2016-12-15T09:56:00Z', 'resolveTime': '2017-01-12T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5851d897ac6d4bf10b1d357b', 'number': 32, 'openTime': '2016-12-15T01:00:00Z', 'resolveTime': '2017-01-05T09:56:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58488d878082364f050b2e5e', 'number': 31, 'openTime': '2016-12-08T01:00:00Z', 'resolveTime': '2017-01-05T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '583f61e64824888e06322404', 'number': 30, 'openTime': '2016-12-01T01:00:00Z', 'resolveTime': '2016-12-29T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5835f4e1a1c0ed9003041b5b', 'number': 29, 'openTime': '2016-11-24T01:00:00Z', 'resolveTime': '2016-12-22T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '582cefc0fb620c2d0d14541b', 'number': 28, 'openTime': '2016-11-17T01:00:00Z', 'resolveTime': '2016-12-15T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '58239b6c43253b8804603a2c', 'number': 27, 'openTime': '2016-11-10T01:00:00Z', 'resolveTime': '2016-12-08T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '581a54a0cff35534113c5b78', 'number': 26, 'openTime': '2016-11-03T00:00:00Z', 'resolveTime': '2016-12-01T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5810d6755152d7b502e46b2f', 'number': 25, 'openTime': '2016-10-27T00:00:00Z', 'resolveTime': '2016-11-24T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5807df9e05d45ca709019658', 'number': 24, 'openTime': '2016-10-20T00:00:00Z', 'resolveTime': '2016-11-17T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57feb95594a60fb10d2fc2b5', 'number': 23, 'openTime': '2016-10-13T00:00:00Z', 'resolveTime': '2016-11-10T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57f56b671fd7b492089b5556', 'number': 22, 'openTime': '2016-10-06T00:00:00Z', 'resolveTime': '2016-11-03T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57ec432cbda17743039adc83', 'number': 21, 'openTime': '2016-09-29T00:00:00Z', 'resolveTime': '2016-10-27T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57e2d83295c9fe518ccf18b1', 'number': 20, 'openTime': '2016-09-22T00:00:00Z', 'resolveTime': '2016-10-20T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57d97c7d95c9fe518ccf18b0', 'number': 19, 'openTime': '2016-09-15T00:00:00Z', 'resolveTime': '2016-10-13T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57cf4f7095c9fe518ccf18ac', 'number': 18, 'openTime': '2016-09-08T00:00:00Z', 'resolveTime': '2016-10-06T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57c60cf795c9fe518ccf18aa', 'number': 17, 'openTime': '2016-09-01T00:00:00Z', 'resolveTime': '2016-09-29T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57bd1a0c95c9fe518ccf18a8', 'number': 16, 'openTime': '2016-08-25T00:00:00Z', 'resolveTime': '2016-09-22T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57b4899195c9fe518ccf18a6', 'number': 15, 'openTime': '2016-08-18T00:00:00Z', 'resolveTime': '2016-09-15T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57aada7d95c9fe518ccf18a4', 'number': 14, 'openTime': '2016-08-11T00:00:00Z', 'resolveTime': '2016-09-08T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57a228e895c9fe518ccf18a2', 'number': 13, 'openTime': '2016-08-04T00:00:00Z', 'resolveTime': '2016-09-01T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57991fc095c9fe518ccf18a0', 'number': 12, 'openTime': '2016-07-28T00:00:00Z', 'resolveTime': '2016-08-25T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '578fa2fa95c9fe518ccf189d', 'number': 11, 'openTime': '2016-07-21T00:00:00Z', 'resolveTime': '2016-08-18T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5784da390e889085a5cfd51b', 'number': 10, 'openTime': '2016-07-13T00:00:00Z', 'resolveTime': '2016-08-11T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '5772b916a6fe2a12184dba65', 'number': 9, 'openTime': '2016-06-29T00:00:00Z', 'resolveTime': '2016-08-03T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '576484ccf9a57fac85762009', 'number': 8, 'openTime': '2016-06-19T00:00:00Z', 'resolveTime': '2016-07-20T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '57574e902f77e20a3ef4bf22', 'number': 7, 'openTime': '2016-06-08T00:00:00Z', 'resolveTime': '2016-07-10T00:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56d8b272ee5ca4964652231b', 'number': 6, 'openTime': '2016-05-01T01:00:00Z', 'resolveTime': '2016-06-26T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56d8b272ee5ca4964652231b', 'number': 5, 'openTime': '2016-04-03T01:00:00Z', 'resolveTime': '2016-05-22T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56d8b272ee5ca4964652231b', 'number': 4, 'openTime': '2016-03-04T01:00:00Z', 'resolveTime': '2016-04-24T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56d8b272ee5ca4964652231b', 'number': 3, 'openTime': '2016-02-03T01:00:00Z', 'resolveTime': '2016-03-25T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56d8b272ee5ca4964652231b', 'number': 2, 'openTime': '2016-01-05T01:00:00Z', 'resolveTime': '2016-02-24T01:00:00Z', 'resolvedGeneral': True, 'resolvedStaking': True}, {'datasetId': '56516517e16d9f8ea0aa716f', 'number': 1, 'openTime': '2015-12-01T08:00:01Z', 'resolveTime': '2016-01-26T07:59:59Z', 'resolvedGeneral': True, 'resolvedStaking': True}]
2019-12-31 13:05:33,720 INFO numerapi.numerapi: getting leaderboard for round 0
2019-12-31 13:05:33,988 ERROR numerapi.numerapi: Cannot query field "originality" on type "LeaderboardEntry".
Traceback (most recent call last):
File "/home/tensor/docker/numerai/NumerAPI/example.py", line 33, in
main()
File "/home/tensor/docker/numerai/NumerAPI/example.py", line 19, in main
leaderboard = napi.get_leaderboard()
File "/home/tensor/docker/numerai/NumerAPI/numerapi/numerapi.py", line 198, in get_leaderboard
result = self.raw_query(query, arguments)
File "/home/tensor/docker/numerai/NumerAPI/numerapi/numerapi.py", line 153, in raw_query
raise ValueError(err)
ValueError: Cannot query field "originality" on type "LeaderboardEntry".
Process finished with exit code 1
`
get_stakes() needs updating
Hi -
Trying to call get_stakes() as per the docs with something like this:
napi = numerapi.NumerAPI( PUBLIC_ID, SECRET_KEY)
napi.get_stakes( MODEL_ID)
Throws an error.
2021-02-12 14:40:24,678 ERROR numerapi.base_api: Cannot query field "stakeTxs" on type "Model". Did you mean "stakeBonusPayments" or "v2Stake"?
--------------------
ValueErrorTraceback (most recent call last)
<ipython-input-7-9d5a0bb1c65f> in <module>
----> 1 napi.get_stakes()
~/.pyenv/versions/3.7.9/envs/dev/lib/python3.7/site-packages/numerapi/numerapi.py in get_stakes(self, model_id)
881 """
882 arguments = {'modelId': model_id}
--> 883 data = self.raw_query(query, arguments, authorization=True)['data']
884 stakes = data['model']['stakeTxs']
885 # convert strings to python objects
~/.pyenv/versions/3.7.9/envs/dev/lib/python3.7/site-packages/numerapi/base_api.py in raw_query(self, query, variables, authorization)
118 err = self._handle_call_error(result['errors'])
119 # fail!
--> 120 raise ValueError(err)
121 return result
122
ValueError: Cannot query field "stakeTxs" on type "Model". Did you mean "stakeBonusPayments" or "v2Stake"?
I might be missing something obvious but I'm passing in a model UUID as guided. Thoughts?
Thanks in advance,
-- chris
SignalsAPI.ticker_universe file does not exists
Calling numerapi.SignalsAPI().ticker_universe() results in
File "/home/guild/.local/share/virtualenvs/numerai_signals-U8JYJbZP/lib/python3.8/site-packages/numerapi/signalsapi.py", line 310, in ticker_universe
path = self.download_dataset("signals/universe_public.csv")
File "/home/guild/.local/share/virtualenvs/numerai_signals-U8JYJbZP/lib/python3.8/site-packages/numerapi/base_api.py", line 201, in download_dataset
dataset_url = self.raw_query(query, args)['data']['dataset']
File "/home/guild/.local/share/virtualenvs/numerai_signals-U8JYJbZP/lib/python3.8/site-packages/numerapi/base_api.py", line 133, in raw_query
raise ValueError(err)
ValueError: the requested file does not exist
check_new_round default 24h doesn't suit well the daily tournaments
Dear developes,
with the introduction of the daily tournaments the default value of 24h for check_new_round seems too high. Basically the function returns always True. It would be worth decreasing that to 12h or something.
thank you
Luca
daily_submissions_performances returns results even after rounds is resolved
Hi,
I use numerapi to get the final rounds results for my models. In the past I did this the following way:
df = pd.DataFrame(napi.daily_submissions_performances(model_name))
data = df.sort_values(by="date").groupby("roundNumber").last()
However, this suddenly gave me wrong results. I found out that numerapi is returning the results for each model even beyond the 20 days of the round. This behaviour seems strange to me.
To make it work again I had to change the code to the following:
df = pd.DataFrame(napi.daily_submissions_performances(model_name))
data = df.sort_values(by="date").groupby("roundNumber").nth(19)
Is this behaviour intended?
check_round_open()
It throws an error if the round is not open. It would be much better if it returned false.
HTTPError: 403 Client Error: Forbidden for url
Just tried to download data for the new tournament...
explicit model_id ?
I found doing submit_predictions that I needed to use the actual model_id string from the numerai model page.
The get_model_id stuff in the examples failed with insufficient permissions.
get_user_activities() errors out
The following code used to work:
>>> import numerapi
>>> napi = numerapi.NumerAPI(verbosity="info")
>>> data = napi.get_user_activities("madmin")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.7/site-packages/numerapi/numerapi.py", line 716, in get_user_activities
if item['stake']['date'] is None:
TypeError: 'NoneType' object is not subscriptable
Send "source" field during createSubmission
Numerai recently introduced an optional "source" field on submissions that can help us gather statistics on how each user is submitting to the tournament. This is as easy as including the field source: String here:
- NumerAPI:
Lines 614 to 628 in 6924adf
- SignalsAPI:
numerapi/numerapi/signalsapi.py
Lines 132 to 143 in 6924adf
and then adding the "source": "numerapi" in this dict:
- NumerAPI:
Lines 629 to 633 in 6924adf
- SignalsAPI:
numerapi/numerapi/signalsapi.py
Lines 144 to 146 in 6924adf
There's a 1 NMR bounty available for completing this
How to upload predictions for the validation set ?
Maybe I am missing something but I can't see how to upload predictions for the validation set and get back evaluation metrics. Is this implemented or not ?
get_account_transactions throws ValueError
Using versions 2.9.0 and initialising the API with
napi = numerapi.NumerAPI(secret_key=SECRET_KEY, public_id=PUBLIC_ID)
when calling napi.get_account_transactions() the following exception is thrown
ValueError: Cannot query field "nmrWithdrawals" on type "Account". Did you mean "usdWithdrawals"?
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url ...
Hi,
when trying to download the current dataset, I receive the following error:
>>> import numerapi
>>> numerapi.__version__
'2.7.0'
>>> napi = numerapi.NumerAPI(verbosity="info")
>>> napi.download_current_dataset()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/martin/miniconda3/envs/numerai-env/lib/python3.8/site-packages/numerapi/numerapi.py", line 112, in download_current_dataset
utils.download_file(url, dataset_path, self.show_progress_bars)
File "/home/martin/miniconda3/envs/numerai-env/lib/python3.8/site-packages/numerapi/utils.py", line 39, in download_file
req.raise_for_status()
File "/home/martin/miniconda3/envs/numerai-env/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://numerai-datasets.s3.amazonaws.com/t8/278/numerai_datasets.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIJRTTNQLX2AQCKYA%2F20210827%2Fus-west-1%2Fs3%2Faws4_request&X-Amz-Date=20210827T134237Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&X-Amz-Signature=09bf8f25803b8b6f0eea2c0c926ca6cc9f4f288536bbe136287c34fa74622edenumerapi installed via pip into conda environment
python 3.8.10
conda 4.10.1
pip 21.2.2
I'll receive the same error message when deactivating the conda environment
>>> import numerapi
>>> numerapi.__version__
'2.7.0'
>>> napi = numerapi.NumerAPI(verbosity="info")
>>> napi.download_current_dataset()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/martin/.local/lib/python3.9/site-packages/numerapi/numerapi.py", line 112, in download_current_dataset
utils.download_file(url, dataset_path, self.show_progress_bars)
File "/home/martin/.local/lib/python3.9/site-packages/numerapi/utils.py", line 39, in download_file
req.raise_for_status()
File "/usr/lib/python3.9/site-packages/requests/models.py", line 943, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://numerai-datasets.s3.amazonaws.com/t8/278/numerai_datasets.zip?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIJRTTNQLX2AQCKYA%2F20210827%2Fus-west-1%2Fs3%2Faws4_request&X-Amz-Date=20210827T135130Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&X-Amz-Signature=c1265bb60cd825ceb52579ea27d5daa5adcffaa5b7f04bf4e5506287e81b6c65python 3.9.5
Updated numerapi to version 2.7.0, but the same error occurred earlier with version 2.6.0.
When I paste the URL into my browser I can download the zip-file. Adding a header to the get request as suggested here and here did not solve the problem.
Help appreciated, thanks!
Sync stake functionality between NumeraiAPI and SignalsAPI
stake_set is missing from SignalsAPI, will NumeraiAPI.stake_set work if moved to the BaseAPI?
There's a few more differences across NumeraiAPI and SignalsAPI as well,
numerapi.round_details(round_number) not working for rounds <= 318
numerapi.round_details(round_number) not working for rounds <= 318
Cannot submit file (not on compute)
It seems there is something missing in the headers when uploading a submission file.
I'm not on compute, I want to schedule a script on a local machine.
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