Labelator.io - python client
Python client for Labelator.io - labeling and ML training studio
Install
pip install labelatorio
Getting your API token
Docs:
Full Labelator.io documentation can be found here docs.labelator.io
Page dedicated this client can be found here
Usage
Connecting client
import labelatorio
client = labelatorio.Client(api_token="your_api_token")
Getting project info
Package requirements are handled using pip. To install them do
# get project by id
existing_project = client.projects.get("2fab1778-e8b1-4327-ac83-16dd0e783ab4")
# if you have just name
existing_project = client.projects.get_by_name("my name")
# or if you don't know the exact name
existing_project = client.projects.search("my name")
Adding, updating documents
df = pd.DataFrame({
"key":["first","second"], # mandatory
"text":["this is my first text", "completely different text..."], # mandatory
"my_custom_column":["note 1",None] # optional
"labels":[["ClassA"],None] #optional if you have labels - should be defined in project
})
ids = client.documents.add_documents(project_id, data=df)
client.documents.set_labels(project_id,ids[1],["ClassB"])
Quering documents
# simple keyword search ...
found = client.documents.search(keyword="completely different")
# find all documents where "ClassA" was predicted
found = client.documents.search( predicted_label="ClassA")
# find all documents where "ClassA" was incorrectly predicted
found = client.documents.search( false_positives="ClassA")
1 maintainer
Metadata
1 maintainer
Release files for labelatorio 0.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| labelatorio-0.4.1.tar.gz | 17.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| labelatorio-0.4.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 35.0 kB
Release files / labelatorio-0.4.1.tar.gz
| Download URL | labelatorio-0.4.1.tar.gz |
|---|---|
| Size | 17.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.16
|
Release files / labelatorio-0.4.1-py3-none-any.whl
| Download URL | labelatorio-0.4.1-py3-none-any.whl |
|---|---|
| Size | 17.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1bb136e1529d5be4732339b31df6ff22f6d5c1c4d9e37350dccc8bf1e147a787
|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.16
|
