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fiddler-client-2.0.0.dev1
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مشاهده بیشترتوضیحات
Python client for Fiddler Service
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | fiddler-client-2.0.0.dev1 |
| نام | fiddler-client |
| نسخه کتابخانه | 2.0.0.dev1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Fiddler Labs |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://fiddler.ai |
| آدرس اینترنتی | https://pypi.org/project/fiddler-client/ |
| مجوز | - |
Fiddler Client
=============
Python client for interacting with Fiddler. Provides a user-friendly interface to our REST API and enables event
publishing for use with our monitoring features.
Requirements
------------
Requires Python >= Python-3.6.3 and pip >= 19.0
Installation
------------
$ pip3 install fiddler-client
API Example Usage
-------------
Documentation for the API can be found [here](https://api.fiddler.ai/#introduction). For examples of interacting with our APIs, please check out our [Quick Start Guide](https://docs.fiddler.ai/quick-start/) as well as the work notebooks found on our [Samples Github](https://github.com/fiddler-labs/fiddler-samples).
Version History
-------------
### 1.7.3
- #### **Modification**
- Send row and column count information to dataset upload api
### 1.7.2
- #### **Modification**
- Bring back `WeightingParams` object
### 1.7.1
- #### **Modification**
- Relaxed boto3 version constraint
### 1.7.0
- #### **Removed**
- Remove support for initializing fiddler client with version=1
- Following methods are removed
- get_segment_info
- delete_segment
- deactivate_segment
- activate_segment
- list_segments
- upload_segment
- add_monitoring_config
- publish_parquet_s3
- publish_events_log
### 1.6.2
- #### **Modifications**
- Make dataset_id a required field in add_model()
- Update max_inferred_cardinality to 100
- #### **New Features**
- New method for updating a model artifact `update_model_artifact`
### 1.5.3
- #### **Modifications**
- Fix add_model_artifact error for NLP models
- Add model_info validation during add_model
### 1.5.2
- #### **Modifications**
- Adds fix for self signed certificate not working by adding verify param to FiddlerApi
### 1.5.1
- #### **Modifications**
- Fix in `violation_of_type` to include numpy dtypes such as `int64`
### 1.5.0
- #### **New Features**
- New methods addition for alert rules: `add_alert_rule`, `get_alert_rules`, `delete_alert_rule`
- New method to get triggered alerts for an alert rule: `get_triggered_alerts`
### 1.4.5
- #### **Modifications**
- Assert nullable columns in `missing_value_encodings`(If users send non-nullable columns as `missing_value_encodings`, Fiddler converts them as nullable automatically with a warning)
### 1.4.4
- #### **Modifications**
- Allow types other than `Column data_type` for `missing_value_encodings`.
### 1.4.3
- #### **Modifications**
- Accept `string` `'inf'` in `float` columns in `missing_value_encodings`.
### 1.4.2
- #### **New Features**
- Support `missing_value_encodings` as a new field of `model_info` object.
### 1.4.1
- #### **Modifications**
- Minor bug fix to handle string nan
### 1.4.0
- #### **Modifications**
- Default client initiation is now the v2 client
- `publish_events_batch` is now async, returns status id and doesn't wait for the upload to complete.
- Default behavior of all publish data in v2 client is async (`is_sync = False`)
### 1.3.0
- #### **New Features**
- New capabilities for Artifact-less Monitoring
### 1.2.8
- ### **Modifications**
- Change the `batch_size` argument default to 1000 for `trigger_pre_computation`
- Updated the `delete_model` API default value for the `delete_prod` parameter from False to True.
- We will by default delete all the events associated with the model.
### 1.2.7
- ### **Modifications**
- Added check for "model" key before access in from_dict
- Allow changing artifact_status when updating the model
- Adds docstrings for add_model, add_model_surrogate and add_model_artifact
### 1.2.6
- ### **Modifications**
- Fixed publish_events_batch_schema backward compatible.
### 1.2.5
- ### **Modifications**
- Added add_model_surrogate and add_model_artifact APIs for artifactless monitoring
- Simplifies the add_model API by removing unnecessary parameters
- Fixed publish_events_batch_schema parameter names.
### 1.2.4
- ### **Modifications**
- Fixed a type coercion bug that caused some get_slice calls to fail cryptically
### 1.2.3
- ### **Modifications**
- Map Tree shap values from log odds space to probability space
- Added add_model API for artifactless monitoring
- Fixed bug in request when creating a model using add_model
### 1.2.2
- ### **Modifications**
- Fixed a bug that prevented importing the client in some environments.
### 1.2.1
- ### **Modifications**
- Removed unnecessary server-client version check that produced an uninformative warning.
### 1.2.0
- #### **New Features**
- New `WeightingParams` object. This enables weighted histograms for class-imbalanced models.
- #### **Modifications**
- `update_model` allows some small modifications in model info for the following fields: custom_explanation_names, preferred_explanation_method, display_name, description, framework, algorithm and model_deployment_params
### 1.1.0
- #### **New Features**
- Add v2 client. v2 methods can be accessed either via sub-module (`client.v2.`) or by instantiating the `FiddlerApi` and passing `version=2`.
- #### **Modifications**
- Remove handlers from root logger
- Add url, org_id, auth_token and version validation while instantiating client
- Fix dataset ingestion file extension issue
- init monitoring issue
- Fix publish_event request header bug
- Add `publish_events_batch_dataframe` and `upload_dataset_dataframe` methods
- Support for DatasetInfo class
- Using `http_client` package. A wrapper over `requetsts`.
### 1.0.6
- #### **Modifications**
- Add client v2 sub-package.
### 1.0.5
- ##### **Modifications**
- relax the version requirements for `requests`.
- adds flag to init_monitoring to enable synchronous initialization
### 1.0.4
- ##### **Modifications**
- Fixed the JSON transformation issue which was forcing `requests` package upgrade issue
### 1.0.3
- ##### **New Features**
- Tree SHAP Helper.
- ##### **Modifications**
- `fdl.ModelInfo` has an additional optional parameter to enabled Tree Shap
### 1.0.2
- ##### **New Features**
- Integrated Gradients Keras TF2 Helpers.
- ##### **Modifications**
- Relax `botocore` version requirements.
### 1.0.1
- ##### **Modifications**
- Minor bug fixes and improvements.
- `run_explanation` has two additional optional arguments (`n_permutation` and `n_background`) allowing users to change the default parameters for Fiddler SHAP explanations.
### 1.0.0
Inaugural client for Fiddler 22.0! This version includes numerous improvements for stability, performance, and usability.
Compatible with server versions >=22.0.0.
### 0.8.1.8
- ##### **Modifications**
- Minor bug fixes and improvements.
### 0.8.1.7
- ##### **Modifications**
- Minor bug fixes and improvements.
### 0.8.1.6
- ##### **Modifications**
- Add a parameter in list_projects API to get detailed project information
- Minor bug fix for the datetime format.
### 0.8.1.5
- ##### **Modifications**
- Add a parameter in list_projects API to get detailed project information
- Allow `run_explanation` api call to pass a list of explanation with `ig_flex` and one of the shap algorithm
### 0.8.1.4
- ##### **Modifications**
- Minor bugfix for categorical feature drift
### 0.8.1.3
- ##### **Modifications**
- Addressed an issue with categorical features with string literals containing numeric content
### 0.8.1.2
- ##### **Modifications**
- Implement a ranking surrogate model for ranking task models
### 0.8.1.1
- ##### **Modifications**
- change the dependecy of requests package to 0.25.1
### 0.8.1
- ##### **Modifications**
- Improved `SegmentInfo` validation.
- make the dependency versions less strict.
### 0.8.0
- ##### **New Features**
- New `publish_events_batch_schema` API call, Publishes a batch events object to Fiddler Service using the passed `publish_schema` as a template.
- New Ranking Monitoring capability available with publish_events_batch API
- ##### **Modifications**
- Enforced package versions in setup.py
- `trigger_pre_computation` has an additional optional argument (`cache_dataset`) to enable/disable dataset histograms caching.
- `register_model` has 3 additional optional arguments to enable/disable pdp caching (set to False by default), feature importance caching (set to True by default) and dataset histograms caching (set to True by default).
### 0.7.6
- ##### **New Features**
- New segment monitoring related functionality (currently in preview):
- Ability to create and validate `SegmentInfo` objects,
- `upload_segment` BE call,
- `activate_segment` BE call,
- `deactivate_segment` BE call, and
- `list_segments` BE call,
- ##### **Modifications**
- Upon connecting to the server, the client now performs a version check for the *server* by default. Earlier the default was to only do a version check for the client.
### 0.7.5
- ##### **New Features**
- New `update_event` parameter for `publish_events_batch` API.
- Changes to `fdl.publish_event()`:
- Renamed parameter `event_time_stamp` to `event_timestamp`
- Added new parameter: `timestamp_format`
- Allows specification of timestamp format using the `FiddlerTimestamp` class
### 0.7.4
- ##### **New Features**
- New `initialize_monitoring` API call, sets up monitoring for a model. Intended to also work retroactively for legacy schema.
- ##### **Modifications**
- Modified `DatasetInfo.from_dataframe` and `ModelInfo.from_dataset_info` to take additional `dataset_id` as parameter.
- Modified the `outputs` parameter of `ModelInfo.from_dataset_info` to now expect a dictionary in case of regression tasks, specifying output range.
- Modified the `preferred_explanation_method` parameter of `ModelInfo.from_dataset_info` to accept string names from `custom_explanation_names`. Details in docstring.
- Misc bug fixes and documentation enhancements.
### 0.7.3
- ##### **New Features**
- Changed the default display for `ModelInfo` and `DatasetInfo` to render HTML instead of plaintext, when accessed via jupyter notebooks
- Added support for GCP Storage ingestion of log events using `fdl.BatchPublishType.GCP_STORAGE`
### 0.7.2
- ##### **New Features**
- Restructured the following arguments for `fdl.ModelInfo.from_dataset_info()`
- Added: `categorical_target_class_details`:
- Mandatory for Multiclass classification tasks, optional for Binary (unused for Regression)
- Used to specify the positive class for Binary classification, and the class order for Multiclass classification
- Modified: `target`:
- No longer optional, models must specify target columns
### 0.7.1
- ##### **New Features**
- Restructured the following arguments for `fdl.publish_events_batch()`
- Added: `id_field`:
- Column to extract `id` value from
- Added: `timestamp_format`:
- Format of timestamp within batch object. Can be one of:
- `fdl.FiddlerTimestamp.INFER`
- `fdl.FiddlerTimestamp.EPOCH_MILLISECONDS`
- `fdl.FiddlerTimestamp.EPOCH_SECONDS`
- `fdl.FiddlerTimestamp.ISO_8601`
Removed: `default_timestamp`
- Minor bug fixes
- ##### **Deprecation Warning**
- Support `fdl.publish_events_log` and `fdl.publish_parquet_s3` will soon be
deprecated in favor of `fdl.publish_events_batch()`
### 0.7.0
- ##### **Dataset Refactor**
- Datasets refactored to be members of a Project
- *This is a change promoting Datasets to be first class within Fiddler. It will affects both the UI and several API in Fiddler*
- Many API utilizing Projects will now require `project_id` passed as a parameter
- ##### **New Features**
- Added `fdl.update_model()` to client
- *update the specified model, with model binary and package.py from
the specified model_dir*
- Added `fdl.get_model()` to client
- *download the model binary, package.py and model.yaml to the given
output dir.*
- Added `fdl.publish_events_batch()` to client
- *Publishes a batch events object to Fiddler Service.*
- *Note: Support for other batch methods including `fdl.publish_events_log()`
and `fdl.publish_parquet_s3()` will be deprecated in the near future
in favor of `fdl.publish_events_batch()`*
- ##### **Changes**
- Simplified logic within `fld.upload-dataset()`
- Added client/server handshake for checking version compatibilities
- *Warning issued in case of mismatch*
- Deleted redundant APIs
- `fdl.create_surrogate_model()`
- `fdl.upload_model_sklearn()`
- Restructured APIs to be more duck typing-friendly (relaxing data type restrictions)
- Patches for minor bug-fixes
### 0.6.18
- ##### **Features**
- Minor updates to ease use of binary classification labels
### 0.6.17
- ##### **Features**
- Added new arguments to `ModelInfo.from_dataset_info()`
- `preferred_explanation_method` to express a preferred default explanation algorithm for a model
- `custom_explanation_names` to support user-provided explanation algorithms which the user will implement on their model object via package.py.
### 0.6.16
- ##### **Features**
- Minor improvements to `publish_events_log()` to circumvent datatype conversion issues
### 0.6.15
- ##### **Features**
- Added strict name checks
### 0.6.14
- ##### **Features**
- Added client-native multithreading support for `publish_events_log()`
using new parameters `num_threads` and `batch_size`
### 0.6.13
- ##### **Features**
- Added `fdl.generate_sample_events()` to client
- *API for generating monitoring traffic to test out Fiddler*
- Added `fdl.trigger_pre_computation()` to client
- *Triggers various precomputation steps within the Fiddler service based on input parameters.*
- Optionally add proxies to FiddlerApi() init
### 0.6.12
- ##### **Features**
- Added `fdl.publish_parquet_s3()` to client
- *Publishes parquet events file from S3 to Fiddler instance.
Experimental and may be expanded in the future.*
### 0.6.10
- ##### **Features**
- Added `fdl.register_model()` to client
- *Register a model in fiddler. This will generate a surrogate model,
which can be replaced later with original model.*
نیازمندی
| مقدار | نام |
|---|---|
| - | Werkzeug |
| - | boto3 |
| - | deepdiff |
| ==1.2.13 | deprecated |
| ==2.1.0 | deprecation |
| - | fastavro |
| - | importlib-resources |
| - | packaging |
| <=1.5.3,>=1.2.5 | pandas |
| >=21.0 | pip |
| >=3.0.0 | pyarrow |
| >=1.9.0 | pydantic |
| - | pyyaml |
| - | requests-toolbelt |
| <3 | requests |
| <3,>=2 | semver |
| ==4.64.1 | tqdm |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >3.6.3 | Python |
نحوه نصب
نصب پکیج whl fiddler-client-2.0.0.dev1:
pip install fiddler-client-2.0.0.dev1.whl
نصب پکیج tar.gz fiddler-client-2.0.0.dev1:
pip install fiddler-client-2.0.0.dev1.tar.gz