1.3.12

What's Changed

• [FEATURE]: excessive logs remove by @IvanildoBarauna in #66
• chore(deps-dev): bump pylint from 3.3.0 to 3.3.1 by @dependabot in #67
• chore(deps-dev): bump coverage from 7.6.1 to 7.6.3 by @dependabot in #69
• chore(deps-dev): bump black from 24.8.0 to 24.10.0 by @dependabot in #68
• chore(deps-dev): bump coverage from 7.6.3 to 7.6.4 by @dependabot in #70
• chore: Added Change Log by @IvanildoBarauna in #71
• chore(deps-dev): bump coverage from 7.6.4 to 7.6.7 by @dependabot in #72
• dependabot consolidate by @IvanildoBarauna in #76
• chore(deps-dev): bump coverage from 7.6.7 to 7.6.8 by @dependabot in #73
• chore(deps-dev): bump pytest from 8.3.3 to 8.3.4 by @dependabot in #74
• chore(deps-dev): bump pylint from 3.3.1 to 3.3.2 by @dependabot in #75
• POC - Improvement Observability sending metrics to DataDog

Full Changelog: 1.3.11...1.3.12

1.3.11

What's Changed

• feature: added max of retries for protect APIServer by @IvanildoBarauna in #60
• chore(deps-dev): bump pytest from 8.3.2 to 8.3.3 by @dependabot in #62
• chore(deps-dev): bump poetry-dynamic-versioning from 1.4.0 to 1.4.1 by @dependabot in #63
• chore(deps-dev): bump pylint from 3.2.6 to 3.3.0 by @dependabot in #64

Full Changelog: 1.3.10...1.3.11

1.3.10

Whats new?

• Quantity retries limited for 5 for protect API Server
• Improve documentation for better experience and undestand when use Retry Strategies.

Full Changelog: https://github.com/IvanildoBarauna/api-to-dataframe/compare/1.3.9...1.3.10

Kind Regargs
Ivanildo Barauna

1.3.4

What's Changed

• chore(deps-dev): bump pylint from 3.2.5 to 3.2.6 by @dependabot in https://github.com/IvanildoBarauna/api-to-dataframe/pull/55
• chore: Enviroment PROD and Devel Setups

Full Changelog: https://github.com/IvanildoBarauna/api-to-dataframe/compare/1.3.3...1.3.4

1.3.3

What's Changed

• chore(deps-dev): bump pytest from 8.2.2 to 8.3.1 by @dependabot in https://github.com/IvanildoBarauna/api-to-dataframe/pull/54

Full Changelog: https://github.com/IvanildoBarauna/api-to-dataframe/compare/1.3.2...1.3.3

[HOTFIX] Custom Logger Level

Whats New?

• Custom Logger fixed for correct level lob exibition
• More performance onC Library

Update NOW and enjoy!

Kind Regards,
Ivanildo Barauna

Production Version on AIR

Whats new?

• Implemented logger
• Implemented custom log messages in critical points of application
• Black Formatted
• Pylint Conventions

[NEWS] Evolute to 4. Beta version in Pypi

What's Changed

• chore: Update Notebook by @IvanildoBarauna in https://github.com/IvanildoBarauna/api-to-dataframe/pull/45
• feat Improves by @IvanildoBarauna in https://github.com/IvanildoBarauna/api-to-dataframe/pull/47

Full Changelog: https://github.com/IvanildoBarauna/api-to-dataframe/compare/1.2.1...1.2.3

Update Documentation and Improve Dev XP

• Rename param delay to intial_delay
• Refact tests

Retry Strategies Avaliable

A new version 1.2.1 of api-to-dataframe is LIVE
We are happy to announce another version of the solution you need to be more productive in your developments that involves API consumption to generate DataFrames.

Now Scientists, Data Engineers, Data Analysts and all other professionals who need to obtain API data and create dataframes can use RETRY STRATEGIES.

Retry Strategies is a feature that allows you to define a Retry strategy in case your GET operation fails. We don't want that to happen, but if it does, we're here to try again in a safe way.

There are two ways to do this, you can use a Linear Strategy which by default makes 3 retries, waiting 1 second each time, or use an Exponential Strategy which doubles the waiting time with each new connection attempt, to protect the servers from APIs you consume. It is worth remembering that all parameters have default values, but can be changed according to your needs.

We hope you enjoy this new feature,

In addition, we have evolved the package to version 3. Alpha, we are one step away from evolving into a beta version, so any feedback/questions are welcome here.
For details on how to implement your Retry strategies, access our README and also this notebook which contains examples of how to do this in a simple way.

Kind Regards,
Ivanildo Barauna