VER: Upgrade dbz to 0.2.0 across bento

Author: cjdsellers

.github/workflows/test.yml

@@ -12,7 +12,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
     name: build - Python ${{ matrix.python-version }} (${{ matrix.os }})
     runs-on: ${{ matrix.os }}
 

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+## 0.6.0 - 2022-11-29
+- Added `metadata.get_dataset_condition` method to `Historical` client
+- Upgraded `dbz-python` to `0.2.0`
+
 ## 0.5.0 - 2022-11-07
  - Fixed dataframe columns for derived data schemas (dropped `channel_id`)
  - Fixed `batch.submit_job` requests for `dbz` encoding

README.md

@@ -9,29 +9,29 @@
 The official Python client library for [Databento](https://databento.com).
 
 Key features include:
-- Fast, lightweight access to both live and historical data from [multiple markets](https://docs0.databento.com/knowledge-base/new-users/venues-and-publishers?historical=python&live=python).
-- [Multiple schemas](https://docs0.databento.com/knowledge-base/new-users/list-of-supported-market-data-schemas?historical=python&live=python) such as MBO, MBP, top of book, OHLCV, last sale, and more.
-- [Fully normalized](https://docs0.databento.com/knowledge-base/new-users/normalization?historical=python&live=python), i.e. identical message schemas for both live and historical data, across multiple asset classes.
-- Provides mappings between different symbology systems, including [smart symbology](https://docs0.databento.com/reference-historical/basics/symbology?historical=python&live=python) for futures rollovers.
+- Fast, lightweight access to both live and historical data from [multiple markets](https://docs.databento.com/knowledge-base/new-users/venues-and-publishers?historical=python&live=python).
+- [Multiple schemas](https://docs.databento.com/knowledge-base/new-users/list-of-supported-market-data-schemas?historical=python&live=python) such as MBO, MBP, top of book, OHLCV, last sale, and more.
+- [Fully normalized](https://docs.databento.com/knowledge-base/new-users/normalization?historical=python&live=python), i.e. identical message schemas for both live and historical data, across multiple asset classes.
+- Provides mappings between different symbology systems, including [smart symbology](https://docs.databento.com/reference-historical/basics/symbology?historical=python&live=python) for futures rollovers.
 - [Point-in-time]() instrument definitions, free of look-ahead bias and retroactive adjustments.
-- Reads and stores market data in an extremely efficient file format using [Databento Binary Encoding](https://docs0.databento.com/knowledge-base/new-users/dbz-format?historical=python&live=python).
-- Event-driven [market replay](https://docs0.databento.com/reference-historical/helpers/bento-replay?historical=python&live=python), including at high-frequency order book granularity.
-- Support for [batch download](https://docs0.databento.com/knowledge-base/new-users/historical-data-streaming-vs-batch-download?historical=python&live=python) of flat files.
+- Reads and stores market data in an extremely efficient file format using [Databento Binary Encoding](https://docs.databento.com/knowledge-base/new-users/dbz-format?historical=python&live=python).
+- Event-driven [market replay](https://docs.databento.com/reference-historical/helpers/bento-replay?historical=python&live=python), including at high-frequency order book granularity.
+- Support for [batch download](https://docs.databento.com/knowledge-base/new-users/historical-data-streaming-vs-batch-download?historical=python&live=python) of flat files.
 - Support for [pandas](https://pandas.pydata.org/docs/), CSV, and JSON.
 
 ## Documentation
 The best place to begin is with our [Getting started](https://docs.databento.com/getting-started?historical=python&live=python) guide.
 
 You can find our full client API reference on the [Historical Reference](https://docs.databento.com/reference-historical?historical=python&live=python) and
 [Live Reference](https://docs.databento.com/reference-live?historical=python&live=python) sections of our documentation. See also the
-[Examples](https://docs0.databento.com/examples?historical=python&live=python) section for various tutorials and code samples.
+[Examples](https://docs.databento.com/examples?historical=python&live=python) section for various tutorials and code samples.
 
 ## Requirements
 The library is fully compatible with the latest distribution of Anaconda 3.7 and above.
 The minimum dependencies as found in the `requirements.txt` are also listed below:
 - Python (>=3.7)
 - aiohttp (>=3.7.2)
-- dbz-python (>=0.1.5)
+- dbz-python (>=0.2.0)
 - numpy (>=1.17.0)
 - pandas (>=1.1.3)
 - requests (>=2.24.0)

requirements.txt

@@ -1,5 +1,5 @@
 aiohttp>=3.7.2
-dbz-python>=0.1.5
+dbz-python>=0.2.0
 numpy>=1.17.0
 pandas>=1.1.3
 requests>=2.24.0