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DOC: Standardize start, end and limit descriptions
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README.md

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@@ -12,17 +12,17 @@ Key features include:
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- 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).
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- [Multiple schemas](https://docs.databento.com/knowledge-base/new-users/market-data-schemas?historical=python&live=python) such as MBO, MBP, top of book, OHLCV, last sale, and more.
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- [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.
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- Provides mappings between different symbology systems, including [smart symbology](https://docs.databento.com/reference-historical/basics/symbology?historical=python&live=python) for futures rollovers.
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- Provides mappings between different symbology systems, including [smart symbology](https://docs.databento.com/api-reference-historical/basics/symbology?historical=python&live=python) for futures rollovers.
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- [Point-in-time]() instrument definitions, free of look-ahead bias and retroactive adjustments.
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- Reads and stores market data in an extremely efficient file format using [Databento Binary Encoding](https://docs.databento.com/knowledge-base/new-users/dbn-encoding?historical=python&live=python).
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- Event-driven [market replay](https://docs.databento.com/reference-historical/helpers/bento-replay?historical=python&live=python), including at high-frequency order book granularity.
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- Event-driven [market replay](https://docs.databento.com/api-reference-historical/helpers/bento-replay?historical=python&live=python), including at high-frequency order book granularity.
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- Support for [batch download](https://docs.databento.com/knowledge-base/new-users/stream-vs-batch?historical=python&live=python) of flat files.
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- Support for [pandas](https://pandas.pydata.org/docs/), CSV, and JSON.
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## Documentation
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The best place to begin is with our [Getting started](https://docs.databento.com/getting-started?historical=python&live=python) guide.
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You can find our full client API reference on the [Historical Reference](https://docs.databento.com/reference-historical?historical=python&live=python) and
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You can find our full client API reference on the [Historical Reference](https://docs.databento.com/api-reference-historical?historical=python&live=python) and
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[Live Reference](https://docs.databento.com/reference-live?historical=python&live=python) sections of our documentation. See also the
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[Examples](https://docs.databento.com/examples?historical=python&live=python) section for various tutorials and code samples.
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databento/historical/api/batch.py

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@@ -103,7 +103,7 @@ def submit_job(
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stype_out : SType or str, default 'product_id'
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The output symbology type to resolve to.
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limit : int, optional
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The maximum number of records for the request. If `None` then no limit.
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The maximum number of records to return. If `None` then no limit.
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Returns
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-------

databento/historical/api/metadata.py

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@@ -313,8 +313,7 @@ def get_record_count(
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stype_in : SType or str, default 'native'
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The input symbology type to resolve from.
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limit : int, optional
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The maximum number of records to include in the query.
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If `None` then no limit.
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The maximum number of records to return. If `None` then no limit.
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Returns
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-------
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stype_in : SType or str, default 'native'
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The input symbology type to resolve from.
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limit : int, optional
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The maximum number of records to include in the query. If `None` then no limit.
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The maximum number of records to return. If `None` then no limit.
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Returns
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-------
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stype_in : SType or str, default 'native'
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The input symbology type to resolve from.
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limit : int, optional
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The maximum number of records to include in the query. If `None` then no limit.
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The maximum number of records to return. If `None` then no limit.
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Returns
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-------

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