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databento-0.9.0
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Official Python client library for Databento
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | databento-0.9.0 |
| نام | databento |
| نسخه کتابخانه | 0.9.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Databento |
| ایمیل نویسنده | support@databento.com |
| آدرس صفحه اصلی | https://github.com/databento/databento-python |
| آدرس اینترنتی | https://pypi.org/project/databento/ |
| مجوز | Apache License 2.0 |
# databento-python
[](https://github.com/databento/databento-python/actions/workflows/test.yml)
[](https://pypi.org/project/databento)
[](./LICENSE)
[](https://github.com/psf/black)
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://docs.databento.com/knowledge-base/new-users/venues-and-publishers?historical=python&live=python).
- [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.
- [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/api-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://docs.databento.com/knowledge-base/new-users/dbn-encoding?historical=python&live=python).
- 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.
- Support for [batch download](https://docs.databento.com/knowledge-base/new-users/stream-vs-batch?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/api-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://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)
- databento-dbn (==0.5.0)
- numpy (>=1.17.0)
- pandas (>=1.1.3)
- requests (>=2.24.0)
- zstandard (>=0.20.0)
## Installation
To install the latest stable version of the package from PyPI:
pip install -U databento
## Usage
The library needs to be configured with an API key from your account.
[Sign up](https://databento.com/signup) for free and you will automatically
receive a set of API keys to start with. Each API key is a 32-character
string starting with `db-`, that can be found on the API Keys page of your [Databento user portal](https://databento.com/platform/keys).
A simple Databento application looks like this:
```python
import databento as db
client = db.Historical('YOUR_API_KEY')
data = client.timeseries.get_range(
dataset='GLBX.MDP3',
symbols='ES.FUT',
stype_in='smart',
start='2022-06-10T14:30',
end='2022-06-10T14:40',
)
data.replay(callback=print) # market replay, with `print` as event handler
```
Replace `YOUR_API_KEY` with an actual API key, then run this program.
This uses `.replay()` to access the entire block of data
and dispatch each data event to an event handler. You can also use
`.to_df()` or `.to_ndarray()` to cast the data into a Pandas `DataFrame` or numpy `ndarray`:
```python
df = data.to_df(pretty_ts=True, pretty_px=True) # to DataFrame, with pretty formatting
array = data.to_ndarray() # to ndarray
```
Note that the API key was also passed as a parameter, which is
[not recommended for production applications](https://docs.databento.com/knowledge-base/new-users/security-managing-api-keys?historical=python&live=python).
Instead, you can leave out this parameter to pass your API key via the `DATABENTO_API_KEY` environment variable:
```python
import databento as db
# Pass as parameter
client = db.Historical('YOUR_API_KEY')
# Or, pass as `DATABENTO_API_KEY` environment variable
client = db.Historical()
```
## License
Distributed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0.html).
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl databento-0.9.0:
pip install databento-0.9.0.whl
نصب پکیج tar.gz databento-0.9.0:
pip install databento-0.9.0.tar.gz