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@@ -1 +1 @@-gzip compressed data, was "cbhist-0.0.1.tar", last modified: Mon May 13 18:04:05 2024, max compression+gzip compressed data, was "cbhist-0.0.2.tar", last modified: Wed May 29 21:33:21 2024, max compression
@@ -1,22 +1,22 @@
Metadata-Version: 2.1
Name: cbhist
-Version: 0.0.1+Version: 0.0.2
Summary: A python library for pulling in historical candles from coinbase.
Home-page: https://github.com/8W9aG/cbhist
Author: Will Sackfield
Author-email: [email protected]
License: MIT
Keywords: coinbase history historical price candle
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests>=2.31.0
-Requires-Dist: pandas>=2.2.2+Requires-Dist: pandas>=2.2.1
Requires-Dist: tqdm>=4.66.4
Requires-Dist: tenacity>=8.3.0
# cbhist
<a href="https://pypi.org/project/cbhist/">
<img alt="PyPi" src="https://img.shields.io/pypi/v/cbhist">
@@ -41,15 +41,15 @@
This is a python package hosted on pypi, so to install simply run the following command:
`pip install cbhist`
## Usage example :eyes:
-To pull a dataframe containing all the information for a particular league, the following example can be used:+To pull a dataframe containing all the candles for a coinbase product:
```python
import datetime
from cbhist.historical import fetch_historical
granularity = 60 # Candle for every minute
html2text {}
@@ -1,14 +1,14 @@-Metadata-Version: 2.1 Name: cbhist Version: 0.0.1 Summary: A python library for+Metadata-Version: 2.1 Name: cbhist Version: 0.0.2 Summary: A python library for
pulling in historical candles from coinbase. Home-page: https://github.com/
8W9aG/cbhist Author: Will Sackfield Author-email: [email protected]
License: MIT Keywords: coinbase history historical price candle Classifier:
License :: OSI Approved :: MIT License Classifier: Programming Language ::
Python :: 3 Description-Content-Type: text/markdown License-File: LICENSE
-Requires-Dist: requests>=2.31.0 Requires-Dist: pandas>=2.2.2 Requires-Dist:+Requires-Dist: requests>=2.31.0 Requires-Dist: pandas>=2.2.1 Requires-Dist:
tqdm>=4.66.4 Requires-Dist: tenacity>=8.3.0 # cbhist _�[_�P_�y_�P_�i_�]A python library for
pulling in historical candles from coinbase. ## Dependencies :
globe_with_meridians: Python 3.11.6: - [pandas](https://pandas.pydata.org/) -
[requests](https://requests.readthedocs.io/en/latest/) - [tqdm](https://
github.com/tqdm/tqdm) - [tenacity](https://tenacity.readthedocs.io/en/latest/
) ## Raison D'être :thought_balloon: The [coinbase exchange API](https://
docs.cloud.coinbase.com/exchange/reference/exchangerestapi_getproductcandles)
@@ -17,14 +17,13 @@
Typically the approach is to iterate across a time series and perform a request
for each time chunk, however this can be sped up greatly by doing a binary
search before doing an iterative pull to determine when the asset begins to
have candles. Formalising this into a proper library produces a dataframe made
it easier to work in different projects than re-inventing the wheel each time.
## Installation :inbox_tray: This is a python package hosted on pypi, so to
install simply run the following command: `pip install cbhist` ## Usage example
-:eyes: To pull a dataframe containing all the information for a particular-league, the following example can be used: ```python import datetime from-cbhist.historical import fetch_historical granularity = 60 # Candle for every-minute df = fetch_coinbase("ETH-USD", granularity, datetime.datetime(2010, 1,-1)) ``` This results in a dataframe with a datetime index and OHLC (+ volume)-columns. ## License :memo: The project is available under the [MIT License]-(LICENSE).+:eyes: To pull a dataframe containing all the candles for a coinbase product:+```python import datetime from cbhist.historical import fetch_historical+granularity = 60 # Candle for every minute df = fetch_coinbase("ETH-USD",+granularity, datetime.datetime(2010, 1, 1)) ``` This results in a dataframe+with a datetime index and OHLC (+ volume) columns. ## License :memo: The+project is available under the [MIT License](LICENSE).
@@ -23,15 +23,15 @@
This is a python package hosted on pypi, so to install simply run the following command:
`pip install cbhist`
## Usage example :eyes:
-To pull a dataframe containing all the information for a particular league, the following example can be used:+To pull a dataframe containing all the candles for a coinbase product:
```python
import datetime
from cbhist.historical import fetch_historical
granularity = 60 # Candle for every minute
html2text {}
@@ -10,13 +10,13 @@
across a time series and perform a request for each time chunk, however this
can be sped up greatly by doing a binary search before doing an iterative pull
to determine when the asset begins to have candles. Formalising this into a
proper library produces a dataframe made it easier to work in different
projects than re-inventing the wheel each time. ## Installation :inbox_tray:
This is a python package hosted on pypi, so to install simply run the following
command: `pip install cbhist` ## Usage example :eyes: To pull a dataframe
-containing all the information for a particular league, the following example-can be used: ```python import datetime from cbhist.historical import-fetch_historical granularity = 60 # Candle for every minute df = fetch_coinbase-("ETH-USD", granularity, datetime.datetime(2010, 1, 1)) ``` This results in a-dataframe with a datetime index and OHLC (+ volume) columns. ## License :memo:-The project is available under the [MIT License](LICENSE).+containing all the candles for a coinbase product: ```python import datetime+from cbhist.historical import fetch_historical granularity = 60 # Candle for+every minute df = fetch_coinbase("ETH-USD", granularity, datetime.datetime+(2010, 1, 1)) ``` This results in a dataframe with a datetime index and OHLC (++volume) columns. ## License :memo: The project is available under the [MIT+License](LICENSE).
@@ -1,22 +1,22 @@
Metadata-Version: 2.1
Name: cbhist
-Version: 0.0.1+Version: 0.0.2
Summary: A python library for pulling in historical candles from coinbase.
Home-page: https://github.com/8W9aG/cbhist
Author: Will Sackfield
Author-email: [email protected]
License: MIT
Keywords: coinbase history historical price candle
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests>=2.31.0
-Requires-Dist: pandas>=2.2.2+Requires-Dist: pandas>=2.2.1
Requires-Dist: tqdm>=4.66.4
Requires-Dist: tenacity>=8.3.0
# cbhist
<a href="https://pypi.org/project/cbhist/">
<img alt="PyPi" src="https://img.shields.io/pypi/v/cbhist">
@@ -41,15 +41,15 @@
This is a python package hosted on pypi, so to install simply run the following command:
`pip install cbhist`
## Usage example :eyes:
-To pull a dataframe containing all the information for a particular league, the following example can be used:+To pull a dataframe containing all the candles for a coinbase product:
```python
import datetime
from cbhist.historical import fetch_historical
granularity = 60 # Candle for every minute
html2text {}
@@ -1,14 +1,14 @@-Metadata-Version: 2.1 Name: cbhist Version: 0.0.1 Summary: A python library for+Metadata-Version: 2.1 Name: cbhist Version: 0.0.2 Summary: A python library for
pulling in historical candles from coinbase. Home-page: https://github.com/
8W9aG/cbhist Author: Will Sackfield Author-email: [email protected]
License: MIT Keywords: coinbase history historical price candle Classifier:
License :: OSI Approved :: MIT License Classifier: Programming Language ::
Python :: 3 Description-Content-Type: text/markdown License-File: LICENSE
-Requires-Dist: requests>=2.31.0 Requires-Dist: pandas>=2.2.2 Requires-Dist:+Requires-Dist: requests>=2.31.0 Requires-Dist: pandas>=2.2.1 Requires-Dist:
tqdm>=4.66.4 Requires-Dist: tenacity>=8.3.0 # cbhist _�[_�P_�y_�P_�i_�]A python library for
pulling in historical candles from coinbase. ## Dependencies :
globe_with_meridians: Python 3.11.6: - [pandas](https://pandas.pydata.org/) -
[requests](https://requests.readthedocs.io/en/latest/) - [tqdm](https://
github.com/tqdm/tqdm) - [tenacity](https://tenacity.readthedocs.io/en/latest/
) ## Raison D'être :thought_balloon: The [coinbase exchange API](https://
docs.cloud.coinbase.com/exchange/reference/exchangerestapi_getproductcandles)
@@ -17,14 +17,13 @@
Typically the approach is to iterate across a time series and perform a request
for each time chunk, however this can be sped up greatly by doing a binary
search before doing an iterative pull to determine when the asset begins to
have candles. Formalising this into a proper library produces a dataframe made
it easier to work in different projects than re-inventing the wheel each time.
## Installation :inbox_tray: This is a python package hosted on pypi, so to
install simply run the following command: `pip install cbhist` ## Usage example
-:eyes: To pull a dataframe containing all the information for a particular-league, the following example can be used: ```python import datetime from-cbhist.historical import fetch_historical granularity = 60 # Candle for every-minute df = fetch_coinbase("ETH-USD", granularity, datetime.datetime(2010, 1,-1)) ``` This results in a dataframe with a datetime index and OHLC (+ volume)-columns. ## License :memo: The project is available under the [MIT License]-(LICENSE).+:eyes: To pull a dataframe containing all the candles for a coinbase product:+```python import datetime from cbhist.historical import fetch_historical+granularity = 60 # Candle for every minute df = fetch_coinbase("ETH-USD",+granularity, datetime.datetime(2010, 1, 1)) ``` This results in a dataframe+with a datetime index and OHLC (+ volume) columns. ## License :memo: The+project is available under the [MIT License](LICENSE).
@@ -19,15 +19,15 @@
if not x.startswith(".") and not x.startswith("-e")
]
return requires
setup(
name='cbhist',
- version='0.0.1',+ version='0.0.2',
description='A python library for pulling in historical candles from coinbase.',
long_description=long_description,
long_description_content_type='text/markdown',
classifiers=[
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
],