A Python wrapper to Haver Analytics' RESTful API.
Project description
haver
The haver library provides a convenient wrapper to Haver Analytics' RESTful API.
Installation
pip install haver
How to
Connection and Authentication
from haver import Haver
haver = Haver(api_key='<your-haver-API-token>')
The class Haver
also accepts keyword arguments to be passed to requests,
which handles the connection to the API under the hood. In this way,
by passing e.g. verify
and proxy
parameters, users can access Haver databases from behind firewalls.
For example:
haver = Haver(api_key='<your-haver-API-key>',
verify=False, # Or local path to certificates
proxies={'http': 'http://proxy-username:proxy-password@proxy-server.com:8080',
'https': 'http://proxy-username:proxy-password@proxy-server.com:8080'})
Instead of passing the API key explicitely each time,
the user can also set an environmental variable HAVER_TOKEN
containing the API key.
In this case connection will be as simple as
haver = Haver()
.
Obtaining your API Key
You can find your API key at this link.
Exploring available resources
All available databases can easily be listed as
haver.get_databases()
which will return a dictionary with keys the database names and values the corresponding database description:
{'UNPOP': 'U.N. Population Statistics',
'EPFRECA': 'Fund Country Allocations',
'EUFIN': 'Financial Data',
...
}
Further information on each dataset can be obtained via the method haver.database_info
,
and series within each database can be listed e.g. as
haver.get_series(database='UNPOP', full_info=True)
In addition, a search function is also available to allow the user to search series by their descriptions, for example as:
haver.search(query='employment')
Querying data
In order to retrieve data, the user has the option of querying one series at a time via the dedicated method
haver.read(database='EUDATA', series='N997CE')
which returns data in dictionary format, or querying multiple series as
haver.read_df(haver_codes=['N997CE@EUDATA','N025CE@EUDATA'])
where individual haver_codes
are created by joining series and database names as {series}@{database}
.
Finally, a database of available recessions can be obtained as
haver.recessions()
Author
Luca Mingarelli, 2024
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file haver-0.3.0.tar.gz
.
File metadata
- Download URL: haver-0.3.0.tar.gz
- Upload date:
- Size: 17.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 07862f471b398392432678f02ed8bdc8bed2bccb5da2b7f6c6c6ec9437291d67 |
|
MD5 | 6df77576abdc473c86c7fa1d67da7ab5 |
|
BLAKE2b-256 | 6ec4e6a7892eb1cbbef15a9d3ed0285fa6d3f0e752a6e6e0d634f319806184d6 |
File details
Details for the file haver-0.3.0-py3-none-any.whl
.
File metadata
- Download URL: haver-0.3.0-py3-none-any.whl
- Upload date:
- Size: 16.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 581bf4f963323ddcb5d998b366278a4970bed861ab88c958896fdeb4ddbf2819 |
|
MD5 | e2267391132f47f6ea5b7f2eeb5e1b23 |
|
BLAKE2b-256 | 52cfa484f2394eac51c9a1a2c6237ef771e6100091ed58e1bef36d2e6a1c83a9 |