Skip to main content

Python module containing system_verilog files for CV32E41P cpu.

Project description

pythondata-cpu-cv32e41p

Non-Python files needed for the cpu cv32e41p packaged into a Python module so they can be used with Python libraries and tools.

This is useful for usage with tools like LiteX.

The data files can be found under the Python module pythondata_cpu_cv32e41p. The pythondata_cpu_cv32e41p.data_location value can be used to find the files on the file system.

Example of getting the data file directly;

import pythondata_cpu_cv32e41p

my_data_file = "abc.txt"

with open(os.path.join(pythondata_cpu_cv32e41p.data_location, my_data_file)) as f:
    print(f.read())

Example of getting the data file using litex.data.find API;

from pythondata_cpu_cv32e41p import data_file

my_data_file = "abc.txt"

with open(data_file(my_data_file)) as f:
    print(f.read())

The data files come from https://github.com/openhwgroup/cv32e41p and are imported using git subtrees to the directory pythondata_cpu_cv32e41p/system_verilog.

Installing

Directly from git repository

Manually

You can install the package manually, however this is not recommended.

git clone https://github.com/litex-hub/pythondata-cpu-cv32e41p.git
cd pythondata-cpu-cv32e41p
sudo python setup.py install

Using pip with git repository

You can use pip to install the data package directly from github using;

pip install --user git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git

If you want to install for the whole system rather than just the current user, you need to remove the --user argument and run as sudo like so;

sudo pip install git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git

You can install a specific revision of the repository using;

pip install --user git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git@<tag>
pip install --user git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git@<branch>
pip install --user git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git@<hash>

With requirements.txt file

Add to your Python requirements.txt file using;

-e git+https://github.com/litex-hub/pythondata-cpu-cv32e41p.git

To use a specific revision of the repository, use the following;

-e https://github.com/litex-hub/pythondata-cpu-cv32e41p.git@<hash>

Via PyPi

Using pip

pip install --user pythondata-cpu-cv32e41p

With requirements.txt file

Add to your Python requirements.txt file using;

pythondata-cpu-cv32e41p

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

pythondata-cpu-cv32e41p-0.0.post1858.tar.gz (939.3 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file pythondata-cpu-cv32e41p-0.0.post1858.tar.gz.

File metadata

  • Download URL: pythondata-cpu-cv32e41p-0.0.post1858.tar.gz
  • Upload date:
  • Size: 939.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for pythondata-cpu-cv32e41p-0.0.post1858.tar.gz
Algorithm Hash digest
SHA256 264263bd8cbf7bf533ab92af8780969acb39ea9339247b3ac0fc615395622083
MD5 bc61c00e9dfe2a11a88cc8dec7af8758
BLAKE2b-256 059c3792a46c8f6f5112d2f77400441fa46d614ccb2e3962fe2eba0efa87eb64

See more details on using hashes here.

File details

Details for the file pythondata_cpu_cv32e41p-0.0.post1858-py3-none-any.whl.

File metadata

  • Download URL: pythondata_cpu_cv32e41p-0.0.post1858-py3-none-any.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for pythondata_cpu_cv32e41p-0.0.post1858-py3-none-any.whl
Algorithm Hash digest
SHA256 9ec1bd7367980c3931b67090cd8b20f76417bfab75c19c8041dd9dbee66cd555
MD5 8d4ce0757cc271ec207eb47d3179f3a5
BLAKE2b-256 1621e43fa77b6a0211db231fa66ea5175e909134e820af04dd2a2f6d3865637a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page