metadata

configs:
  - config_name: default
    data_files: spaces.csv
license: other
language:
  - code
size_categories:
  - 100K<n<1M

📊 Dataset Description

This dataset comprises code files of Huggingface Spaces that have more than 0 likes as of November 10, 2023. This dataset contains various programming languages totaling in 672 MB of compressed and 2.05 GB of uncompressed data.

📝 Data Fields

Field	Type	Description
repository	string	Huggingface Spaces repository names.
sdk	string	Software Development Kit of the space.
license	string	License type of the space.

🧩 Data Structure

Data structure of the data.

spaces/
├─ author1/
│  ├─ space1
│  ├─ space2
├─ author2/
│  ├─ space1
│  ├─ space2
│  ├─ space3

🏛️ Licenses

Huggingface Spaces contains a variety of licenses. Here is the list of the licenses that this dataset contains:

[
   'None',
   'mit',
   'apache-2.0',
   'openrail',
   'gpl-3.0',
   'other',
   'afl-3.0',
   'unknown',
   'creativeml-openrail-m',
   'cc-by-nc-4.0',
   'cc-by-4.0',
   'cc',
   'cc-by-nc-sa-4.0',
   'bigscience-openrail-m',
   'bsd-3-clause',
   'agpl-3.0',
   'wtfpl',
   'gpl',
   'artistic-2.0',
   'lgpl-3.0',
   'cc-by-sa-4.0',
   'Configuration error',
   'bsd',
   'cc-by-nc-nd-4.0',
   'cc0-1.0',
   'unlicense',
   'llama2',
   'bigscience-bloom-rail-1.0',
   'gpl-2.0',
   'bsd-2-clause',
   'osl-3.0',
   'cc-by-2.0',
   'cc-by-3.0',
   'cc-by-nc-3.0',
   'cc-by-nc-2.0',
   'cc-by-nd-4.0',
   'openrail++',
   'bigcode-openrail-m',
   'bsd-3-clause-clear',
   'eupl-1.1',
   'cc-by-sa-3.0',
   'mpl-2.0',
   'c-uda',
   'gfdl',
   'cc-by-nc-sa-2.0',
   'cc-by-2.5',
   'bsl-1.0',
   'odc-by',
   'deepfloyd-if-license',
   'ms-pl',
   'ecl-2.0',
   'pddl',
   'ofl-1.1',
   'lgpl-2.1',
   'postgresql',
   'lppl-1.3c',
   'ncsa',
   'cc-by-nc-sa-3.0'
]

📊 Dataset Statistics

Language	File Extension	File Counts	File Size (MB)	Line Counts
Python	.py	141,560	1079.0	28,653,744
SQL	.sql	21	523.6	645
JavaScript	.js	6,790	369.8	2,137,054
Markdown	.md	63,237	273.4	3,110,443
HTML	.html	1,953	265.8	516,020
C	.c	1,320	132.2	3,558,826
Go	.go	429	46.3	6,331
CSS	.css	3,097	25.6	386,334
C Header	.h	2,824	20.4	570,948
C++	.cpp	1,117	15.3	494,939
TypeScript	.ts	4,158	14.8	439,551
TSX	.tsx	4,273	9.4	306,416
Shell	.sh	3,294	5.5	171,943
Perl	.pm	92	4.2	128,594
C#	.cs	22	3.9	41,265

🖥️ Language

📁 Size

📝 Line Count

🤗 Huggingface Spaces Statistics

🛠️ Software Development Kit (SDK)

Software Development Kit pie chart.

🏛️ License

License chart.

📅 Dataset Creation

This dataset was created in these steps:

Scraped all spaces using the Huggingface Hub API.

from huggingface_hub import HfApi
api = HfApi()

spaces = api.list_spaces(sort="likes", full=1, direction=-1)

Filtered spaces with more than 0 likes.

a = {}

for i in tqdm(spaces):
  i = i.__dict__
  if i['likes'] > 0:
    try:
      try:
          a[i['id']] = {'sdk': i['sdk'], 'license': i['cardData']['license'], 'likes': i['likes']}
      except KeyError:
        a[i['id']] = {'sdk': i['sdk'], 'license': None, 'likes': i['likes']}
    except:
      a[i['id']] = {'sdk': "Configuration error", 'license': "Configuration error", 'likes': i['likes']}

data_list = [{'repository': key, 'sdk': value['sdk'], 'license': value['license'], 'likes': value['likes']} for key, value in a.items()]

df = pd.DataFrame(data_list)

Cloned spaces locally.

from huggingface_hub import snapshot_download

programming = ['.asm', '.bat', '.cmd', '.c', '.h', '.cs', '.cpp', '.hpp', '.c++', '.h++', '.cc', '.hh', '.C', '.H', '.cmake', '.css', '.dockerfile', 'Dockerfile', '.f90', '.f', '.f03', '.f08', '.f77', '.f95', '.for', '.fpp', '.go', '.hs', '.html', '.java', '.js', '.jl', '.lua', 'Makefile', '.md', '.markdown', '.php', '.php3', '.php4', '.php5', '.phps', '.phpt', '.pl', '.pm', '.pod', '.perl', '.ps1', '.psd1', '.psm1', '.py', '.rb', '.rs', '.sql', '.scala', '.sh', '.bash', '.command', '.zsh', '.ts', '.tsx', '.tex', '.vb']
pattern = [f"*{i}" for i in programming]

for i in repos:
  snapshot_download(i, repo_type="space", local_dir=f"spaces/{i}", allow_patterns=pattern)

Processed the data to derive statistics.