Initial commit

README.md

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+# Static Space
+
+Heavily WIP.

app.py

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+from datetime import datetime, timedelta
+import json
+from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
+from urllib.parse import parse_qs, urlparse
+
+from huggingface_hub import list_datasets
+from datasets import load_dataset
+import numpy as np
+
+
+def running_mean(x, N, total_length=-1):
+    cumsum = np.cumsum(np.insert(x, 0, 0))
+    to_pad = max(total_length - len(cumsum), 0)
+    return np.pad(cumsum[N:] - cumsum[:-N], (to_pad, 0)) / float(N)
+
+
+class RequestHandler(SimpleHTTPRequestHandler):
+    def do_GET(self):
+        print(self.path)
+        if self.path == "/":
+            self.path = "index.html"
+
+            return SimpleHTTPRequestHandler.do_GET(self)
+
+        if self.path.startswith("/initialize"):
+            metrics_datasets = [d.id.split('/')[1] for d in list_datasets(author='open-source-metrics', use_auth_token=True)]
+            pip_installs_datasets = [d.split('-')[0] for d in metrics_datasets if 'pip' in d]
+
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+
+            self.wfile.write(json.dumps(pip_installs_datasets).encode("utf-8"))
+
+            return SimpleHTTPRequestHandler
+
+        if self.path.startswith("/retrievePipInstalls"):
+            url = urlparse(self.path)
+            query = parse_qs(url.query)
+            library_names = query.get("input", None)[0]
+            library_names = library_names.split(',')
+
+            returned_values = {}
+            for library_name in library_names:
+                dataset = load_dataset(f"open-source-metrics/{library_name}-pip-installs", use_auth_token=True)['train']
+                for i in dataset:
+                    if i['day'] in returned_values:
+                        returned_values[i['day']][library_name] = i['num_downloads']
+                    else:
+                        returned_values[i['day']] = {library_name: i['num_downloads']}
+
+            for library_name in library_names:
+                for i in returned_values.keys():
+                    if library_name not in returned_values[i]:
+                        returned_values[i][library_name] = 0
+
+            output = {l: [k[l] for k in returned_values.values()][::-1] for l in library_names}
+            output['day'] = list(returned_values.keys())[::-1]
+
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+
+            self.wfile.write(json.dumps(output).encode("utf-8"))
+
+            return SimpleHTTPRequestHandler
+
+        if self.path.startswith("/retrieveStars"):
+            url = urlparse(self.path)
+            query = parse_qs(url.query)
+            library_names = query.get("input", None)[0]
+            library_names = library_names.split(',')
+
+            returned_values = {}
+            dataset_dict = load_dataset(f"open-source-metrics/stars", use_auth_token=True, revision='90cb31b2db73c8c4291bcf317d831595e4fb2a91').sort('dates')
+
+            for library_name in library_names:
+                dataset = dataset_dict[library_name]
+                n = 0
+                for i in dataset:
+                    n += 1
+                    if i['dates'] in returned_values:
+                        returned_values[i['dates']][library_name] = n
+                    else:
+                        returned_values[i['dates']] = {library_name: n}
+
+            for library_name in library_names:
+                for i in returned_values.keys():
+                    if library_name not in returned_values[i]:
+                        returned_values[i][library_name] = None
+
+            output = {l: [k[l] for k in returned_values.values()][::-1] for l in library_names}
+            output['day'] = list(returned_values.keys())[::-1]
+
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+
+            self.wfile.write(json.dumps(output).encode("utf-8"))
+
+            return SimpleHTTPRequestHandler
+
+        return SimpleHTTPRequestHandler.do_GET(self)
+
+
+server = ThreadingHTTPServer(("", 7860), RequestHandler)
+
+print("Running on port 7860")
+server.serve_forever()

index.html

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+<!DOCTYPE html>
+<html lang="en">
+    <head>
+        <title>OSS Metrics</title>
+        <link rel="stylesheet" href="style.css" />
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/3.9.1/chart.min.js"></script>
+        <script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns/dist/chartjs-adapter-date-fns.bundle.min.js"></script>
+        <script type="module" src="index.js"></script>
+    </head>
+
+    <body>
+        <div id="loading"></div>
+        <div class="graphs">
+            <div id="library-selector"></div>
+            <div id="graph-selector"></div>
+        </div>
+        <canvas id="pip-graph"></canvas>
+        <canvas id="star-graph"></canvas>
+    </body>
+</html>

index.js

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+if (document.location.search.includes('dark-theme=true')) {
+    document.body.classList.add('dark-theme');
+}
+
+const load = () => {
+    const l0 = document.createElement('div')
+    const l1 = document.createElement('div')
+    const l2 = document.createElement('div')
+    l0.classList.add('lds-ripple')
+
+    l0.appendChild(l1)
+    l0.appendChild(l2)
+    return l0
+}
+
+let charts = [];
+
+const createButton = (title, libraries, methods) => {
+    const button = document.createElement('button')
+    button.textContent = title;
+    button.onclick = async () => {
+        document.getElementById('pip-graph').innerHTML = ''
+        document.getElementById('star-graph').innerHTML = ''
+        const e = load()
+        document.body.appendChild(e)
+        const selectedLibraries = libraries.filter(e => document.querySelector(`#${e}Checkbox`).checked);
+        if (charts.length !== 0) {
+            for (const chart of charts) {
+                chart.destroy()
+            }
+        }
+        for (const method of methods()) {
+            charts.push(await method(selectedLibraries))
+        }
+        document.body.removeChild(e)
+    };
+
+    return button;
+}
+
+const initialize = async () => {
+    const inferResponse = await fetch(`initialize`);
+    const inferJson = await inferResponse.json();
+    const graphsDiv = document.getElementsByClassName('graphs')[0];
+    const librarySelector = document.getElementById('library-selector');
+    const graphSelector = document.getElementById('graph-selector');
+
+    const introSpan = document.createElement("h3")
+    introSpan.textContent = "Select libraries to display"
+    librarySelector.appendChild(introSpan);
+
+    const graphSpan = document.createElement("h3")
+    graphSpan.textContent = "Select graphs to display"
+    graphSelector.appendChild(graphSpan);
+
+    for (const element of inferJson) {
+        const div = document.createElement('div');
+        const checkBox = document.createElement('input');
+        checkBox.type = 'checkbox'
+        checkBox.id = `${element}Checkbox`;
+
+        const checkBoxLabel = document.createElement('label');
+        checkBoxLabel.textContent = element.charAt(0).toUpperCase() + element.slice(1)
+
+        checkBoxLabel.appendChild(checkBox)
+        div.appendChild(checkBoxLabel)
+
+        librarySelector.appendChild(div)
+    }
+
+    for (const element of ['pip', 'stars']) {
+        const div = document.createElement('div');
+        const checkBox = document.createElement('input');
+        checkBox.type = 'checkbox'
+        checkBox.id = `${element}CheckboxGraph`;
+
+        const checkBoxLabel = document.createElement('label');
+        checkBoxLabel.textContent = element.charAt(0).toUpperCase() + element.slice(1)
+
+        checkBoxLabel.appendChild(checkBox)
+        div.appendChild(checkBoxLabel)
+
+        graphSelector.appendChild(div)
+    }
+
+    const fetchButton = createButton('Fetch', inferJson, () => {
+        const graphNames = ['pip', 'stars'].filter(e => document.querySelector(`#${e}CheckboxGraph`).checked);
+        const graphs = []
+
+        if (graphNames.includes('pip'))
+            graphs.push(retrievePipInstalls)
+
+        if (graphNames.includes('stars'))
+            graphs.push(retrieveStars)
+
+        return graphs
+    })
+    graphsDiv.appendChild(fetchButton);
+};
+
+const retrievePipInstalls = async (libraryNames) => {
+    const inferResponse = await fetch(`retrievePipInstalls?input=${libraryNames}`);
+    const inferJson = await inferResponse.json();
+    const colors = ['Lilac', 'Red', 'Blue', 'Orange', 'Green']
+
+    console.log(inferJson)
+    const labels = Array.from(inferJson['day']).map(e => new Date(e))
+    const datasets = [];
+    for (const element in inferJson) {
+        if (element === 'day')
+            continue
+
+        const color = colors.pop()
+        datasets.push({
+            label: element,
+            data: inferJson[element],
+            backgroundColor: color,
+            borderColor: color,
+            tension: 0.01,
+            pointRadius: 1,
+            borderWidth: 2,
+            fill: false
+        })
+    }
+
+    const ctx = document.getElementById('pip-graph');
+
+    const myChart = new Chart(ctx, {
+        type: 'line',
+        data: {labels, datasets},
+        options: {
+            scales: {
+                y: {
+                    beginAtZero: true
+                },
+                x: {
+                    type: 'time',
+                }
+            },
+        }
+    });
+    return myChart;
+};
+
+const retrieveStars = async (libraryNames) => {
+    const inferResponse = await fetch(`retrieveStars?input=${libraryNames}`);
+    const inferJson = await inferResponse.json();
+    const colors = ['Lilac', 'Red', 'Blue', 'Orange', 'Green']
+
+    const labels = Array.from(inferJson['day']).map(e => new Date(e))
+    const datasets = [];
+    for (const element in inferJson) {
+        if (element === 'day')
+            continue
+
+        const color = colors.pop()
+        datasets.push({
+            label: element,
+            data: inferJson[element],
+            backgroundColor: color,
+            borderColor: color,
+            tension: 0.01,
+            pointRadius: 1,
+            borderWidth: 2,
+            fill: false
+        })
+    }
+
+    const ctx = document.getElementById('star-graph');
+
+    const myChart = new Chart(ctx, {
+        type: 'line',
+        data: {labels, datasets},
+        options: {
+            scales: {
+                y: {
+                    beginAtZero: true
+                },
+                x: {
+                    type: 'time',
+                }
+            },
+        }
+    });
+    return myChart;
+};
+
+(
+    async () => {
+        const e = load()
+        document.body.appendChild(e)
+        await initialize()
+        document.body.removeChild(e)
+    }
+)();

python-app/bootstrap_dataset.py

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+# Script to bootstrap a dataset
+# Bootstraping a dataset requires first running an SQL script in BigQuery and downloading the json.
+# A dataset will then be created on the Hub with the initial data. This script will go step-by-step over the creation.
+
+import os
+import sys
+from pathlib import Path
+from datasets import Dataset
+from huggingface_hub import dataset_info
+
+# Define the library name you'd like to work on.
+from huggingface_hub.utils import RepositoryNotFoundError
+
+library_name = input("Library name: ")
+current_dir = Path(__file__).parent
+
+if f"{library_name}.csv" not in os.listdir(current_dir / 'csv_files'):
+    query = Path(current_dir / 'query.sql').read_text().replace("<PROJECT_NAME>", library_name)
+
+    print("Open the following link: https://console.cloud.google.com/bigquery?project=huggingface-ml\n")
+    print(f"Run the following query:\n\n{query}\n\n")
+    print("Press paste the results here (Ctrl+D once pasted): ")
+    csv_values = sys.stdin.read()
+
+    Path(current_dir / f'csv_files/{library_name}.csv').write_text(csv_values)
+
+try:
+    dataset_info(f'open-source-metrics/{library_name}-pip-installs')
+    dataset_exists = True
+except RepositoryNotFoundError:
+    dataset_exists = False
+
+dataset = Dataset.from_csv(str(current_dir / f'csv_files/{library_name}.csv'), delimiter='\t')
+dataset.push_to_hub(f'open-source-metrics/{library_name}-pip-installs', private=True)
+print("Dataset is pushed to Hub.")

python-app/csv_files/accelerate.csv

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+num_downloads	day
+2977	2022-08-04
+5776	2022-08-03
+6482	2022-08-02
+7032	2022-08-01
+2740	2022-07-31
+2806	2022-07-30
+5266	2022-07-29
+6563	2022-07-28
+7116	2022-07-27
+6171	2022-07-26
+5593	2022-07-25
+2367	2022-07-24
+2845	2022-07-23
+4827	2022-07-22
+4592	2022-07-21
+6426	2022-07-20
+6025	2022-07-19
+5396	2022-07-18
+2382	2022-07-17
+2621	2022-07-16
+4585	2022-07-15
+4767	2022-07-14
+5019	2022-07-13
+4820	2022-07-12
+4380	2022-07-11
+2524	2022-07-10
+1994	2022-07-09
+3965	2022-07-08
+4574	2022-07-07
+4858	2022-07-06
+4776	2022-07-05
+4247	2022-07-04
+2364	2022-07-03
+2346	2022-07-02
+4103	2022-07-01
+3996	2022-06-30
+4695	2022-06-29
+4589	2022-06-28
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+1767	2022-06-26
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python-app/csv_files/datasets.csv

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python-app/graphql.py

@@ -0,0 +1,130 @@
+import json
+
+import requests
+
+counter = 0
+
+class Query:
+    name: str
+    mutations: ()
+    schema = ""
+    url = "https://api.github.com/graphql"
+    headers = {
+        "Accept": "application/json",
+        "Authorization": "Bearer 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",
+        "Accept-Encoding": "gzip, deflate, br",
+        "Content-Type": "application/json",
+        "Connection": "keep-alive",
+        "DNT": '1',
+        "Origin": "file://"
+    }
+
+    def __init__(self, name):
+        self.name = name
+        self.schema = f"query {name}" + "{ <NEXT_VAL> }"
+        self.path = []
+        self.to_save = []
+        self.to_iter = []
+
+    def mutation(self, _name, **kwargs):
+        args = []
+        for k, v in kwargs.items():
+            if isinstance(v, str):
+                args.append(f'{k}: \"{v}\"')
+            else:
+                args.append(f'{k}: {v}')
+
+        args = ', '.join(args)
+
+        if len(args):
+            args = f'({args})'
+
+        self.schema = self.schema.replace('<NEXT_VAL>', f"{_name}{args}" + "{ <NEXT_VAL> }")
+        self.path += [_name]
+        return self
+
+    def iter(self, _name):
+        self.path += [_name]
+        to_replace = f"{_name} (<ITER {self.path}>)" + "{ totalCount pageInfo { endCursor hasNextPage} <NEXT_VAL> }"
+        self.schema = self.schema.replace('<NEXT_VAL>', to_replace)
+        self.to_iter.append([*self.path])
+        return self
+
+    def save_result(self, _name):
+        self.schema = self.schema.replace('<NEXT_VAL>', f"{_name} <NEXT_VAL>")
+        self.to_save.append([*self.path, _name])
+        return self
+
+    @property
+    def nodes(self):
+        self.path.append('nodes')
+        self.schema = self.schema.replace('<NEXT_VAL>', 'nodes { <NEXT_VAL> }')
+        return self
+
+    def end_of_page(self, previous, iterable):
+        if previous is None:
+            return False
+
+        for selector in iterable:
+            previous = previous[selector]
+
+        return previous['pageInfo']['hasNextPage']
+
+    def recursive_iterable(self, schema, iterables):
+        if len(iterables) > 0:
+            iterable = iterables[0]
+            iterables = iterables[1:]
+        else:
+            return
+
+        output = None
+        while not self.end_of_page(output, iterable):
+            if output is None:
+                index = f'first: 20'
+            else:
+                index = f'after: {output}'
+
+            new_schema = schema.replace(f'<ITER {str(iterable)}>', index)
+
+            if 'ITER' not in new_schema:
+                print('new schema', new_schema)
+                res = requests.post(self.url, headers=self.headers, json={'query': new_schema})
+                output = res.json()['data']
+
+            out = self.recursive_iterable(new_schema, iterables)
+            print('output', out)
+
+            return output
+
+    def call(self):
+        schema = self.schema.replace('<NEXT_VAL>', '')
+        self.recursive_iterable(schema, self.to_iter)
+
+        # print(self.schema.replace('<NEXT_VAL>', ''))
+        # print('will save', self.to_save)
+        # print('will iterate over', self.to_iter)
+        # # res = requests.post(self.url, headers=self.headers, json={'query': self.schema.replace('<NEXT_VAL>', '')})
+        # # output = res.json()['data']
+        # output = json.loads('{"repository": {"nameWithOwner": "huggingface/transformers", "issues": {"totalCount": 9843, "pageInfo": {"endCursor": "Y3Vyc29yOnYyOpHOFwK_Mw==", "hasNextPage": true}, "nodes": [{"number": 3}, {"number": 5}, {"number": 6}, {"number": 9}, {"number": 10}, {"number": 11}, {"number": 12}, {"number": 13}, {"number": 15}, {"number": 19}, {"number": 20}, {"number": 23}, {"number": 24}, {"number": 25}, {"number": 26}, {"number": 27}, {"number": 28}, {"number": 30}, {"number": 31}, {"number": 33}, {"number": 34}, {"number": 35}, {"number": 36}, {"number": 37}, {"number": 38}, {"number": 39}, {"number": 41}, {"number": 43}, {"number": 44}, {"number": 45}, {"number": 46}, {"number": 47}, {"number": 48}, {"number": 49}, {"number": 50}, {"number": 51}, {"number": 52}, {"number": 53}, {"number": 54}, {"number": 55}, {"number": 56}, {"number": 57}, {"number": 59}, {"number": 61}, {"number": 62}, {"number": 63}, {"number": 64}, {"number": 65}, {"number": 67}, {"number": 68}]}}}')
+        #
+        # for iterable in self.to_iter[::-1]:
+        #     for selector in iterable:
+        #         output = output[selector]
+        #
+        #     page_info = output['pageInfo']
+        #
+        #     print('pageInfo', page_info)
+        #     # if page_info['hasNextPage']:
+        #
+        # return output
+
+
+query = Query('GetRepository')
+query.mutation('repository', owner='huggingface', name='transformers')
+query.save_result('nameWithOwner')
+
+query.iter('issues').nodes.save_result('number')
+query.mutation('comments', first=100).nodes.mutation('reactions')
+query.save_result('totalCount')
+
+print(query.call())

python-app/query.sql

@@ -0,0 +1,12 @@
+#standardSQL
+SELECT
+  COUNT(*) AS num_downloads,
+  DATE_TRUNC(DATE(timestamp), DAY) AS `day`
+FROM `bigquery-public-data.pypi.file_downloads`
+WHERE
+  file.project = '<PROJECT_NAME>'
+  AND DATE(timestamp)
+    BETWEEN DATE_TRUNC(DATE_SUB(CURRENT_DATE(), INTERVAL 18 MONTH), MONTH)
+    AND CURRENT_DATE()
+GROUP BY `day`
+ORDER BY `day` DESC

python-app/reactions.py

@@ -0,0 +1,21 @@
+query = """
+query GetRepository {
+  repository(owner: "huggingface", name: "transformers"){
+    nameWithOwner
+    issues (first: 50){
+      totalCount
+      nodes {
+        number
+        comments (first: 10) {
+          totalCount
+          nodes {
+            reactions (first: 10) {
+              totalCount
+            }
+          }
+        }
+      }
+    }
+  }
+}
+"""

python-app/requirements.txt

@@ -0,0 +1,2 @@
+datasets
+pypistats

python-app/update_metrics.py

@@ -0,0 +1,34 @@
+import pypistats
+from huggingface_hub import list_datasets
+from datasets import load_dataset, concatenate_datasets, Dataset
+
+def update_pip_installs():
+    metrics_datasets = [d.id for d in list_datasets(author='open-source-metrics', use_auth_token=True)]
+    pip_installs_datasets = [d for d in metrics_datasets if 'pip' in d]
+
+    for dataset_name in pip_installs_datasets:
+        dataset = load_dataset(dataset_name, use_auth_token=True)
+        library_name = dataset.split('/')[1].split('-')[0]
+        data = pypistats.overall(library_name, total=True, format="pandas")
+        data = data.groupby("category").get_group("without_mirrors").sort_values("date")
+
+        data.drop('category', axis=1, inplace=True)
+        data.drop('percent', axis=1, inplace=True)
+
+        pypistats_dataset = Dataset.from_pandas(data)
+        pypistats_dataset.rename_column('downloads', 'num_downloads')
+        pypistats_dataset.rename_column('date', 'day')
+
+        column_names = pypistats_dataset.column_names
+        column_names.remove('num_downloads')
+        column_names.remove('day')
+
+        pypistats_dataset.remove_columns(column_names)
+
+        days = pypistats_dataset['day']
+
+
+
+
+
+update_pip_installs()

style.css

@@ -0,0 +1,84 @@
+html {
+    /*color: white;*/
+    /*background-color: rgb(50, 50, 50);*/
+    font-family: Source Sans Pro,ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,Segoe UI,Roboto,Helvetica Neue,Arial,Noto Sans,sans-serif,Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol,Noto Color Emoji;
+    line-height: 1.5;
+}
+
+body {
+    display: flex;
+    align-items: center;
+    flex-direction: column;
+}
+
+button {
+    width: 100%;
+    height: 40px;
+    margin-top: 20px;
+    cursor: pointer;
+    background: none;
+    border: 2px solid black;
+    /*color: white;*/
+    transition: all 0.2s ease;
+}
+
+button:hover {
+    border: 2px solid gray;
+    color: gray;
+    transition: all 0.2s ease;
+}
+
+.graphs {
+    margin: 20px;
+}
+
+.graphs > div {
+    margin: 20px;
+}
+
+.lds-ripple {
+    display: inline-block;
+    position: relative;
+    width: 80px;
+    height: 80px;
+}
+.lds-ripple div {
+    position: absolute;
+    border: 4px solid #000;
+    opacity: 1;
+    border-radius: 50%;
+    animation: lds-ripple 1s cubic-bezier(0, 0.2, 0.8, 1) infinite;
+}
+.lds-ripple div:nth-child(2) {
+    animation-delay: -0.5s;
+}
+@keyframes lds-ripple {
+    0% {
+        top: 36px;
+        left: 36px;
+        width: 0;
+        height: 0;
+        opacity: 0;
+    }
+    4.9% {
+        top: 36px;
+        left: 36px;
+        width: 0;
+        height: 0;
+        opacity: 0;
+    }
+    5% {
+        top: 36px;
+        left: 36px;
+        width: 0;
+        height: 0;
+        opacity: 1;
+    }
+    100% {
+        top: 0px;
+        left: 0px;
+        width: 72px;
+        height: 72px;
+        opacity: 0;
+    }
+}