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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

Topics

Resources

Stars

0 stars

Watchers

0 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

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Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

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Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

Topics

Resources

Stars

0 stars

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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closecity

This is the Python software development kit for the Close.City API. It returns travel times from every US census block to nearby places, on foot, by bike, and by public transit. The data behind close.city is served over the Close API.

Documentation:https://henryspatialanalysis.github.io/closecity-python/

Install

pip install closecity
pip install "closecity[tiger]"# to auto-download census-block boundaries

This pulls in httpx, pandas, and geopandas, so results come back as data frames out of the box: a GeoDataFrame where geometry applies, a plain DataFrame otherwise.

A first call

You make requests through a client. Routes with geometry come back as GeoDataFrames, so you can map them right away.

fromclosecityimportClient, close_map# The key (ck_live_) comes from https://account.close.city (5,000 free tokens# on signup, no card). You can also set the CLOSECITY_KEY environment variable# and call Client() with no argument.close=Client("ck_live_your_key") # use your own key here# Supermarkets within a 1.5 km walk of a point (type 30 is grocery stores):supermarkets=close.pois_search(lat=41.823, lon=-71.412, radius_m=1500, type=30)
close_map(supermarkets, color="#e8590c") # interactive map, bright hoverable points

Catalog and lookup routes are free, need no key, and come back as data frames:

close=Client()
close.modes() # walk, bike, transitclose.places("Providence") # a city name to its GEOID and centre

Key terms

A few terms come up throughout the API:

  • Census block. The smallest area the Census Bureau publishes. Each one has a 15-digit id called a GEOID.
  • Destination type. A category of place, such as grocery stores or libraries. Each type has a numeric id. Look them up with close.destination_types().
  • Mode. How someone travels: walk, bike, or transit.
  • Isochrone or catchment: the area you can reach starting from a point within a time limit, by a selected travel mode.

Choose an output

Set output on the client, or per call:

  • output = "spatial" (the default) returns a GeoDataFrame for inherently spatial data and a DataFrame otherwise. Block routes join census-block boundaries with pygris (the tiger extra), downloaded once and cached.
  • output = "tabular" returns a plain DataFrame for every route and never downloads boundaries. Reach for it when you only want the numbers.
  • output = "raw" returns the underlying Reply / Paginator, with the parsed body on .data and the token counts alongside.
close=Client("ck_live_your_key", output="raw") # use your own key hereforpoiinclose.pois_search(lat=41.823, lon=-71.412, radius_m=1500):
print(poi["name"])

Handling errors

Problem responses become typed exceptions. Catch a specific one, or the CloseAPIError base.

fromclosecityimportTokensExhaustedError, CloseAPIErrortry:
close.block_summary("000000000000000")
exceptTokensExhaustedError:
...
exceptCloseAPIErroraserr:
print(err.status, err.slug)

The client does not retry automatically. On a RateLimitedError or ServiceUnavailableError, wait err.retry_after seconds (from the Retry-After header) and retry the request yourself.

Reference

Development

pip install -e '.[dev]'
pytest # unit tests, no network (httpx MockTransport)
ruff check src tests

About

Python client for the Close API: walking, cycling, and public transit travel times from every US census block to nearby amenities

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages