Repository: censusdis/censusdis (language: python)

Issue:
Getting SSL Error when downloading the data. Can we use certificate_file and api_key in the censusdis functions?
# Introduction
I am following the instructions from getting started tutorial: https://censusdis.readthedocs.io/en/latest/intro.html.

When I run the code I get the SSL Error.

# Code
```python
import censusdis.data as ced

# American Community Survey 5-Year Data
# https://www.census.gov/data/developers/data-sets/acs-5year.html
DATASET = "acs/acs5"

# The year we want data for.
YEAR = 2020

# This are the census variables for total population and median household income.
# For more details, see
#
#     https://api.census.gov/data/2020/acs/acs5/variables.html,
#     https://api.census.gov/data/2020/acs/acs5/variables/B01003_001E.html, and
#     https://api.census.gov/data/2020/acs/acs5/variables/B19013_001E.html.
#
TOTAL_POPULATION_VARIABLE = "B01003_001E"
MEDIAN_HOUSEHOLD_INCOME_VARIABLE = "B19013_001E"

# The variables we are going to query.
VARIABLES = ["NAME", TOTAL_POPULATION_VARIABLE, MEDIAN_HOUSEHOLD_INCOME_VARIABLE]

# Get the value of our variables for every state in the
# year we have chosen.
df_states = ced.download(
    DATASET,
    YEAR,
    VARIABLES,
    state="*",
)

```

# Question: Can we pass certificate file path to avoid SSL error?
```python
df_states = ced.download(
    DATASET,
    YEAR,
    VARIABLES,
    state="*",
  cert_file = my_certificate_file.pem # ** Can we do similar to this?
)
```

# Question: Placing of census api key
Can we put the api_key.txt anywhere or it must be in .census/api_key.txt ?

# Attempt 1: Monkey patch requests.get code
```
library file: ~/venv/myenv/Lib/site-packages/censusdis/geography.py
change: request = requests.get(url,verify=False)
```

# I can use requests to download NAME.html file, but the error says check that
```python
import requests

url = "https://api.census.gov/data/2022/acs/acs5/variables/NAME.html"

# download the certificate and place inside folder .census
resp = requests.get(url,verify='.census/api_census_gov.crt')
print(resp.text[:100])
```

# Error
```
C:\Users\a126291\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings
  warnings.warn(
---------------------------------------------------------------------------
SSLCertVerificationError                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:467, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    466 try:
--> 467     self._validate_conn(conn)
    468 except (SocketTimeout, BaseSSLError) as e:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:1099, in HTTPSConnectionPool._validate_conn(self, conn)
   1098 if conn.is_closed:
-> 1099     conn.connect()
   1101 # TODO revise this, see https://github.com/urllib3/urllib3/issues/2791

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:653, in HTTPSConnection.connect(self)
    651 server_hostname_rm_dot = server_hostname.rstrip(".")
--> 653 sock_and_verified = _ssl_wrap_socket_and_match_hostname(
    654     sock=sock,
    655     cert_reqs=self.cert_reqs,
    656     ssl_version=self.ssl_version,
    657     ssl_minimum_version=self.ssl_minimum_version,
    658     ssl_maximum_version=self.ssl_maximum_version,
    659     ca_certs=self.ca_certs,
    660     ca_cert_dir=self.ca_cert_dir,
    661     ca_cert_data=self.ca_cert_data,
    662     cert_file=self.cert_file,
    663     key_file=self.key_file,
    664     key_password=self.key_password,
    665     server_hostname=server_hostname_rm_dot,
    666     ssl_context=self.ssl_context,
    667     tls_in_tls=tls_in_tls,
    668     assert_hostname=self.assert_hostname,
    669     assert_fingerprint=self.assert_fingerprint,
    670 )
    671 self.sock = sock_and_verified.socket

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:806, in _ssl_wrap_socket_and_match_hostname(sock, cert_reqs, ssl_version, ssl_minimum_version, ssl_maximum_version, cert_file, key_file, key_password, ca_certs, ca_cert_dir, ca_cert_data, assert_hostname, assert_fingerprint, server_hostname, ssl_context, tls_in_tls)
    804         server_hostname = normalized
--> 806 ssl_sock = ssl_wrap_socket(
    807     sock=sock,
    808     keyfile=key_file,
    809     certfile=cert_file,
    810     key_password=key_password,
    811     ca_certs=ca_certs,
    812     ca_cert_dir=ca_cert_dir,
    813     ca_cert_data=ca_cert_data,
    814     server_hostname=server_hostname,
    815     ssl_context=context,
    816     tls_in_tls=tls_in_tls,
    817 )
    819 try:

File ~\venv\py39darts\lib\site-packages\urllib3\util\ssl_.py:465, in ssl_wrap_socket(sock, keyfile, certfile, cert_reqs, ca_certs, server_hostname, ssl_version, ciphers, ssl_context, ca_cert_dir, key_password, ca_cert_data, tls_in_tls)
    463     pass
--> 465 ssl_sock = _ssl_wrap_socket_impl(sock, context, tls_in_tls, server_hostname)
    466 return ssl_sock

File ~\venv\py39darts\lib\site-packages\urllib3\util\ssl_.py:509, in _ssl_wrap_socket_impl(sock, ssl_context, tls_in_tls, server_hostname)
    507     return SSLTransport(sock, ssl_context, server_hostname)
--> 509 return ssl_context.wrap_socket(sock, server_hostname=server_hostname)

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:501, in SSLContext.wrap_socket(self, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, session)
    495 def wrap_socket(self, sock, server_side=False,
    496                 do_handshake_on_connect=True,
    497                 suppress_ragged_eofs=True,
    498                 server_hostname=None, session=None):
    499     # SSLSocket class handles server_hostname encoding before it calls
    500     # ctx._wrap_socket()
--> 501     return self.sslsocket_class._create(
    502         sock=sock,
    503         server_side=server_side,
    504         do_handshake_on_connect=do_handshake_on_connect,
    505         suppress_ragged_eofs=suppress_ragged_eofs,
    506         server_hostname=server_hostname,
    507         context=self,
    508         session=session
    509     )

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:1041, in SSLSocket._create(cls, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, context, session)
   1040             raise ValueError("do_handshake_on_connect should not be specified for non-blocking sockets")
-> 1041         self.do_handshake()
   1042 except (OSError, ValueError):

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:1310, in SSLSocket.do_handshake(self, block)
   1309         self.settimeout(None)
-> 1310     self._sslobj.do_handshake()
   1311 finally:

SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:793, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    792 # Make the request on the HTTPConnection object
--> 793 response = self._make_request(
    794     conn,
    795     method,
    796     url,
    797     timeout=timeout_obj,
    798     body=body,
    799     headers=headers,
    800     chunked=chunked,
    801     retries=retries,
    802     response_conn=response_conn,
    803     preload_content=preload_content,
    804     decode_content=decode_content,
    805     **response_kw,
    806 )
    808 # Everything went great!

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:491, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    490         new_e = _wrap_proxy_error(new_e, conn.proxy.scheme)
--> 491     raise new_e
    493 # conn.request() calls http.client.*.request, not the method in
    494 # urllib3.request. It also calls makefile (recv) on the socket.

SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)

The above exception was the direct cause of the following exception:

MaxRetryError                             Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\requests\adapters.py:486, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    485 try:
--> 486     resp = conn.urlopen(
    487         method=request.method,
    488         url=url,
    489         body=request.body,
    490         headers=request.headers,
    491         redirect=False,
    492         assert_same_host=False,
    493         preload_content=False,
    494         decode_content=False,
    495         retries=self.max_retries,
    496         timeout=timeout,
    497         chunked=chunked,
    498     )
    500 except (ProtocolError, OSError) as err:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:847, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    845     new_e = ProtocolError("Connection aborted.", new_e)
--> 847 retries = retries.increment(
    848     method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2]
    849 )
    850 retries.sleep()

File ~\venv\py39darts\lib\site-packages\urllib3\util\retry.py:515, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    514     reason = error or ResponseError(cause)
--> 515     raise MaxRetryError(_pool, url, reason) from reason  # type: ignore[arg-type]
    517 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry)

MaxRetryError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2020/acs/acs5/variables/NAME.json (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)')))

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\censusdis\data.py:706, in _prefetch_variable_types(dataset, vintage, download_variables, variable_cache)
    705 try:
--> 706     variable_cache.get(dataset, vintage, variable)
    707 except Exception as exc:

File ~\venv\py39darts\lib\site-packages\censusdis\impl\varcache.py:76, in VariableCache.get(self, dataset, year, name)
     74     return cached_value
---> 76 value = self._variable_source.get(dataset, year, name)
     78 self._variable_cache[dataset][year][name] = value

File ~\venv\py39darts\lib\site-packages\censusdis\impl\varsource\censusapi.py:141, in CensusApiVariableSource.get(self, dataset, year, name)
    140 url = self.url(dataset, year, name)
--> 141 value = json_from_url(url)
    143 return value

File ~\venv\py39darts\lib\site-packages\censusdis\impl\fetch.py:17, in json_from_url(url, params)
     16 """Get json from a URL."""
---> 17 request = requests.get(url, params=params)
     19 if request.status_code == 200:

File ~\venv\py39darts\lib\site-packages\requests\api.py:73, in get(url, params, **kwargs)
     63 r"""Sends a GET request.
     64 
     65 :param url: URL for the new :class:`Request` object.
   (...)
     70 :rtype: requests.Response
     71 """
---> 73 return request("get", url, params=params, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\api.py:59, in request(method, url, **kwargs)
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:703, in Session.send(self, request, **kwargs)
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)

File ~\venv\py39darts\lib\site-packages\requests\adapters.py:517, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    515 if isinstance(e.reason, _SSLError):
    516     # This branch is for urllib3 v1.22 and later.
--> 517     raise SSLError(e, request=request)
    519 raise ConnectionError(e, request=request)

SSLError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2020/acs/acs5/variables/NAME.json (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)')))

The above exception was the direct cause of the following exception:

CensusApiException                        Traceback (most recent call last)
Cell In[5], line 3
      1 # Get the value of our variables for every state in the
      2 # year we have chosen.
----> 3 df_states = ced.download(
      4     DATASET,
      5     YEAR,
      6     VARIABLES,
      7     state="*",
      8 )

File ~\venv\py39darts\lib\site-packages\censusdis\data.py:499, in download(dataset, vintage, download_variables, group, leaves_of_group, set_to_nan, skip_annotations, with_geometry, remove_water, download_contained_within, area_threshold, api_key, variable_cache, row_keys, **kwargs)
    486     return _download_multiple(
    487         dataset,
    488         vintage,
   (...)
    494         **kwargs,
    495     )
    497 # Prefetch all the types before we load the data.
    498 # That way we fail fast if a field is not known.
--> 499 _prefetch_variable_types(dataset, vintage, download_variables, variable_cache)
    500 # Also check that the row_keys, if supplied, are present in the dataset
    501 if row_keys:

File ~\venv\py39darts\lib\site-packages\censusdis\data.py:715, in _prefetch_variable_types(dataset, vintage, download_variables, variable_cache)
    708 census_url = CensusApiVariableSource.url(
    709     dataset, vintage, variable, response_format="html"
    710 )
    711 census_variables_url = CensusApiVariableSource.variables_url(
    712     dataset, vintage, response_format="html"
    713 )
--> 715 raise CensusApiException(
    716     f"Unable to get metadata on the variable {variable} from the "
    717     f"dataset {dataset} for year {vintage} from the census API. "
    718     f"Check the census URL for the variable ({census_url}) to ensure it exists. "
    719     f"If not found, check {census_variables_url} for all variables in the dataset."
    720 ) from exc

CensusApiException: Unable to get metadata on the variable NAME from the dataset acs/acs5 for year 2020 from the census API. Check the census URL for the variable (https://api.census.gov/data/2020/acs/acs5/variables/NAME.html) to ensure it exists. If not found, check https://api.census.gov/data/2020/acs/acs5/variables.html for all variables in the dataset.
```


Discussion / hints:
Answering the second question first: there are three ways to provide your API key:

1. provide it as an argument to `download`, i.e. `ced.download( ..., api_key="MY_API_KEY")`
2. put in in the file `~/.censusdis/api_key.txt` as you were trying to do
3. set it into the environment variable `US_CENSUS_API_KEY`

The code that handles finding it in one of those places is in the class `EnvironmentApiKey` which you can find [here](https://github.com/censusdis/censusdis/blob/f1e9c9357e2774e028eb8aad303189076baa5928/censusdis/geography.py#L294). 

I suppose it is possible to allow it to be some other place that you specify with an optional argument. Is that an important feature for you?

The other trick for when you are just starting out is to not put it in any of those three places. You will still be able to access the server but the total volumne of requests you can make may be limited.
For the other question, if I understand it right, you want to be able to pass an argument to `ced.download` whose value ends up getting passed as the `cert` argument to `requests.get`. If that's right, maybe just calling it `cert` is the right thing to do. And while we are at it, passing `verify` through to `requests.get` seems like a good idea too. Do I have that right?
But I'm also not totally sure why the normal cert from `api.census.gov` is not working for you, forcing you to go down this path. Are you behind a proxy server that is doing something funny with certs?
I am working on office computer and even Python.org website needs verify=False or given certificate. The code requests.get(url) always gives error. I will again test api_key tomorrow and post further comments. Thanks a lot for the quick responses.
**Update**

1. I had commented geography.py file requests.get, now made it original
```python
# from: request = requests.get(url)
# to  : request = requests.get(url,verify=False)

Now, reverted back to original.
```

2. Use API key from ~/.censusdis/api_key.txt
```python
from pathlib import Path

path_api = Path().home() / '.censusdis/api_key.txt'
api_key = path_api.read_text()
print(api_key[:5])
```

3. Use this API key in the code
```python
import censusdis.data as ced
from censusdis.datasets import ACS5
from censusdis import states

df_median_income = ced.download(
    # Data set: American Community Survey 5-Year
    dataset=ACS5,
    # Vintage: 2022
    vintage=2022,
    # Variable: median household income
    download_variables=['NAME', 'B19013_001E'],
    # Geography: All counties in New Jersey.
    state=states.NJ,
    county='*',
    api_key=api_key
)
```

# Note: I can download NAME.html page, but CAN NOT run the code from censusdis
```python
import requests

url = "https://api.census.gov/data/2022/acs/acs5/variables/NAME.html"

resp = requests.get(url,verify=os.path.expanduser('~/.censusdis/api_census_gov.crt'))
print(resp.text[:100]) # this works fine
```

# Error
```
---------------------------------------------------------------------------
SSLCertVerificationError                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:467, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    466 try:
--> 467     self._validate_conn(conn)
    468 except (SocketTimeout, BaseSSLError) as e:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:1099, in HTTPSConnectionPool._validate_conn(self, conn)
   1098 if conn.is_closed:
-> 1099     conn.connect()
   1101 # TODO revise this, see https://github.com/urllib3/urllib3/issues/2791

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:653, in HTTPSConnection.connect(self)
    651 server_hostname_rm_dot = server_hostname.rstrip(".")
--> 653 sock_and_verified = _ssl_wrap_socket_and_match_hostname(
    654     sock=sock,
    655     cert_reqs=self.cert_reqs,
    656     ssl_version=self.ssl_version,
    657     ssl_minimum_version=self.ssl_minimum_version,
    658     ssl_maximum_version=self.ssl_maximum_version,
    659     ca_certs=self.ca_certs,
    660     ca_cert_dir=self.ca_cert_dir,
    661     ca_cert_data=self.ca_cert_data,
    662     cert_file=self.cert_file,
    663     key_file=self.key_file,
    664     key_password=self.key_password,
    665     server_hostname=server_hostname_rm_dot,
    666     ssl_context=self.ssl_context,
    667     tls_in_tls=tls_in_tls,
    668     assert_hostname=self.assert_hostname,
    669     assert_fingerprint=self.assert_fingerprint,
    670 )
    671 self.sock = sock_and_verified.socket

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:806, in _ssl_wrap_socket_and_match_hostname(sock, cert_reqs, ssl_version, ssl_minimum_version, ssl_maximum_version, cert_file, key_file, key_password, ca_certs, ca_cert_dir, ca_cert_data, assert_hostname, assert_fingerprint, server_hostname, ssl_context, tls_in_tls)
    804         server_hostname = normalized
--> 806 ssl_sock = ssl_wrap_socket(
    807     sock=sock,
    808     keyfile=key_file,
    809     certfile=cert_file,
    810     key_password=key_password,
    811     ca_certs=ca_certs,
    812     ca_cert_dir=ca_cert_dir,
    813     ca_cert_data=ca_cert_data,
    814     server_hostname=server_hostname,
    815     ssl_context=context,
    816     tls_in_tls=tls_in_tls,
    817 )
    819 try:

File ~\venv\py39darts\lib\site-packages\urllib3\util\ssl_.py:465, in ssl_wrap_socket(sock, keyfile, certfile, cert_reqs, ca_certs, server_hostname, ssl_version, ciphers, ssl_context, ca_cert_dir, key_password, ca_cert_data, tls_in_tls)
    463     pass
--> 465 ssl_sock = _ssl_wrap_socket_impl(sock, context, tls_in_tls, server_hostname)
    466 return ssl_sock

File ~\venv\py39darts\lib\site-packages\urllib3\util\ssl_.py:509, in _ssl_wrap_socket_impl(sock, ssl_context, tls_in_tls, server_hostname)
    507     return SSLTransport(sock, ssl_context, server_hostname)
--> 509 return ssl_context.wrap_socket(sock, server_hostname=server_hostname)

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:501, in SSLContext.wrap_socket(self, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, session)
    495 def wrap_socket(self, sock, server_side=False,
    496                 do_handshake_on_connect=True,
    497                 suppress_ragged_eofs=True,
    498                 server_hostname=None, session=None):
    499     # SSLSocket class handles server_hostname encoding before it calls
    500     # ctx._wrap_socket()
--> 501     return self.sslsocket_class._create(
    502         sock=sock,
    503         server_side=server_side,
    504         do_handshake_on_connect=do_handshake_on_connect,
    505         suppress_ragged_eofs=suppress_ragged_eofs,
    506         server_hostname=server_hostname,
    507         context=self,
    508         session=session
    509     )

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:1041, in SSLSocket._create(cls, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, context, session)
   1040             raise ValueError("do_handshake_on_connect should not be specified for non-blocking sockets")
-> 1041         self.do_handshake()
   1042 except (OSError, ValueError):

File ~\AppData\Local\Programs\Python\Python39\lib\ssl.py:1310, in SSLSocket.do_handshake(self, block)
   1309         self.settimeout(None)
-> 1310     self._sslobj.do_handshake()
   1311 finally:

SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:793, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    792 # Make the request on the HTTPConnection object
--> 793 response = self._make_request(
    794     conn,
    795     method,
    796     url,
    797     timeout=timeout_obj,
    798     body=body,
    799     headers=headers,
    800     chunked=chunked,
    801     retries=retries,
    802     response_conn=response_conn,
    803     preload_content=preload_content,
    804     decode_content=decode_content,
    805     **response_kw,
    806 )
    808 # Everything went great!

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:491, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    490         new_e = _wrap_proxy_error(new_e, conn.proxy.scheme)
--> 491     raise new_e
    493 # conn.request() calls http.client.*.request, not the method in
    494 # urllib3.request. It also calls makefile (recv) on the socket.

SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)

The above exception was the direct cause of the following exception:

MaxRetryError                             Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\requests\adapters.py:486, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    485 try:
--> 486     resp = conn.urlopen(
    487         method=request.method,
    488         url=url,
    489         body=request.body,
    490         headers=request.headers,
    491         redirect=False,
    492         assert_same_host=False,
    493         preload_content=False,
    494         decode_content=False,
    495         retries=self.max_retries,
    496         timeout=timeout,
    497         chunked=chunked,
    498     )
    500 except (ProtocolError, OSError) as err:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:847, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    845     new_e = ProtocolError("Connection aborted.", new_e)
--> 847 retries = retries.increment(
    848     method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2]
    849 )
    850 retries.sleep()

File ~\venv\py39darts\lib\site-packages\urllib3\util\retry.py:515, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    514     reason = error or ResponseError(cause)
--> 515     raise MaxRetryError(_pool, url, reason) from reason  # type: ignore[arg-type]
    517 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry)

MaxRetryError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2022/acs/acs5/geography.json (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)')))

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
Cell In[4], line 5
      2 from censusdis.datasets import ACS5
      3 from censusdis import states
----> 5 df_median_income = ced.download(
      6     # Data set: American Community Survey 5-Year
      7     dataset=ACS5,
      8     # Vintage: 2022
      9     vintage=2022,
     10     # Variable: median household income
     11     download_variables=['NAME', 'B19013_001E'],
     12     # Geography: All counties in New Jersey.
     13     state=states.NJ,
     14     county='*',
     15     api_key=api_key
     16 )

File ~\venv\py39darts\lib\site-packages\censusdis\data.py:455, in download(dataset, vintage, download_variables, group, leaves_of_group, set_to_nan, skip_annotations, with_geometry, remove_water, download_contained_within, area_threshold, api_key, variable_cache, row_keys, **kwargs)
    452     row_keys = list(row_keys)
    454 # The side effect here is to prime the cache.
--> 455 cgeo.geo_path_snake_specs(dataset, vintage)
    457 if set_to_nan is True:
    458     set_to_nan = ALL_SPECIAL_VALUES

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:456, in geo_path_snake_specs(dataset, year)
    452 def geo_path_snake_specs(dataset: str, year: int) -> Dict[str, List[str]]:
    453     """Construc a map to snake case for all know geo path specs."""
    454     return {
    455         name: [path_component_to_snake(dataset, year, c) for c in path_spec.path]
--> 456         for name, path_spec in PathSpec.get_path_specs(dataset, year).items()
    457     }

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:225, in PathSpec.get_path_specs(dataset, vintage)
    222 """Fet all the path specifications for the given dataset and vintage."""
    223 if vintage not in PathSpec._PATH_SPECS_BY_DATASET_YEAR[dataset]:
    224     PathSpec._PATH_SPECS_BY_DATASET_YEAR[dataset][vintage] = (
--> 225         PathSpec._fetch_path_specs(dataset, vintage)
    226     )
    227     PathSpec._PATH_SPEC_SNAKE_MAP[dataset][vintage] = {
    228         component.replace(" ", "_")
    229         .replace("/", "_")
   (...)
    237         for component in path_spec.path
    238     }
    239     PathSpec._PATH_SPEC_SNAKE_INV_MAP[dataset][vintage] = {
    240         name: py_name
    241         for py_name, name in PathSpec._PATH_SPEC_SNAKE_MAP[dataset][
    242             vintage
    243         ].items()
    244     }

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:188, in PathSpec._fetch_path_specs(dataset, year)
    184 @staticmethod
    185 def _fetch_path_specs(dataset: str, year: int) -> Dict[str, "PathSpec"]:
    186     url = PathSpec._geo_url(dataset, year)
--> 188     request = requests.get(url)
    190     if request.status_code == 200:
    191         parsed_json = request.json()

File ~\venv\py39darts\lib\site-packages\requests\api.py:73, in get(url, params, **kwargs)
     62 def get(url, params=None, **kwargs):
     63     r"""Sends a GET request.
     64 
     65     :param url: URL for the new :class:`Request` object.
   (...)
     70     :rtype: requests.Response
     71     """
---> 73     return request("get", url, params=params, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\api.py:59, in request(method, url, **kwargs)
     55 # By using the 'with' statement we are sure the session is closed, thus we
     56 # avoid leaving sockets open which can trigger a ResourceWarning in some
     57 # cases, and look like a memory leak in others.
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    584 send_kwargs = {
    585     "timeout": timeout,
    586     "allow_redirects": allow_redirects,
    587 }
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:703, in Session.send(self, request, **kwargs)
    700 start = preferred_clock()
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)
    706 elapsed = preferred_clock() - start

File ~\venv\py39darts\lib\site-packages\requests\adapters.py:517, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    513         raise ProxyError(e, request=request)
    515     if isinstance(e.reason, _SSLError):
    516         # This branch is for urllib3 v1.22 and later.
--> 517         raise SSLError(e, request=request)
    519     raise ConnectionError(e, request=request)
    521 except ClosedPoolError as e:

SSLError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2022/acs/acs5/geography.json (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1129)')))
```
I've got a work in progress branch that I think will address your issue. I don't have an environment with a proxy like yours so I need to come up with a way to test it before I merge it in. The branch is https://github.com/censusdis/censusdis/tree/dev/245. The specific commit that exposes the `cert` and `verify` args is https://github.com/censusdis/censusdis/commit/12ac750ff5cf3e1b902448b86bab9babd246f7d5.

So I think a fix is coming, but it's not quite here yet.

Once it is done, you should be able to do

```python
df_states = ced.download(
    DATASET,
    YEAR,
    VARIABLES,
    state="*",
    cert="my_certificate_file.pem"
)
```

For the moment, unless you are doing large volumes of requests, the API key issues is separate. So let's fix this one first then worry about the best way to help you with that one.
**Update**
- I tried the new branch https://github.com/censusdis/censusdis/tree/dev/245

Now, I can pass the cert argument, but still giving errors for me.

# Keys
```python
from pathlib import Path

path_api = Path().home() / '.censusdis/api_key.txt'
api_key = path_api.read_text()
print(api_key[:5])

cert = Path.home() / '.certificates/api_census_gov.crt'
cert_str = str(cert)
cert.read_text()[:10]
```

# Main code
```python
import censusdis.data as ced
from censusdis.datasets import ACS5
from censusdis import states

df_median_income = ced.download(
    # Data set: American Community Survey 5-Year
    dataset=ACS5,
    # Vintage: 2022
    vintage=2022,
    # Variable: median household income
    download_variables=['NAME', 'B19013_001E'],
    # Geography: All counties in New Jersey.
    state=states.NJ,
    county='*',
    api_key=api_key,
    cert=cert_str
)
```

# Error
```
---------------------------------------------------------------------------
SSLError                                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:467, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    466 try:
--> 467     self._validate_conn(conn)
    468 except (SocketTimeout, BaseSSLError) as e:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:1099, in HTTPSConnectionPool._validate_conn(self, conn)
   1098 if conn.is_closed:
-> 1099     conn.connect()
   1101 # TODO revise this, see https://github.com/urllib3/urllib3/issues/2791

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:653, in HTTPSConnection.connect(self)
    651 server_hostname_rm_dot = server_hostname.rstrip(".")
--> 653 sock_and_verified = _ssl_wrap_socket_and_match_hostname(
    654     sock=sock,
    655     cert_reqs=self.cert_reqs,
    656     ssl_version=self.ssl_version,
    657     ssl_minimum_version=self.ssl_minimum_version,
    658     ssl_maximum_version=self.ssl_maximum_version,
    659     ca_certs=self.ca_certs,
    660     ca_cert_dir=self.ca_cert_dir,
    661     ca_cert_data=self.ca_cert_data,
    662     cert_file=self.cert_file,
    663     key_file=self.key_file,
    664     key_password=self.key_password,
    665     server_hostname=server_hostname_rm_dot,
    666     ssl_context=self.ssl_context,
    667     tls_in_tls=tls_in_tls,
    668     assert_hostname=self.assert_hostname,
    669     assert_fingerprint=self.assert_fingerprint,
    670 )
    671 self.sock = sock_and_verified.socket

File ~\venv\py39darts\lib\site-packages\urllib3\connection.py:806, in _ssl_wrap_socket_and_match_hostname(sock, cert_reqs, ssl_version, ssl_minimum_version, ssl_maximum_version, cert_file, key_file, key_password, ca_certs, ca_cert_dir, ca_cert_data, assert_hostname, assert_fingerprint, server_hostname, ssl_context, tls_in_tls)
    804         server_hostname = normalized
--> 806 ssl_sock = ssl_wrap_socket(
    807     sock=sock,
    808     keyfile=key_file,
    809     certfile=cert_file,
    810     key_password=key_password,
    811     ca_certs=ca_certs,
    812     ca_cert_dir=ca_cert_dir,
    813     ca_cert_data=ca_cert_data,
    814     server_hostname=server_hostname,
    815     ssl_context=context,
    816     tls_in_tls=tls_in_tls,
    817 )
    819 try:

File ~\venv\py39darts\lib\site-packages\urllib3\util\ssl_.py:456, in ssl_wrap_socket(sock, keyfile, certfile, cert_reqs, ca_certs, server_hostname, ssl_version, ciphers, ssl_context, ca_cert_dir, key_password, ca_cert_data, tls_in_tls)
    455 if key_password is None:
--> 456     context.load_cert_chain(certfile, keyfile)
    457 else:

SSLError: [SSL] PEM lib (_ssl.c:4065)

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:793, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    792 # Make the request on the HTTPConnection object
--> 793 response = self._make_request(
    794     conn,
    795     method,
    796     url,
    797     timeout=timeout_obj,
    798     body=body,
    799     headers=headers,
    800     chunked=chunked,
    801     retries=retries,
    802     response_conn=response_conn,
    803     preload_content=preload_content,
    804     decode_content=decode_content,
    805     **response_kw,
    806 )
    808 # Everything went great!

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:491, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    490         new_e = _wrap_proxy_error(new_e, conn.proxy.scheme)
--> 491     raise new_e
    493 # conn.request() calls http.client.*.request, not the method in
    494 # urllib3.request. It also calls makefile (recv) on the socket.

SSLError: [SSL] PEM lib (_ssl.c:4065)

The above exception was the direct cause of the following exception:

MaxRetryError                             Traceback (most recent call last)
File ~\venv\py39darts\lib\site-packages\requests\adapters.py:486, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    485 try:
--> 486     resp = conn.urlopen(
    487         method=request.method,
    488         url=url,
    489         body=request.body,
    490         headers=request.headers,
    491         redirect=False,
    492         assert_same_host=False,
    493         preload_content=False,
    494         decode_content=False,
    495         retries=self.max_retries,
    496         timeout=timeout,
    497         chunked=chunked,
    498     )
    500 except (ProtocolError, OSError) as err:

File ~\venv\py39darts\lib\site-packages\urllib3\connectionpool.py:847, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    845     new_e = ProtocolError("Connection aborted.", new_e)
--> 847 retries = retries.increment(
    848     method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2]
    849 )
    850 retries.sleep()

File ~\venv\py39darts\lib\site-packages\urllib3\util\retry.py:515, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    514     reason = error or ResponseError(cause)
--> 515     raise MaxRetryError(_pool, url, reason) from reason  # type: ignore[arg-type]
    517 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry)

MaxRetryError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2022/acs/acs5/geography.json (Caused by SSLError(SSLError(9, '[SSL] PEM lib (_ssl.c:4065)')))

During handling of the above exception, another exception occurred:

SSLError                                  Traceback (most recent call last)
Cell In[11], line 5
      2 from censusdis.datasets import ACS5
      3 from censusdis import states
----> 5 df_median_income = ced.download(
      6     # Data set: American Community Survey 5-Year
      7     dataset=ACS5,
      8     # Vintage: 2022
      9     vintage=2022,
     10     # Variable: median household income
     11     download_variables=['NAME', 'B19013_001E'],
     12     # Geography: All counties in New Jersey.
     13     state=states.NJ,
     14     county='*',
     15     api_key=api_key,
     16     cert=cert_str
     17 )

File ~\venv\py39darts\lib\site-packages\censusdis\data.py:479, in download(dataset, vintage, download_variables, group, leaves_of_group, set_to_nan, skip_annotations, with_geometry, remove_water, download_contained_within, area_threshold, api_key, variable_cache, row_keys, verify, cert, **kwargs)
    476     row_keys = list(row_keys)
    478 # The side effect here is to prime the cache.
--> 479 cgeo.geo_path_snake_specs(dataset, vintage, verify=verify, cert=cert)
    481 if set_to_nan is True:
    482     set_to_nan = ALL_SPECIAL_VALUES

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:474, in geo_path_snake_specs(dataset, year, verify, cert)
    464 def geo_path_snake_specs(
    465     dataset: str,
    466     year: int,
   (...)
    469     cert: Optional[Union[str, Tuple[str, str]]] = None,
    470 ) -> Dict[str, List[str]]:
    471     """Construct a map to snake case for all know geo path specs."""
    472     return {
    473         name: [path_component_to_snake(dataset, year, c) for c in path_spec.path]
--> 474         for name, path_spec in PathSpec.get_path_specs(
    475             dataset, year, verify=verify, cert=cert
    476         ).items()
    477     }

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:237, in PathSpec.get_path_specs(dataset, vintage, verify, cert)
    234 """Fetch all the path specifications for the given dataset and vintage."""
    235 if vintage not in PathSpec._PATH_SPECS_BY_DATASET_YEAR[dataset]:
    236     PathSpec._PATH_SPECS_BY_DATASET_YEAR[dataset][vintage] = (
--> 237         PathSpec._fetch_path_specs(dataset, vintage, verify=verify, cert=cert)
    238     )
    239     PathSpec._PATH_SPEC_SNAKE_MAP[dataset][vintage] = {
    240         component.replace(" ", "_")
    241         .replace("/", "_")
   (...)
    249         for component in path_spec.path
    250     }
    251     PathSpec._PATH_SPEC_SNAKE_INV_MAP[dataset][vintage] = {
    252         name: py_name
    253         for py_name, name in PathSpec._PATH_SPEC_SNAKE_MAP[dataset][
    254             vintage
    255         ].items()
    256     }

File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:194, in PathSpec._fetch_path_specs(dataset, year, verify, cert)
    184 @staticmethod
    185 def _fetch_path_specs(
    186     dataset: str,
   (...)
    190     cert: Optional[Union[str, Tuple[str, str]]] = None,
    191 ) -> Dict[str, "PathSpec"]:
    192     url = PathSpec._geo_url(dataset, year)
--> 194     request = requests.get(url, verify=verify, cert=cert)
    196     if request.status_code == 200:
    197         parsed_json = request.json()

File ~\venv\py39darts\lib\site-packages\requests\api.py:73, in get(url, params, **kwargs)
     62 def get(url, params=None, **kwargs):
     63     r"""Sends a GET request.
     64 
     65     :param url: URL for the new :class:`Request` object.
   (...)
     70     :rtype: requests.Response
     71     """
---> 73     return request("get", url, params=params, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\api.py:59, in request(method, url, **kwargs)
     55 # By using the 'with' statement we are sure the session is closed, thus we
     56 # avoid leaving sockets open which can trigger a ResourceWarning in some
     57 # cases, and look like a memory leak in others.
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    584 send_kwargs = {
    585     "timeout": timeout,
    586     "allow_redirects": allow_redirects,
    587 }
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File ~\venv\py39darts\lib\site-packages\requests\sessions.py:703, in Session.send(self, request, **kwargs)
    700 start = preferred_clock()
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)
    706 elapsed = preferred_clock() - start

File ~\venv\py39darts\lib\site-packages\requests\adapters.py:517, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    513         raise ProxyError(e, request=request)
    515     if isinstance(e.reason, _SSLError):
    516         # This branch is for urllib3 v1.22 and later.
--> 517         raise SSLError(e, request=request)
    519     raise ConnectionError(e, request=request)
    521 except ClosedPoolError as e:

SSLError: HTTPSConnectionPool(host='api.census.gov', port=443): Max retries exceeded with url: /data/2022/acs/acs5/geography.json (Caused by SSLError(SSLError(9, '[SSL] PEM lib (_ssl.c:4065)')))

```
Thanks for the details. It's a little hard for me to debug without access to your environment, but we will get there. A key point in the stack trace above is

```
File ~\venv\py39darts\lib\site-packages\censusdis\geography.py:194, in PathSpec._fetch_path_specs(dataset, year, verify, cert)
    184 @staticmethod
    185 def _fetch_path_specs(
    186     dataset: str,
   (...)
    190     cert: Optional[Union[str, Tuple[str, str]]] = None,
    191 ) -> Dict[str, "PathSpec"]:
    192     url = PathSpec._geo_url(dataset, year)
--> 194     request = requests.get(url, verify=verify, cert=cert)
    196     if request.status_code == 200:
    197         parsed_json = request.json()
```

Would it be possible for you to run this in a debugger, set a breakpoint there, tell me each time the breakpoint is hit what the `url` is and validate that the values of `verify`,  and `cert` are as you expect them to be? I think the final time before it raises the exception the `url` will be `https://api.census.gov/data/2022/acs/acs5/geography.json`. And at that point I want to see if `verify` and `cert` are right.
There is another issue on the horizon here. The maps are downloaded from a different server which has a different certificate than the main API server. So once we have the data working and you want to add `with_geometry=True`  to a call to `ced.download` there is going to have to be an additional argument for `map_cert=`. 

I've seen some hairy security setups like this before and it always makes using the `requests` module a pain. But I think we are close to a solution. But in this case the simple-looking API `ced.download` is orchestrating multiple calls to different remote APIs, so it passing the cert all the way through the call tree is kind of messy. I almost wonder if giving the user the option to set the two certs and the `verify` flag globally is a better option at this point. It's more of a config up front before you do anything.

Fix patch:
diff --git a/censusdis/data.py b/censusdis/data.py
index 41cabd4f8..50f6439b3 100644
--- a/censusdis/data.py
+++ b/censusdis/data.py
@@ -37,6 +37,9 @@
 from censusdis.impl.varsource.censusapi import CensusApiVariableSource
 from censusdis.values import ALL_SPECIAL_VALUES
 
+import censusdis.impl.fetch
+
+
 logger = getLogger(__name__)
 
 
@@ -1301,3 +1304,6 @@ def add_inferred_geography(
     gdf = gpd.GeoDataFrame(df_with_geo)
 
     return gdf
+
+
+certificates = censusdis.impl.fetch.certificates
diff --git a/censusdis/datasets.py b/censusdis/datasets.py
index 8912cc581..248c20a04 100644
--- a/censusdis/datasets.py
+++ b/censusdis/datasets.py
@@ -528,7 +528,7 @@
 
 TIMESERIES_IDB = "timeseries/idb/5year"
 
-TIMESERIES_INTLTRADE = "timeseries/intltrade/imports/usda"
+TIMESERIES_INTLTRADE = "timeseries/intltrade/imports/usdaimport"
 
 TIMESERIES_POVERTY = "timeseries/poverty/saipe/schdist"
 
@@ -810,7 +810,7 @@
     TIMESERIES_HHPULSE: "http://api.census.gov/data/timeseries/hhpulse",
     TIMESERIES_HPS: "http://api.census.gov/data/timeseries/hps",
     TIMESERIES_IDB: "http://api.census.gov/data/timeseries/idb/5year",
-    TIMESERIES_INTLTRADE: "http://api.census.gov/data/timeseries/intltrade/imports/usda",
+    TIMESERIES_INTLTRADE: "http://api.census.gov/data/timeseries/intltrade/imports/usdaimport",
     TIMESERIES_POVERTY: "http://api.census.gov/data/timeseries/poverty/saipe/schdist",
     TIMESERIES_PSEO: "http://api.census.gov/data/timeseries/pseo/flows",
     TIMESERIES_QWI: "http://api.census.gov/data/timeseries/qwi/se",
diff --git a/censusdis/geography.py b/censusdis/geography.py
index 3e72d77ef..be5187ad6 100644
--- a/censusdis/geography.py
+++ b/censusdis/geography.py
@@ -21,6 +21,8 @@
 import requests
 
 from .impl.exceptions import CensusApiException
+from .impl.fetch import certificates
+
 
 InSpecType = Union[str, Iterable[str]]
 
@@ -185,7 +187,9 @@ def _geo_url(dataset: str, year: int) -> str:
     def _fetch_path_specs(dataset: str, year: int) -> Dict[str, "PathSpec"]:
         url = PathSpec._geo_url(dataset, year)
 
-        request = requests.get(url)
+        request = requests.get(
+            url, cert=certificates.data_cert, verify=certificates.data_verify
+        )
 
         if request.status_code == 200:
             parsed_json = request.json()
diff --git a/censusdis/impl/fetch.py b/censusdis/impl/fetch.py
index 57a018d7c..f4a50cf40 100644
--- a/censusdis/impl/fetch.py
+++ b/censusdis/impl/fetch.py
@@ -1,8 +1,7 @@
 # Copyright (c) 2022 Darren Erik Vengroff
 """Utilities for loading census data."""
-
 from logging import getLogger
-from typing import Any, Mapping, Optional
+from typing import Any, Mapping, Optional, Union, Tuple
 
 import pandas as pd
 import requests
@@ -12,9 +11,158 @@
 logger = getLogger(__name__)
 
 
+class _CertificateManager:
+    """Manage the certificates and verification flags used when we make calls to the U.S. Census servers."""
+
+    _have_a_singletop_certificate_manager = False
+
+    def __init__(
+        self,
+        *,
+        data_verify: Union[bool, str] = True,
+        data_cert: Optional[Union[str, Tuple[str, str]]] = None,
+        map_verify: Union[bool, str] = True,
+        map_cert: Optional[Union[str, Tuple[str, str]]] = None,
+    ):
+        """
+        Manage the certificates and verification flags used when we make calls to the U.S. Census servers.
+
+        Parameters
+        ----------
+        data_verify
+            Value to pass to `requests.get` in the `verify=` argument for data API calls to `https://api.census.gov`.
+        data_cert
+            Value to pass to `requests.get` in the `cert=` argument for data API calls to `https://api.census.gov`.
+        map_verify
+            Value to pass to `requests.get` in the `verify=` argument for getting map data with calls to
+            `https://www2.census.gov`.
+        map_cert
+            Value to pass to `requests.get` in the `cert=` argument for getting map data with calls to
+            `https://www2.census.gov`.
+        """
+        if self._have_a_singletop_certificate_manager:
+            raise ValueError(
+                "Cannot create a CertificateManager. Please use `censusdis.data.certificates`."
+            )
+
+        self._data_verify = data_verify
+        self._data_cert = data_cert
+        self._map_verify = map_verify
+        self._map_cert = map_cert
+
+        self._have_a_singletop_certificate_manager = True
+
+    @property
+    def data_verify(self) -> Union[bool, str]:
+        """Value to pass to `requests.get` in the `verify=` argument for data from `https://api.census.gov`."""
+        return self._data_verify
+
+    @property
+    def data_cert(self) -> Union[str, Tuple[str, str], None]:
+        """Value to pass to `requests.get` in the `cert=` argument for data from `https://api.census.gov`."""
+        return self._data_cert
+
+    @property
+    def map_verify(self) -> Union[bool, str]:
+        """Value to pass to `requests.get` in the `verify=` argument for maps from `https://www2.census.gov`."""
+        return self._map_verify
+
+    @property
+    def map_cert(self) -> Union[str, Tuple[str, str], None]:
+        """Value to pass to `requests.get` in the `cert=` argument for maps from `https://www2.census.gov`."""
+        return self._map_cert
+
+    def use(
+        self,
+        *,
+        data_verify: Union[bool, str] = True,
+        data_cert: Optional[Union[str, Tuple[str, str]]] = None,
+        map_verify: Union[bool, str] = True,
+        map_cert: Optional[Union[str, Tuple[str, str]]] = None,
+    ) -> "_CertificateManagerContext":
+        """
+        Set certificates and verification flags globally or within a context.
+
+        If you want to set up certificate handling globally, you can just call this
+        method alone, for example:
+
+            import censusdis.data as ced
+
+            ced.certificates.use(data_verify=False, map_verify=False)
+
+        will turn off certificate verification for all data and map calls. This can by useful
+        in a notebook environment, where you want to set up how certificates are handled once
+        at the top of the notebook.
+
+        If you want the effects to only be temporary, you can use a context manager with a `with`
+        statement as follows::
+
+            import censusdis.data as ced
+
+            with ced.certificates.use(data_verify=False, map_verify=False):
+                # No verification will be performed here.
+                df = ced.download(...)
+
+            # Upon exiting the context, verification is back on.
+            df = ced.download(...)
+
+        Parameters
+        ----------
+        data_verify
+            Value to pass to `requests.get` in the `verify=` argument for data API calls to `https://api.census.gov`.
+        data_cert
+            Value to pass to `requests.get` in the `cert=` argument for data API calls to `https://api.census.gov`.
+        map_verify
+            Value to pass to `requests.get` in the `verify=` argument for getting map data with calls to
+            `https://www2.census.gov`.
+        map_cert
+            Value to pass to `requests.get` in the `cert=` argument for getting map data with calls to
+            `https://www2.census.gov`.
+        """
+        context = _CertificateManagerContext(self)
+        self._data_verify = data_verify
+        self._data_cert = data_cert
+        self._map_verify = map_verify
+        self._map_cert = map_cert
+        return context
+
+
+class _CertificateManagerContext:
+    def __init__(self, certificate_manager: _CertificateManager):
+        self._certificate_manager = certificate_manager
+        self._data_verify = certificate_manager.data_verify
+        self._data_cert = certificate_manager.data_cert
+        self._map_verify = certificate_manager.map_verify
+        self._map_cert = certificate_manager.map_cert
+
+    def __enter__(self):
+        pass
+
+    def __exit__(self, type_, value, traceback):
+        self._certificate_manager._data_verify = self._data_verify
+        self._certificate_manager._data_cert = self._data_cert
+        self._certificate_manager._map_verify = self._map_verify
+        self._certificate_manager._map_cert = self._map_cert
+
+
+certificates = _CertificateManager()
+"""
+A container for the certificates and verification flags used when we make calls to the U.S. Census servers.
+
+Unless you are working behind a security proxy or firewall that manipulates certificates in
+some way, you will never have to use this.
+
+If you would not normally use the `verify=` or `cert=` arguments when using `requests.get` then
+you need not worry about this. If you would, then use the values you would pass for accessing
+`https://api.census.gov` or `https://www2.census.gov`.
+"""
+
+
 def json_from_url(url: str, params: Optional[Mapping[str, str]] = None) -> Any:
     """Get json from a URL."""
-    request = requests.get(url, params=params)
+    request = requests.get(
+        url, params=params, cert=certificates.data_cert, verify=certificates.data_verify
+    )
 
     if request.status_code == 200:
         parsed_json = request.json()
diff --git a/censusdis/maps.py b/censusdis/maps.py
index b309ffa33..77edb8d58 100644
--- a/censusdis/maps.py
+++ b/censusdis/maps.py
@@ -25,6 +25,7 @@
 import matplotlib.patheffects as pe
 
 from censusdis.impl.exceptions import CensusApiException
+from censusdis.impl.fetch import certificates
 from censusdis.states import AK, HI, NAMES_FROM_IDS, PR
 
 logger = getLogger(__name__)
@@ -468,7 +469,12 @@ def _fetch_file(
         zip_url = f"{base_url}/{name}.zip"
 
         # Fetch the zip file and write it.
-        response = requests.get(zip_url, timeout=timeout)
+        response = requests.get(
+            zip_url,
+            timeout=timeout,
+            cert=certificates.map_cert,
+            verify=certificates.map_verify,
+        )
 
         if response.status_code == 404:
             raise MapException(
diff --git a/docs/intro.rst b/docs/intro.rst
index aaef165cc..c61ad8d76 100644
--- a/docs/intro.rst
+++ b/docs/intro.rst
@@ -23,23 +23,6 @@ or `poetry <https://python-poetry.org/>`_ to manage
 your dependencies, then you can add ``censusdis`` the
 same way you would add any other dependency.
 
-Census API Key (Optional Initially)
------------------------------------
-
-The Census API that ``censusdis`` calls requires the use of an API
-key unless you are doing only a relatively small number of queries.
-Luckily, the key is free and easy to get, and once you have one in
-a file in the right place on your machine ``censusdis`` will automatically
-use it with every call to the Census API.
-
-To obtain a key, visit `this page <https://api.census.gov/data/key_signup.html>`_.
-The key will be sent to you be email. It will be a long string of numbers 
-and letters. Make a directory called ``.censusdis`` in your home directory,
-then inside that directory create a text file called ``api_key.txt``. The file
-should have just one line, and you should paste the key you got via email
-into it. Once this is done, all ``censusdis`` calls to the Census API will
-use this key.
-
 Making Your First Query
 -----------------------
 
@@ -566,6 +549,29 @@ There are additional more advanced examples and
 additional maps and visualizations,
 presented in more `Demo Notebooks <./notebooks.html>`_.
 
+Census API Key (Optional Initially)
+-----------------------------------
+
+The Census API that ``censusdis`` calls recommends the use of an API
+key. But chances are you were able to make it through all of the examples
+above without one. This is because
+until you are doing a large number of queries, you don't need
+one. But
+once you are doing a large number of queries or putting `censusdis` into
+a production pipeline, you should return to this section and obtain a key.
+
+Luckily, the key is free and easy to get, and once you have a key in
+a file in the right place on your machine ``censusdis`` will automatically
+use it with every call to the Census API.
+
+To obtain a key, visit `this page <https://api.census.gov/data/key_signup.html>`_.
+The key will be sent to you be email. It will be a long string of numbers
+and letters. Make a directory called ``.censusdis`` in your home directory,
+then inside that directory create a text file called ``api_key.txt``. The file
+should have just one line, and you should paste the key you got via email
+into it. Once this is done, all ``censusdis`` calls to the Census API will
+use this key.
+
 Help and Issues
 ---------------
 
diff --git a/notebooks/SSL Debugging.ipynb b/notebooks/SSL Debugging.ipynb
new file mode 100644
index 000000000..fd91d7534
--- /dev/null
+++ b/notebooks/SSL Debugging.ipynb
@@ -0,0 +1,645 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "42b2e777-1ab2-4a0d-9252-48d13b4612c1",
+   "metadata": {},
+   "source": [
+    "# SSL Verification and Certificates\n",
+    "\n",
+    "**Note:** If any of the other demonstration notebooks are working properly\n",
+    "for you, then there is nothing in this notebook that you need to know about.\n",
+    "You can safely ignore it. The SSL certificates the U.S. Census Bureau uses \n",
+    "are completely valid and work as intended in almost all cases. But if you\n",
+    "are getting SSL errors, this notebook may be able to help you.\n",
+    "\n",
+    "## Background\n",
+    "\n",
+    "Some organizations use security proxies or firewalls\n",
+    "that interfere with the proper functioning of these certificates when they are used\n",
+    "from Python code. If you are a part of such an organization, you probably already\n",
+    "know this as you have probably had issues accessing a wide variety of secure\n",
+    "web sites from Python code.\n",
+    "\n",
+    "### Solution 1: Don't verify the certificate\n",
+    "\n",
+    "One common solution to working in this kind of environments is to ask the Python\n",
+    "`requests` library to either ignore bad SSL certificates. This is done by adding the\n",
+    "`verify=False` argument to APIs like `requests.get()`. So instead of writing something\n",
+    "like\n",
+    "\n",
+    "```python\n",
+    "import requests\n",
+    "\n",
+    "url = \"https://www.mysite.org/document\"\n",
+    "\n",
+    "response = requests.get(url)\n",
+    "```\n",
+    "\n",
+    "you would write\n",
+    "\n",
+    "```python\n",
+    "import requests\n",
+    "\n",
+    "url = \"https://www.mysite.org/document\"\n",
+    "\n",
+    "response = requests.get(url, verify=False)\n",
+    "```\n",
+    "\n",
+    "### Solution 2: Provide your own key\n",
+    "\n",
+    "A second solution, which is more secure than just ignoring verification, is to provide your own certificate, like\n",
+    "this\n",
+    "\n",
+    "```python\n",
+    "import requests\n",
+    "\n",
+    "url = \"https://www.mysite.org/document\"\n",
+    "\n",
+    "# Get this file however your organization's security department\n",
+    "# advises you to and use one of the two syntaxes below as they\n",
+    "# advise you:\n",
+    "cert = \"mysite-certificate-file.pem\"\n",
+    "\n",
+    "# Syntax 1: just the cert file\n",
+    "response = requests.get(url, cert=cert)\n",
+    "\n",
+    "# Syntax 2: cert and key in a tuple\n",
+    "response = requests.get(url, cert=(cert, key))\n",
+    "```\n",
+    "\n",
+    "### How can we do this in `censusdis`?\n",
+    "\n",
+    "The problem is, when you are using `censusdis`, it is managing many different calls to different U.S. Census\n",
+    "APIs on your behalf to download and combine the data and maps you request. You could go patch them all but that\n",
+    "would be a pain. \n",
+    "\n",
+    "In order to avoid this pain, we will rely on a special object that can be found at `censusdis.data.certificates`.\n",
+    "The rest of this notebook demonstrates how it can be used.\n",
+    "\n",
+    "Note that as your work through debugging this, you will probably want to move or remove the directory `~/.censusdis/data/shapefiles`\n",
+    "regularly. This directory is a cache of map files. If you want to force `censusdis` to download new map files every time,\n",
+    "then please delete the directory each time before running your code.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54000342-1c59-4a14-be1f-bd6a44a12381",
+   "metadata": {},
+   "source": [
+    "## A Test Query\n",
+    "\n",
+    "This example is plain vanilla. It does nothing to ingore SLL certifite problems or to provide a working key.\n",
+    "If it works in your environment, that's great. You don't need to do anything fancy to manage certificates and\n",
+    "can put this notebook away.\n",
+    "\n",
+    "If, however, this cell gives you an SSL error, then you do have to take additional steps to successfully use \n",
+    "`censusdis`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "48e75017-8556-4c7a-bc22-597391dd657f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>STATE</th>\n",
+       "      <th>COUNTY</th>\n",
+       "      <th>NAME</th>\n",
+       "      <th>B01003_001E</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>34</td>\n",
+       "      <td>001</td>\n",
+       "      <td>Atlantic County, New Jersey</td>\n",
+       "      <td>274339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>003</td>\n",
+       "      <td>Bergen County, New Jersey</td>\n",
+       "      <td>953243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34</td>\n",
+       "      <td>005</td>\n",
+       "      <td>Burlington County, New Jersey</td>\n",
+       "      <td>461853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>34</td>\n",
+       "      <td>007</td>\n",
+       "      <td>Camden County, New Jersey</td>\n",
+       "      <td>522581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34</td>\n",
+       "      <td>009</td>\n",
+       "      <td>Cape May County, New Jersey</td>\n",
+       "      <td>95456</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  STATE COUNTY                           NAME  B01003_001E\n",
+       "0    34    001    Atlantic County, New Jersey       274339\n",
+       "1    34    003      Bergen County, New Jersey       953243\n",
+       "2    34    005  Burlington County, New Jersey       461853\n",
+       "3    34    007      Camden County, New Jersey       522581\n",
+       "4    34    009    Cape May County, New Jersey        95456"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import censusdis.data as ced\n",
+    "import censusdis.maps as cem\n",
+    "from censusdis.datasets import ACS5\n",
+    "from censusdis.states import NJ\n",
+    "\n",
+    "VARIABLE_TOTAL_POPULATION = \"B01003_001E\"\n",
+    "\n",
+    "df = ced.download(\n",
+    "    dataset=ACS5,\n",
+    "    vintage=2022,\n",
+    "    download_variables=[\"NAME\", VARIABLE_TOTAL_POPULATION],\n",
+    "    state=NJ,\n",
+    "    county=\"*\",\n",
+    ")\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7e27661-86d7-4167-ba62-2b857dac1119",
+   "metadata": {},
+   "source": [
+    "## Solution 1: Don't verify the certificate\n",
+    "\n",
+    "Here's how we can ignore certificate verification when `censusdis` downloads data and maps:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c2de7925-fbaa-4c9b-b452-7f1196278b19",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>STATE</th>\n",
+       "      <th>COUNTY</th>\n",
+       "      <th>NAME</th>\n",
+       "      <th>B01003_001E</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>34</td>\n",
+       "      <td>001</td>\n",
+       "      <td>Atlantic County, New Jersey</td>\n",
+       "      <td>274339</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>003</td>\n",
+       "      <td>Bergen County, New Jersey</td>\n",
+       "      <td>953243</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34</td>\n",
+       "      <td>005</td>\n",
+       "      <td>Burlington County, New Jersey</td>\n",
+       "      <td>461853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>34</td>\n",
+       "      <td>007</td>\n",
+       "      <td>Camden County, New Jersey</td>\n",
+       "      <td>522581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34</td>\n",
+       "      <td>009</td>\n",
+       "      <td>Cape May County, New Jersey</td>\n",
+       "      <td>95456</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  STATE COUNTY                           NAME  B01003_001E\n",
+       "0    34    001    Atlantic County, New Jersey       274339\n",
+       "1    34    003      Bergen County, New Jersey       953243\n",
+       "2    34    005  Burlington County, New Jersey       461853\n",
+       "3    34    007      Camden County, New Jersey       522581\n",
+       "4    34    009    Cape May County, New Jersey        95456"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "with ced.certificates.use(data_verify=False):\n",
+    "    df = ced.download(\n",
+    "        dataset=ACS5,\n",
+    "        vintage=2022,\n",
+    "        download_variables=[\"NAME\", VARIABLE_TOTAL_POPULATION],\n",
+    "        state=NJ,\n",
+    "        county=\"*\",\n",
+    "    )\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ca4312ee-8b83-4a95-b04b-63826b22a730",
+   "metadata": {},
+   "source": [
+    "Unverified certificates may generate warnings, but unless someone is carefully spoofing the U.S. Census, the data you get back is legitimate.\n",
+    "\n",
+    "The maps that `censusdis` loads when the `with_geometry=True` argument is used come from a different server than the data. \n",
+    "So if we are getting maps, we may need to separately skip verifying that server's certificate too. We can do this as follow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "734d2095-da94-4545-a98b-6ceabffb7c9f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n",
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'www2.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "with ced.certificates.use(data_verify=False, map_verify=False):\n",
+    "    gdf = ced.download(\n",
+    "        dataset=ACS5,\n",
+    "        vintage=2022,\n",
+    "        download_variables=[\"NAME\", VARIABLE_TOTAL_POPULATION],\n",
+    "        state=NJ,\n",
+    "        county=\"*\",\n",
+    "        with_geometry=True,\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2c1bd29d-cf75-49f2-81b7-0b43f999607b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1000 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = cem.plot_map(\n",
+    "    gdf,\n",
+    "    geo_label=gdf[\"NAME\"].apply(lambda name: name.split(\"County, \")[0]),\n",
+    "    edgecolor=\"black\",\n",
+    "    color=\"beige\",\n",
+    "    figsize=(8, 10),\n",
+    ")\n",
+    "\n",
+    "_ = ax.set_title(\"New Jersey Counties\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5bd65cc0-884b-41d8-be64-fe669aadf8c7",
+   "metadata": {},
+   "source": [
+    "## Solution 2: Provide your own key\n",
+    "\n",
+    "This solution is more secure, and will not generate warnings, but it will require you\n",
+    "to consult with whoever set up the firewall or proxy that is causing problems for\n",
+    "`censusdis` in the first place.\n",
+    "\n",
+    "In discussing this solution, we will assume you are familiar with how to use certificates\n",
+    "with the `requests` library in your Python environment. We aren't and probably can't be\n",
+    "since we don't work in your environment.\n",
+    "\n",
+    "The sample code below does not all work in my environment, but assuming you put the appropriate\n",
+    "key file in the appropriate place for your environment, it should work for you.\n",
+    "\n",
+    "You will need two certificates, one for https://api.census.gov so `censusdis` can get data,\n",
+    "and one for https://www2.census.gov so it can get maps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "81f77eeb-0f61-454a-96c0-f281ba641839",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Could not find the TLS certificate file, invalid path: /path/to/certs/api-census.gov.pem\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Adjust the paths to the two key files as appropriate. These should be the\n",
+    "# same files we would pass to the `cert=` argument of `requests.get` for\n",
+    "# each of the two sites.\n",
+    "\n",
+    "# Store a key that works for https://api.census.gov in this file:\n",
+    "data_cert = \"/path/to/certs/api-census.gov.pem\"\n",
+    "\n",
+    "# Store a key file that works for https://www2.census.gov in this file:\n",
+    "map_cert = \"/path/to/certs/www-census.gov.pem\"\n",
+    "\n",
+    "# We will catch the exception because the paths above need to be\n",
+    "# chosen for your environment. They don't actually exist.\n",
+    "\n",
+    "try:\n",
+    "    with ced.certificates.use(data_cert=data_cert, map_cert=map_cert):\n",
+    "        gdf = ced.download(\n",
+    "            dataset=ACS5,\n",
+    "            vintage=2022,\n",
+    "            download_variables=[\"NAME\", VARIABLE_TOTAL_POPULATION],\n",
+    "            state=NJ,\n",
+    "            county=\"*\",\n",
+    "            with_geometry=True,\n",
+    "        )\n",
+    "except OSError as e:\n",
+    "    print(e)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e73fd94f-3ec2-4dfe-9ac8-243ace07c595",
+   "metadata": {},
+   "source": [
+    "## Global settings\n",
+    "\n",
+    "In the examples above, we always used `ced.certificates.use` as a context manager inside a `with` clause.\n",
+    "This is useful for constraining the effects of `ced.certificates.use` to just a few lines of code. But in\n",
+    "many real world non-demo cases, we just want to set it globally and forget it. Luckily, that is easy to do.\n",
+    "Instead of using `with`, we just call it globally. Typically, we would do this at the top of a notebook.\n",
+    "Here is some code that illustrates how it works with `data_verify`. If works similarly with `data_cert`, `map_verify`,\n",
+    "and `map_cert`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3d58ce67-0916-4cf9-ac29-71f154175534",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Initially, ced.certificates.data_verify is True.\n",
+      "Now, globally, ced.certificates.data_verify is False.\n",
+      "Now, globally, ced.certificates.data_verify is back to True.\n",
+      "    Within the context, ced.certificates.data_verify is False.\n",
+      "Finally, globally, ced.certificates.data_verify is True.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Initially, ced.certificates.data_verify is {ced.certificates.data_verify}.\")\n",
+    "\n",
+    "# Global change.\n",
+    "ced.certificates.use(data_verify=False)\n",
+    "\n",
+    "print(f\"Now, globally, ced.certificates.data_verify is {ced.certificates.data_verify}.\")\n",
+    "\n",
+    "# Change it back globally.\n",
+    "ced.certificates.use(data_verify=True)\n",
+    "\n",
+    "print(\n",
+    "    f\"Now, globally, ced.certificates.data_verify is back to {ced.certificates.data_verify}.\"\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# We can change it temporarily in a context manager.\n",
+    "with ced.certificates.use(data_verify=False):\n",
+    "    print(\n",
+    "        f\"    Within the context, ced.certificates.data_verify is {ced.certificates.data_verify}.\"\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "# And back outside the context the globally set value is back.\n",
+    "print(\n",
+    "    f\"Finally, globally, ced.certificates.data_verify is {ced.certificates.data_verify}.\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66b87b67-7ad0-47ab-b621-c0a36c87f74e",
+   "metadata": {},
+   "source": [
+    "## Debugging with `requests.get`\n",
+    "\n",
+    "If you want a simpler set of examples to debug, try the following. Whichever one you can\n",
+    "get to work in your environment, the corresponding solution from above should work too.\n",
+    "\n",
+    "Remember, you will need to get this to work for both the data URL and the map URL."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8de3da8b-8ea9-47d3-ab2d-b1ed179d0231",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "200"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "\n",
+    "# Do not ignore or replace the cert.\n",
+    "response = requests.get(\"https://api.census.gov\")\n",
+    "response.status_code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6cb71429-4e61-4db3-b58c-fa9ea3a8b1ff",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n",
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'www.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n",
+      "/Users/vengroff/Library/Caches/pypoetry/virtualenvs/censusdis-brFxk0td-py3.9/lib/python3.9/site-packages/urllib3/connectionpool.py:1103: InsecureRequestWarning: Unverified HTTPS request is being made to host 'www.census.gov'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "200"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Skip verification\n",
+    "response = requests.get(\"https://api.census.gov\", verify=False)\n",
+    "response.status_code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7b53bbc3-2212-46fc-bda7-4d9cacf4b0ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Could not find the TLS certificate file, invalid path: /path/to/certs/api-census.gov.pem\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Use a certificate file\n",
+    "try:\n",
+    "    response = requests.get(\"https://api.census.gov\", cert=data_cert)\n",
+    "    print(response.status_code)\n",
+    "except OSError as e:\n",
+    "    print(e)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43dafb0e-4616-4335-879e-91d3e69dbc72",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/poetry.lock b/poetry.lock
index e73a0f0b0..fc7ed3a43 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -473,13 +473,13 @@ test = ["pytest"]
 
 [[package]]
 name = "contextily"
-version = "1.5.2"
+version = "1.6.0"
 description = "Context geo-tiles in Python"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "contextily-1.5.2-py3-none-any.whl", hash = "sha256:d7dbf4228ecd42e58e2fa8559c550bdd7a9585ba6ba4f78a263ac60509a003d6"},
-    {file = "contextily-1.5.2.tar.gz", hash = "sha256:1cd9270b82433ae8211fe161428fc9c88a4a33b18a81df36ede897ea23486249"},
+    {file = "contextily-1.6.0-py3-none-any.whl", hash = "sha256:8a0900ac5cfcec0f4ae46b5d83fe176625355dfeff2376a66b6e61694c2fe9cb"},
+    {file = "contextily-1.6.0.tar.gz", hash = "sha256:8ab8ea9ec427c07960fae4964cfa6964b88c87546b97896422dbefc9fa8457f3"},
 ]
 
 [package.dependencies]
@@ -1086,13 +1086,13 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "7.0.2"
+version = "7.1.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_metadata-7.0.2-py3-none-any.whl", hash = "sha256:f4bc4c0c070c490abf4ce96d715f68e95923320370efb66143df00199bb6c100"},
-    {file = "importlib_metadata-7.0.2.tar.gz", hash = "sha256:198f568f3230878cb1b44fbd7975f87906c22336dba2e4a7f05278c281fbd792"},
+    {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
+    {file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
 ]
 
 [package.dependencies]
@@ -1101,17 +1101,17 @@ zipp = ">=0.5"
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
 [[package]]
 name = "importlib-resources"
-version = "6.3.1"
+version = "6.4.0"
 description = "Read resources from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_resources-6.3.1-py3-none-any.whl", hash = "sha256:4811639ca7fa830abdb8e9ca0a104dc6ad13de691d9fe0d3173a71304f068159"},
-    {file = "importlib_resources-6.3.1.tar.gz", hash = "sha256:29a3d16556e330c3c8fb8202118c5ff41241cc34cbfb25989bbad226d99b7995"},
+    {file = "importlib_resources-6.4.0-py3-none-any.whl", hash = "sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c"},
+    {file = "importlib_resources-6.4.0.tar.gz", hash = "sha256:cdb2b453b8046ca4e3798eb1d84f3cce1446a0e8e7b5ef4efb600f19fc398145"},
 ]
 
 [package.dependencies]
@@ -1119,7 +1119,7 @@ zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["jaraco.collections", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
+testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
 
 [[package]]
 name = "iniconfig"
@@ -1859,13 +1859,13 @@ test = ["black", "check-manifest", "flake8", "ipykernel", "ipython", "ipywidgets
 
 [[package]]
 name = "nbconvert"
-version = "7.16.2"
+version = "7.16.3"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "nbconvert-7.16.2.tar.gz", hash = "sha256:8310edd41e1c43947e4ecf16614c61469ebc024898eb808cce0999860fc9fb16"},
+    {file = "nbconvert-7.16.3-py3-none-any.whl", hash = "sha256:ddeff14beeeedf3dd0bc506623e41e4507e551736de59df69a91f86700292b3b"},
+    {file = "nbconvert-7.16.3.tar.gz", hash = "sha256:a6733b78ce3d47c3f85e504998495b07e6ea9cf9bf6ec1c98dda63ec6ad19142"},
 ]
 
 [package.dependencies]
@@ -1892,7 +1892,7 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
 webpdf = ["playwright"]
 
 [[package]]
@@ -2360,47 +2360,47 @@ tests = ["pytest"]
 
 [[package]]
 name = "pyarrow"
-version = "15.0.1"
+version = "15.0.2"
 description = "Python library for Apache Arrow"
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -3498,13 +3498,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "threadpoolctl"
-version = "3.3.0"
+version = "3.4.0"
 description = "threadpoolctl"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "threadpoolctl-3.3.0-py3-none-any.whl", hash = "sha256:6155be1f4a39f31a18ea70f94a77e0ccd57dced08122ea61109e7da89883781e"},
-    {file = "threadpoolctl-3.3.0.tar.gz", hash = "sha256:5dac632b4fa2d43f42130267929af3ba01399ef4bd1882918e92dbc30365d30c"},
+    {file = "threadpoolctl-3.4.0-py3-none-any.whl", hash = "sha256:8f4c689a65b23e5ed825c8436a92b818aac005e0f3715f6a1664d7c7ee29d262"},
+    {file = "threadpoolctl-3.4.0.tar.gz", hash = "sha256:f11b491a03661d6dd7ef692dd422ab34185d982466c49c8f98c8f716b5c93196"},
 ]
 
 [[package]]
diff --git a/pyproject.toml b/pyproject.toml
index ddbca5838..70f3ad90d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "censusdis"
 version = "1.1.4"
-description = "US Census utilities for a variety of data loading and mapping purposes."
+description = "US Census utilities for a variety of data loading, analysis, and mapping purposes."
 license = "HL3-CL-ECO-EXTR-FFD-LAW-MIL-SV"
 authors = ["Darren Vengroff"]
 readme = "README.md"


Test patch:
diff --git a/tests/test_cert_verify.py b/tests/test_cert_verify.py
new file mode 100644
index 000000000..3e62dbf24
--- /dev/null
+++ b/tests/test_cert_verify.py
@@ -0,0 +1,219 @@
+"""
+Test that we can pass verify and cert through our API to requests.get.
+
+The overall strategy here is to use `unittest.mock` to intercept calls
+to `requests.get` and make sure that the `cert` and `verify` arguments we
+pass in through public `censusdis` APIs make it down to them. Since these
+APIs typically end up making several calls to `requests.get`, we don't go
+to the trouble of trying to completely mock out their return values. Instead,
+we pass the arguments on to the real `requests.get` after filtering out
+the `cert` and `verify` arguments we just verified.
+
+These tests are designed to be run in an environment where `cert` and `verify`
+are not actually needed. In an environment where they are needed, things will
+probably fail as we filter them out before making the actual call.
+"""
+
+import unittest
+from contextlib import contextmanager
+from typing import Union, Optional, Tuple
+from unittest import mock
+
+import geopandas as gpd
+import pandas as pd
+from requests import Response
+from requests import get as requests_get
+
+import censusdis.data as ced
+from censusdis.datasets import ACS5
+
+
+@contextmanager
+def verify_requests_gets(
+    test_case,
+    *,
+    data_verify: Union[bool, str] = True,
+    data_cert: Optional[Union[str, Tuple[str, str]]] = None,
+    map_verify: Union[bool, str] = True,
+    map_cert: Optional[Union[str, Tuple[str, str]]] = None,
+):
+    """Verify that `cert` and `verify` flags make it down to `request.get` call in a context."""
+
+    def verified_requests_get(url: str, *args, **kwargs) -> Response:
+        """Verify that we got the verify and cert we expected, then return actual `requests.get` results."""
+        if url.startswith("https://api.census.gov"):
+            # This is the data case.
+
+            # Make sure it was set to what we set it to.
+            test_case.assertEqual(data_verify, ced.certificates.data_verify)
+            test_case.assertEqual(data_cert, ced.certificates.data_cert)
+            # Make sure the args came through.
+            test_case.assertEqual(data_verify, kwargs["verify"])
+            test_case.assertEqual(data_cert, kwargs["cert"])
+        elif url.startswith("https://www.census.gov") or url.startswith(
+            "https://www2.census.gov"
+        ):
+            # This is the map case.
+
+            # Make sure it was set to what we set it to.
+            test_case.assertEqual(map_verify, ced.certificates.map_verify)
+            test_case.assertEqual(map_cert, ced.certificates.map_cert)
+            # Make sure the args came through.
+            test_case.assertEqual(map_verify, kwargs["verify"])
+            test_case.assertEqual(map_cert, kwargs["cert"])
+        else:
+            test_case.fail(f"Unexpected URL {url}")
+
+        # Note we drop `verify` and `cert` here. Hopefully we are
+        # running tests in an environment where they are not
+        # needed.
+        kwargs2 = {k: v for k, v in kwargs.items() if k not in ["verify", "cert"]}
+        return requests_get(url, *args, **kwargs2)
+
+    with ced.certificates.use(
+        data_verify=data_verify,
+        data_cert=data_cert,
+        map_verify=map_verify,
+        map_cert=map_cert,
+    ):
+        with mock.patch("requests.get", side_effect=verified_requests_get):
+            yield
+
+
+class VerifyCertTestCase(unittest.TestCase):
+    """Test that we pass `verify` and `cert` from `ced.download` through to `requests.get`."""
+
+    def test_download_with_defaults(self) -> None:
+        """Make sure default cert and verify values are as expected in calls to `requests.get`."""
+        with verify_requests_gets(self):
+            df_states = ced.download(
+                dataset=ACS5,
+                vintage=2020,
+                download_variables="NAME",
+                state="*",
+            )
+
+            self.assertIsInstance(df_states, pd.DataFrame)
+            self.assertEqual((52, 2), df_states.shape)
+
+    def test_download_with_verify_false(self) -> None:
+        """Make sure a modified verify value is as expected in calls to `requests.get`."""
+        with verify_requests_gets(self, data_verify=False):
+            df_states = ced.download(
+                dataset=ACS5,
+                vintage=2020,
+                download_variables="NAME",
+                state="*",
+            )
+
+            self.assertIsInstance(df_states, pd.DataFrame)
+            self.assertEqual((52, 2), df_states.shape)
+
+    def test_download_with_cert(self) -> None:
+        """Make sure a modified cert value is as expected in calls to `requests.get`."""
+        cert = "THE_CERTIFICATE"
+
+        with verify_requests_gets(self, data_cert=cert):
+            df_states = ced.download(
+                dataset=ACS5,
+                vintage=2020,
+                download_variables="NAME",
+                state="*",
+            )
+
+            self.assertIsInstance(df_states, pd.DataFrame)
+            self.assertEqual((52, 2), df_states.shape)
+
+    def test_download_with_map_with_cert(self) -> None:
+        """Make sure a modified cert value is as expected in calls to `requests.get`."""
+        data_cert = "DATA_CERTIFICATE"
+        map_cert = "MAP_CERTIFICATE"
+
+        with verify_requests_gets(self, data_cert=data_cert, map_cert=map_cert):
+            gdf_states = ced.download(
+                dataset=ACS5,
+                vintage=2020,
+                download_variables="NAME",
+                state="*",
+                with_geometry=True,
+            )
+
+            self.assertIsInstance(gdf_states, gpd.GeoDataFrame)
+            self.assertEqual((52, 3), gdf_states.shape)
+
+    def test_wide_download_with_cert(self) -> None:
+        """Make sure the cert gets through multiples downloads."""
+        dataset = "acs/acs1/spp"
+        year = 2019
+        group = "S0201"
+
+        cert = "THE_CERTIFICATE"
+
+        with verify_requests_gets(self, data_cert=cert):
+            variables = ced.variables.group_variables(
+                dataset,
+                year,
+                group,
+                skip_annotations=False,
+            )
+
+            self.assertGreater(len(variables), ced._MAX_VARIABLES_PER_DOWNLOAD)
+
+            metrics_0 = ced._download_wide_strategy_metrics()
+
+            df = ced.download(dataset, year, variables, state="*")
+
+            self.assertEqual((51, 1 + len(variables)), df.shape)
+
+            metrics_1 = ced._download_wide_strategy_metrics()
+
+            metrics_diff = {k: v - metrics_0[k] for k, v in metrics_1.items()}
+
+            self.assertEqual(1, metrics_diff["merge"])
+            self.assertEqual(0, metrics_diff["concat"])
+
+    def test_metadata(self):
+        """Test that the metadata APIs pass cert correctly down the stack."""
+        cert = "THE_CERTIFICATE"
+
+        with verify_requests_gets(self, data_cert=cert):
+            df_all_datasets = ced.variables.all_data_sets()
+
+            self.assertEqual(5, len(df_all_datasets.columns))
+
+            df_groups = ced.variables.all_groups(ACS5, 2020)
+
+            self.assertEqual(4, len(df_groups.columns))
+
+            df_variables = ced.variables.all_variables(ACS5, 2020, "B03001")
+
+            self.assertEqual(7, len(df_variables.columns))
+
+
+class CertificateTestCase(unittest.TestCase):
+    """Test passing the correct certificates for the census servers."""
+
+    def _download_and_assert(self):
+        gdf_states = ced.download(
+            dataset=ACS5,
+            vintage=2020,
+            download_variables="NAME",
+            state="22",
+            with_geometry=True,
+        )
+
+        self.assertIsInstance(gdf_states, gpd.GeoDataFrame)
+        self.assertEqual((1, 3), gdf_states.shape)
+
+    def test_default(self):
+        """Test a normal download with no certificates."""
+        self._download_and_assert()
+
+    def test_no_verify(self):
+        """Test without verification on either the data or the map."""
+        with ced.certificates.use(data_verify=False, map_verify=False):
+            self._download_and_assert()
+
+
+if __name__ == "__main__":
+    unittest.main()