Question

我创建了一个使用远程模式的ApolloServer。远程模式需要一个授权令牌，我可以从请求中获取该令牌到我的apollo服务器。这是阿波罗服务器的代码。我可以在customFetch函数中对令牌进行硬编码，所有这些都可以，但是我想将调用时获得的令牌传递给服务器。

import {makeRemoteExecutableSchema, introspectSchema, mergeSchemas} from 'graphql-tools';
import {HttpLink} from 'apollo-link-http';
import {ApolloServer} from 'apollo-server';
import fetch from 'node-fetch';

// create executable schemas from remote GraphQL APIs
const customFetch = (uri, options) => {
  // How do I set the token from my server req??
  options.headers.Authorization =
    'Bearer eyJhbGciOiJIUzI1NiIsI Not A Real Token kf5iOg9SkxDBVtQnLJuz3hXEDA';
  return fetch(uri, options);
};

const createRemoteExecutableSchemas = async () => {
  let schemas = [];
  const link = new HttpLink({
    uri: 'http://remote.graphql.server:5555/graphql',
    fetch: customFetch,
  });
  const remoteSchema = await introspectSchema(link);
  const remoteExecutableSchema = makeRemoteExecutableSchema({
    schema: remoteSchema,
    link,
  });
  schemas.push(remoteExecutableSchema);
  return schemas;
};

const createNewSchema = async () => {
  const schemas = await createRemoteExecutableSchemas();
  return mergeSchemas({
    schemas,
  });
};

const runServer = async () => {
  const schema = await createNewSchema();
  const server = new ApolloServer({
    schema
  });
  server.listen().then(({url}) => {
    console.log(`  Server ready at ${url}`);
  });
};

try {
  runServer();
} catch (err) {
  console.error(err);
}

Answer 1

我自己为此苦了一段时间。尝试下一种方法：

import numpy as np
from numpy import log
from scipy.special import gammaln
from numba import njit
import numba as nb

@njit(fastmath=True,error_model='numpy')
def gammaln_nr(z):
    """Numerical Recipes 6.1"""
    #Don't use global variables.. (They only can be changed if you recompile the function)
    coefs = np.array([
    57.1562356658629235, -59.5979603554754912,
    14.1360979747417471, -0.491913816097620199,
    .339946499848118887e-4, .465236289270485756e-4,
    -.983744753048795646e-4, .158088703224912494e-3,
    -.210264441724104883e-3, .217439618115212643e-3,
    -.164318106536763890e-3, .844182239838527433e-4,
    -.261908384015814087e-4, .368991826595316234e-5])

    out=np.empty(z.shape[0])


    for i in range(z.shape[0]):
      y = z[i]
      tmp = z[i] + 5.24218750000000000
      tmp = (z[i] + 0.5) * np.log(tmp) - tmp
      ser = 0.999999999999997092

      n = coefs.shape[0]
      for j in range(n):
          y = y + 1.
          ser = ser + coefs[j] / y

      out[i] = tmp + log(2.5066282746310005 * ser / z[i])
    return out

@njit(fastmath=True,error_model='numpy',parallel=True)
def gammaln_nr_p(z):
    """Numerical Recipes 6.1"""
    #Don't use global variables.. (They only can be changed if you recompile the function)
    coefs = np.array([
    57.1562356658629235, -59.5979603554754912,
    14.1360979747417471, -0.491913816097620199,
    .339946499848118887e-4, .465236289270485756e-4,
    -.983744753048795646e-4, .158088703224912494e-3,
    -.210264441724104883e-3, .217439618115212643e-3,
    -.164318106536763890e-3, .844182239838527433e-4,
    -.261908384015814087e-4, .368991826595316234e-5])

    out=np.empty(z.shape[0])


    for i in nb.prange(z.shape[0]):
      y = z[i]
      tmp = z[i] + 5.24218750000000000
      tmp = (z[i] + 0.5) * np.log(tmp) - tmp
      ser = 0.999999999999997092

      n = coefs.shape[0]
      for j in range(n):
          y = y + 1.
          ser = ser + coefs[j] / y

      out[i] = tmp + log(2.5066282746310005 * ser / z[i])
    return out


import matplotlib.pyplot as plt
import seaborn as sns
import time

n_trials = 8
scipy_times = np.zeros(n_trials)
fastats_times = np.zeros(n_trials)
fastats_times_p = np.zeros(n_trials)

for i in range(n_trials):
    zs = np.linspace(0.001, 100, 10**i) # evaluate gammaln over this range

    # dont take first timing - this is just compilation
    start = time.time()
    arr_1=gammaln_nr(zs)
    end = time.time()

    start = time.time()
    arr_1=gammaln_nr(zs)
    end = time.time()
    fastats_times[i] = end - start

    start = time.time()
    arr_3=gammaln_nr_p(zs)
    end = time.time()
    fastats_times_p[i] = end - start
    start = time.time()

    start = time.time()
    arr_3=gammaln_nr_p(zs)
    end = time.time()
    fastats_times_p[i] = end - start
    start = time.time()

    arr_2=gammaln(zs)
    end = time.time()
    scipy_times[i] = end - start
    print(np.allclose(arr_1,arr_2))
    print(np.allclose(arr_1,arr_3))

fig, ax = plt.subplots(figsize=(12,8))
sns.lineplot(np.logspace(0, n_trials-1, n_trials), fastats_times, label="numba");
sns.lineplot(np.logspace(0, n_trials-1, n_trials), fastats_times_p, label="numba_parallel");
sns.lineplot(np.logspace(0, n_trials-1, n_trials), scipy_times, label="scipy");
ax.set(xscale="log");
ax.set_xlabel("Array Size", fontsize=15);
ax.set_ylabel("Execution Time (s)", fontsize=15);
ax.set_title("Execution Time of Log Gamma");
fig.show()

Apollo服务器：如何将授权令牌传递到远程架构

1 个答案: