json转csv

import re

# csv格式
# 'k1,k2,k3\nv1,v2,v3\nv4,v5,v6\n'

market_list_data = {
    "data": [
        {
            "finance_mic": "SS",
            "finance_name": "上海证券交易所"
        },
        {
            "finance_mic": "SZ",
            "finance_name": "深圳证券交易所"
        },
        {
            "finance_mic": "CCFX",
            "finance_name": "中国金融期货交易所"
        }
    ]
}

tick_data = {
  "data": {
    "tick": {
      "fields": [
        "business_time", 
        "hq_px", 
        "business_amount", 
        "business_balance", 
        "business_count", 
        "business_direction"
      ], 
      "600570.SS": [
        [
          20150907092501, 
          41.58, 
          13000378, 
          540555717, 
          0, 
          0
        ], 
        [
          20150907093000, 
          42.1, 
          148300, 
          6254573, 
          0, 
          1
        ]
      ]
    }
  }
}

kline_data = {
  "data": {
    "candle": {
      "fields": [
        "min_time",
        "open_px",
        "high_px",
        "low_px",
        "close_px"
      ],
      "600570.SS": [
        [
          201501061401,
          54890,
          54890,
          54600,
          54600
        ],
        [
          201501061402,
          54610,
          54610,
          54400,
          54400
        ]
      ]
    }
  }
}

trend_data = {
  "data": {
    "trend": {
      "fields": [
        "min_time",
        "last_px",
        "avg_px",
        "business_amount"
      ],
      "600570.SS": [
        [
          201501090930,
          54.98,
          54.98,
          28327
        ],
        [
          201501090931,
          54.63,
          54.829486,
          49700
        ]
      ]
    }
  }
}

real_data = {
  "data": {
    "snapshot": {
      "fields": [
        "data_timestamp",
        "shares_per_hand",
        "open_px",
        "high_px",
        "low_px",
        "last_px",
        "business_amount",
        "business_balance",
        "offer_grp",
        "bid_grp"
      ],
      "600570.SS": [
        150305133,
        100,
        53980,
        56000,
        52510,
        54950,
        14465811,
        788995643,
        "54850,9887,0,54860,1500,0,54900,13300,0,54950,10000,0,54990,800,0,",
        "54820,8000,0,54810,2100,0,54800,202900,0,54770,100,0,54720,1200,0,"
      ],
      "000001.SZ": [
        153229327,
        100,
        15560,
        15830,
        15300,
        15480,
        170012067,
        2634796408,
        "15490,93700,0,15500,260609,0,15510,69996,0,15520,87008,0,15530,71400,0,",
        "15480,438292,0,15470,149000,0,15460,411400,0,15450,414573,0,15440,303733,0,"
      ]
    }
  }
}

trend5day_data = {
  "data": {
    "trend": {
      "fields": [
        "min_time",
        "last_px",
        "avg_px",
        "business_amount",
        "business_balance"
      ],
      "600570.SS": [
        [
          201504170931,
          124.07,
          124.83,
          387955,
          48426658
        ],
        [
          201504170932,
          123.01,
          124.59,
          572900,
          71378859
        ],
        [
          201504170933,
          121.89,
          123.94,
          834100,
          103378268
        ],
        [
          201504170934,
          122.44,
          123.74,
          941239,
          116465390
        ]
      ]
    }
  }
}


def one_prod_to_csv(data):
    csv = ''

    # head
    csv = csv + ','.join(data.get('fields')) + '\n'
    
    # body
    for item in data.keys():
        if not item is 'fields':
            body_key = item

    body_data = data.get(body_key)

    for item in body_data:
        new_item = []
        for v in item:
            new_item.append(re.sub(r',', '|', str(v)))
        csv = csv + ','.join(new_item) + '\n'

    return csv

def multi_prod_to_csv(data):
    csv = ''

    # head
    csv = csv + ','.join(data.get('fields')) + '\n'

    # body
    for k,v in data.items():
        if not k is 'fields':
            new_v = []
            for item in v:
                new_v.append(re.sub(r',', '|', str(item)))
            csv = csv + ','.join(new_v) + '\n'

    return csv

def dict_to_csv(data):
    csv = ''

    head_data = []
    body_data = []

    for item in data[0].keys():
        head_data.append(item)

    # head
    csv = csv + ','.join(head_data) + '\n'

    # body
    for item in data:
        new_item = []
        for k,v in item.items():
            new_item.append(v)
        body_data.append(new_item)

    for item in body_data:
        csv = csv + ','.join(item) + '\n'

    return csv


def market_list_to_csv(data):
    return dict_to_csv(data)

def tick_to_csv(data):
    return one_prod_to_csv(data)

def kline_to_csv(data):
    return one_prod_to_csv(data)

def trend5day_to_csv(data):
    return one_prod_to_csv(data)

def trend_to_csv(data):
    return one_prod_to_csv(data)

def real_to_csv(data):
    return multi_prod_to_csv(data)


print(market_list_to_csv(market_list_data.get('data')))
print(tick_to_csv(tick_data.get('data').get('tick')))
print(kline_to_csv(kline_data.get('data').get('candle')))
print(trend5day_to_csv(trend5day_data.get('data').get('trend')))
print(trend_to_csv(trend_data.get('data').get('trend')))
print(real_to_csv(real_data.get('data').get('snapshot')))